Development of LiDAR aware allometrics for Abies grandis: A Case Study

NASA Astrophysics Data System (ADS)

Stone, G. A.; Tinkham, W. T.; Smith, A. M.; Hudak, A. T.; Falkowski, M. J.; Keefe, R.

2012-12-01

Forest managers rely increasingly on accurate allometric relationships to inform decisions regarding stand rotations, silvilcultural treatments, timber harvesting, and biometric modeling. At the same time, advances in remote sensing techniques like LiDAR (light detection and ranging) have brought about opportunities to advance how we assess forest growth, and thus are contributing to the need for more accurate allometries. Past studies have attempted to relate LiDAR data to both plot and individual tree measures of forest biomass. However, many of these studies have been limited by the accuracy of their coincident observations. In this study, 24 Abies grandis were measured, felled, and dissected for the explicit objective of developing LiDAR aware allometrics. The analysis predicts spatial variables of competition, growth potential (e.g, trees per acre, aspect, elevation, etc.) and common statistical distributional metrics (e.g., mean, mode, percentiles, variance, skewness, kurtosis, etc.) derived from LiDAR point cloud returns to coincident in situ measures of Abies grandis stem biomass. The resulting allometries exemplify a new approach for predicting structural attributes of interest (biomass, basal area, volume, etc.) directly from LiDAR point cloud data, precluding the measurement errors that are propogated by indirectly predicting these structure attributes of interest from LiDAR data using traditional plot-based measurements.

Comparative Genomics Analyses Reveal Extensive Chromosome Colinearity and Novel Quantitative Trait Loci in Eucalyptus.

PubMed

Li, Fagen; Zhou, Changpin; Weng, Qijie; Li, Mei; Yu, Xiaoli; Guo, Yong; Wang, Yu; Zhang, Xiaohong; Gan, Siming

2015-01-01

Dense genetic maps, along with quantitative trait loci (QTLs) detected on such maps, are powerful tools for genomics and molecular breeding studies. In the important woody genus Eucalyptus, the recent release of E. grandis genome sequence allows for sequence-based genomic comparison and searching for positional candidate genes within QTL regions. Here, dense genetic maps were constructed for E. urophylla and E. tereticornis using genomic simple sequence repeats (SSR), expressed sequence tag (EST) derived SSR, EST-derived cleaved amplified polymorphic sequence (EST-CAPS), and diversity arrays technology (DArT) markers. The E. urophylla and E. tereticornis maps comprised 700 and 585 markers across 11 linkage groups, totaling at 1,208.2 and 1,241.4 cM in length, respectively. Extensive synteny and colinearity were observed as compared to three earlier DArT-based eucalypt maps (two maps with E. grandis × E. urophylla and one map of E. globulus) and with the E. grandis genome sequence. Fifty-three QTLs for growth (10-56 months of age) and wood density (56 months) were identified in 22 discrete regions on both maps, in which only one colocalizaiton was found between growth and wood density. Novel QTLs were revealed as compared with those previously detected on DArT-based maps for similar ages in Eucalyptus. Eleven to 585 positional candidate genes were obained for a 56-month-old QTL through aligning QTL confidence interval with the E. grandis genome. These results will assist in comparative genomics studies, targeted gene characterization, and marker-assisted selection in Eucalyptus and the related taxa.

Comparative Genomics Analyses Reveal Extensive Chromosome Colinearity and Novel Quantitative Trait Loci in Eucalyptus

PubMed Central

Weng, Qijie; Li, Mei; Yu, Xiaoli; Guo, Yong; Wang, Yu; Zhang, Xiaohong; Gan, Siming

2015-01-01

Dense genetic maps, along with quantitative trait loci (QTLs) detected on such maps, are powerful tools for genomics and molecular breeding studies. In the important woody genus Eucalyptus, the recent release of E. grandis genome sequence allows for sequence-based genomic comparison and searching for positional candidate genes within QTL regions. Here, dense genetic maps were constructed for E. urophylla and E. tereticornis using genomic simple sequence repeats (SSR), expressed sequence tag (EST) derived SSR, EST-derived cleaved amplified polymorphic sequence (EST-CAPS), and diversity arrays technology (DArT) markers. The E. urophylla and E. tereticornis maps comprised 700 and 585 markers across 11 linkage groups, totaling at 1,208.2 and 1,241.4 cM in length, respectively. Extensive synteny and colinearity were observed as compared to three earlier DArT-based eucalypt maps (two maps with E. grandis × E. urophylla and one map of E. globulus) and with the E. grandis genome sequence. Fifty-three QTLs for growth (10–56 months of age) and wood density (56 months) were identified in 22 discrete regions on both maps, in which only one colocalizaiton was found between growth and wood density. Novel QTLs were revealed as compared with those previously detected on DArT-based maps for similar ages in Eucalyptus. Eleven to 585 positional candidate genes were obained for a 56-month-old QTL through aligning QTL confidence interval with the E. grandis genome. These results will assist in comparative genomics studies, targeted gene characterization, and marker-assisted selection in Eucalyptus and the related taxa. PMID:26695430

SEIR model simulation for Hepatitis B

NASA Astrophysics Data System (ADS)

Side, Syafruddin; Irwan, Mulbar, Usman; Sanusi, Wahidah

2017-09-01

Mathematical modelling and simulation for Hepatitis B discuss in this paper. Population devided by four variables, namely: Susceptible, Exposed, Infected and Recovered (SEIR). Several factors affect the population in this model is vaccination, immigration and emigration that occurred in the population. SEIR Model obtained Ordinary Differential Equation (ODE) non-linear System 4-D which then reduces to 3-D. SEIR model simulation undertaken to predict the number of Hepatitis B cases. The results of the simulation indicates the number of Hepatitis B cases will increase and then decrease for several months. The result of simulation using the number of case in Makassar also found the basic reproduction number less than one, that means, Makassar city is not an endemic area of Hepatitis B. With approval from the proceedings editor article 020185 titled, "SEIR model simulation for Hepatitis B," is retracted from the public record, as it is a duplication of article 020198 published in the same volume.

Assessing the Transferability of Statistical Predictive Models for Leaf Area Index Between Two Airborne Discrete Return LiDAR Sensor Designs Within Multiple Intensely Managed Loblolly Pine Forest Locations in the South-Eastern USA

NASA Technical Reports Server (NTRS)

Sumnall, Matthew; Peduzzi, Alicia; Fox, Thomas R.; Wynne, Randolph H.; Thomas, Valerie A.; Cook, Bruce

2016-01-01

Leaf area is an important forest structural variable which serves as the primary means of mass and energy exchange within vegetated ecosystems. The objective of the current study was to determine if leaf area index (LAI) could be estimated accurately and consistently in five intensively managed pine plantation forests using two multiple-return airborne LiDAR datasets. Field measurements of LAI were made using the LiCOR LAI2000 and LAI2200 instruments within 116 plots were established of varying size and within a variety of stand conditions (i.e. stand age, nutrient regime and stem density) in North Carolina and Virginia in 2008 and 2013. A number of common LiDAR return height and intensity distribution metrics were calculated (e.g. average return height), in addition to ten indices, with two additional variants, utilized in the surrounding literature which have been used to estimate LAI and fractional cover, were calculated from return heights and intensity, for each plot extent. Each of the indices was assessed for correlation with each other, and was used as independent variables in linear regression analysis with field LAI as the dependent variable. All LiDAR derived metrics were also entered into a forward stepwise linear regression. The results from each of the indices varied from an R2 of 0.33 (S.E. 0.87) to 0.89 (S.E. 0.36). Those indices calculated using ratios of all returns produced the strongest correlations, such as the Above and Below Ratio Index (ABRI) and Laser Penetration Index 1 (LPI1). The regression model produced from a combination of three metrics did not improve correlations greatly (R2 0.90; S.E. 0.35). The results indicate that LAI can be predicted over a range of intensively managed pine plantation forest environments accurately when using different LiDAR sensor designs. Those indices which incorporated counts of specific return numbers (e.g. first returns) or return intensity correlated poorly with field measurements. There were disparities between the number of different types of returns and intensity values when comparing the results from two LiDAR sensors, indicating that predictive models developed using such metrics are not transferable between datasets with different acquisition parameters. Each of the indices were significantly correlated with one another, with one exception (LAI proxy), in particular those indices calculated from all returns, which indicates similarities in information content for those indices. It can then be argued that LiDAR indices have reached a similar stage in development to those calculated from optical-spectral sensors, but which offer a number of advantages, such as the reduction or removal of saturation issues in areas of high biomass.

Temporal Analysis and Automatic Calibration of the Velodyne HDL-32E LiDAR System

NASA Astrophysics Data System (ADS)

Chan, T. O.; Lichti, D. D.; Belton, D.

2013-10-01

At the end of the first quarter of 2012, more than 600 Velodyne LiDAR systems had been sold worldwide for various robotic and high-accuracy survey applications. The ultra-compact Velodyne HDL-32E LiDAR has become a predominant sensor for many applications that require lower sensor size/weight and cost. For high accuracy applications, cost-effective calibration methods with minimal manual intervention are always desired by users. However, the calibrations are complicated by the Velodyne LiDAR's narrow vertical field of view and the very highly time-variant nature of its measurements. In the paper, the temporal stability of the HDL-32E is first analysed as the motivation for developing a new, automated calibration method. This is followed by a detailed description of the calibration method that is driven by a novel segmentation method for extracting vertical cylindrical features from the Velodyne point clouds. The proposed segmentation method utilizes the Velodyne point cloud's slice-like nature and first decomposes the point clouds into 2D layers. Then the layers are treated as 2D images and are processed with the Generalized Hough Transform which extracts the points distributed in circular patterns from the point cloud layers. Subsequently, the vertical cylindrical features can be readily extracted from the whole point clouds based on the previously extracted points. The points are passed to the calibration that estimates the cylinder parameters and the LiDAR's additional parameters simultaneously by constraining the segmented points to fit to the cylindrical geometric model in such a way the weighted sum of the adjustment residuals are minimized. The proposed calibration is highly automatic and this allows end users to obtain the time-variant additional parameters instantly and frequently whenever there are vertical cylindrical features presenting in scenes. The methods were verified with two different real datasets, and the results suggest that up to 78.43% accuracy improvement for the HDL-32E can be achieved using the proposed calibration method.

A SEIR model for transmission of tuberculosis

NASA Astrophysics Data System (ADS)

Side, Syafruddin; Mulbar, Usman; Sidjara, Sahlan; Sanusi, Wahidah

2017-04-01

In this paper will be described Tuberculosis (TB) transmission using Susceptible-Exposed-Infected-Recovered (SEIR) model. SEIR model for transmission of TB were analyzed and performed simulations using data on the number of TB cases in South Sulawesi. The results showed that the levels of the basic reproduction ratio R0 using the model of SEIR is R0 ≤ 1, it means that the status of TB disease in South Sulawesi is at a stage that is not alarming, but based on simulation results using MatLab, predicted that the number of infection cases will continue to increase therefore government needs to take preventive measures to control and reduce the number of TB infections in South Sulawesi.

Mapping of High Value Crops Through AN Object-Based Svm Model Using LIDAR Data and Orthophoto in Agusan del Norte Philippines

NASA Astrophysics Data System (ADS)

Candare, Rudolph Joshua; Japitana, Michelle; Cubillas, James Earl; Ramirez, Cherry Bryan

2016-06-01

This research describes the methods involved in the mapping of different high value crops in Agusan del Norte Philippines using LiDAR. This project is part of the Phil-LiDAR 2 Program which aims to conduct a nationwide resource assessment using LiDAR. Because of the high resolution data involved, the methodology described here utilizes object-based image analysis and the use of optimal features from LiDAR data and Orthophoto. Object-based classification was primarily done by developing rule-sets in eCognition. Several features from the LiDAR data and Orthophotos were used in the development of rule-sets for classification. Generally, classes of objects can't be separated by simple thresholds from different features making it difficult to develop a rule-set. To resolve this problem, the image-objects were subjected to Support Vector Machine learning. SVMs have gained popularity because of their ability to generalize well given a limited number of training samples. However, SVMs also suffer from parameter assignment issues that can significantly affect the classification results. More specifically, the regularization parameter C in linear SVM has to be optimized through cross validation to increase the overall accuracy. After performing the segmentation in eCognition, the optimization procedure as well as the extraction of the equations of the hyper-planes was done in Matlab. The learned hyper-planes separating one class from another in the multi-dimensional feature-space can be thought of as super-features which were then used in developing the classifier rule set in eCognition. In this study, we report an overall classification accuracy of greater than 90% in different areas.

SEIR model simulation for Hepatitis B

NASA Astrophysics Data System (ADS)

Side, Syafruddin; Irwan, Mulbar, Usman; Sanusi, Wahidah

2017-09-01

Mathematical modelling and simulation for Hepatitis B discuss in this paper. Population devided by four variables, namely: Susceptible, Exposed, Infected and Recovered (SEIR). Several factors affect the population in this model is vaccination, immigration and emigration that occurred in the population. SEIR Model obtained Ordinary Differential Equation (ODE) non-linear System 4-D which then reduces to 3-D. SEIR model simulation undertaken to predict the number of Hepatitis B cases. The results of the simulation indicates the number of Hepatitis B cases will increase and then decrease for several months. The result of simulation using the number of case in Makassar also found the basic reproduction number less than one, that means, Makassar city is not an endemic area of Hepatitis B.

Students' Experiences and Challenges of Blended Learning at the University of Dar Es Salaam, Tanzania

ERIC Educational Resources Information Center

Mtebe, Joel S.; Raphael, Christina

2013-01-01

Recent developments in Information and Communication Technologies (ICTs), especially eLearning, have heightened the need for University of Dar es Salaam (UDSM) to supplement on-campus face-to-face delivery as well as meeting increased students' enrolments through blended distance learning. Since 2008, the University has been offering three…

Correlated patterns in hydrothermal plume distribution and apparent magmatic budget along 2500 km of the Southeast Indian Ridge

USGS Publications Warehouse

Baker, Edward; Christophe Hémond,; Anne Briais,; Marcia Maia,; Scheirer, Daniel S.; Sharon L. Walker,; Tingting Wang,; Yongshun John Chen,

2014-01-01

Multiple geological processes affect the distribution of hydrothermal venting along a mid-ocean ridge. Deciphering the role of a specific process is often frustrated by simultaneous changes in other influences. Here we take advantage of the almost constant spreading rate (65–71 mm/yr) along 2500 km of the Southeast Indian Ridge (SEIR) between 77°E and 99°E to examine the spatial density of hydrothermal venting relative to regional and segment-scale changes in the apparent magmatic budget. We use 227 vertical profiles of light backscatter and (on 41 profiles) oxidation-reduction potential along 27 first and second-order ridge segments on and adjacent to the Amsterdam-St. Paul (ASP) Plateau to map ph, the fraction of casts detecting a plume. At the regional scale, venting on the five segments crossing the magma-thickened hot spot plateau is almost entirely suppressed (ph = 0.02). Conversely, the combined ph (0.34) from all other segments follows the global trend of ph versus spreading rate. Off the ASP Plateau, multisegment trends in ph track trends in the regional axial depth, high where regional depth increases and low where it decreases. At the individual segment scale, a robust correlation between ph and cross-axis inflation for first-order segments shows that different magmatic budgets among first-order segments are expressed as different levels of hydrothermal spatial density. This correlation is absent among second-order segments. Eighty-five percent of the plumes occur in eight clusters totaling ∼350 km. We hypothesize that these clusters are a minimum estimate of the length of axial melt lenses underlying this section of the SEIR.

Correlated patterns in hydrothermal plume distribution and apparent magmatic budget along 2500 km of the Southeast Indian Ridge

NASA Astrophysics Data System (ADS)

Baker, Edward T.; Hémond, Christophe; Briais, Anne; Maia, Marcia; Scheirer, Daniel S.; Walker, Sharon L.; Wang, Tingting; Chen, Yongshun John

2014-08-01

Multiple geological processes affect the distribution of hydrothermal venting along a mid-ocean ridge. Deciphering the role of a specific process is often frustrated by simultaneous changes in other influences. Here we take advantage of the almost constant spreading rate (65-71 mm/yr) along 2500 km of the Southeast Indian Ridge (SEIR) between 77°E and 99°E to examine the spatial density of hydrothermal venting relative to regional and segment-scale changes in the apparent magmatic budget. We use 227 vertical profiles of light backscatter and (on 41 profiles) oxidation-reduction potential along 27 first and second-order ridge segments on and adjacent to the Amsterdam-St. Paul (ASP) Plateau to map ph, the fraction of casts detecting a plume. At the regional scale, venting on the five segments crossing the magma-thickened hot spot plateau is almost entirely suppressed (ph = 0.02). Conversely, the combined ph (0.34) from all other segments follows the global trend of ph versus spreading rate. Off the ASP Plateau, multisegment trends in ph track trends in the regional axial depth, high where regional depth increases and low where it decreases. At the individual segment scale, a robust correlation between ph and cross-axis inflation for first-order segments shows that different magmatic budgets among first-order segments are expressed as different levels of hydrothermal spatial density. This correlation is absent among second-order segments. Eighty-five percent of the plumes occur in eight clusters totaling ˜350 km. We hypothesize that these clusters are a minimum estimate of the length of axial melt lenses underlying this section of the SEIR.

Calculation of the overlap factor for scanning LiDAR based on the tridimensional ray-tracing method.

PubMed

Chen, Ruiqiang; Jiang, Yuesong; Wen, Luhong; Wen, Donghai

2017-06-01

The overlap factor is used to evaluate the LiDAR light collection ability. Ranging LiDAR is mainly determined by the optical configuration. However, scanning LiDAR, equipped with a scanning mechanism to acquire a 3D coordinate points cloud for a specified target, is essential in considering the scanning effect at the same time. Otherwise, scanning LiDAR will reduce the light collection ability and even cannot receive any echo. From this point of view, we propose a scanning LiDAR overlap factor calculation method based on the tridimensional ray-tracing method, which can be applied to scanning LiDAR with any special laser intensity distribution, any type of telescope (reflector, refractor, or mixed), and any shape obstruction (i.e., the reflector of a coaxial optical system). A case study for our LiDAR with a scanning mirror is carried out, and a MATLAB program is written to analyze the laser emission and reception process. Sensitivity analysis is carried out as a function of scanning mirror rotation speed and detector position, and the results guide how to optimize the overlap factor for our LiDAR. The results of this research will have a guiding significance in scanning LiDAR design and assembly.

Quantifying tropical dry forest type and succession: substantial improvement with LiDAR

Treesearch

Sebastian Martinuzzi; William A. Gould; Lee A. Vierling; Andrew T. Hudak; Ross F. Nelson; Jeffrey S. Evans

2012-01-01

Improved technologies are needed to advance our knowledge of the biophysical and human factors influencing tropical dry forests, one of the world’s most threatened ecosystems. We evaluated the use of light detection and ranging (LiDAR) data to address two major needs in remote sensing of tropical dry forests, i.e., classification of forest types and delineation of...

Application of Airborne Hydrographic Laser Scanning for Mapping Shallow Water Riverine Environments in the Pacific Northwest, United States

NASA Astrophysics Data System (ADS)

Cooper, C.; Nayegandhi, A.; Faux, R.

2013-12-01

Small-footprint, green wavelength airborne LiDAR systems can provide seamless topography across the land-water interface at very high spatial resolution. These data have the potential to improve floodplain modeling, fisheries habitat assessments, stream restoration efforts, and other applications by continuously mapping shallow water depths that are difficult or impossible to measure using traditional ground-based or water-borne survey techniques. WSI (Corvallis, Oregon) in collaboration with Dewberry, (Tampa, Florida) and Riegl (Orlando, Florida), deployed the Riegl VQ-820-G hydrographic airborne laser scanner to map riverine and lacustrine environments from Oregon to Minnesota. Discussion will focus on the ability to accurately map depth and underwater structure, as well as riparian vegetation and terrain under different conditions. Results indicate that depth penetration varies with both water (i.e. clarity and surface conditions) and bottom conditions (i.e. substrate, depth, and landform). Depth penetration was typically limited to 1 Secchi depth or less across selected project areas. As an example, the green LiDAR system effectively mapped 83% of a shallow water river system, the Sandy River, with typical depths ranging from 0-2.5 meters. WSI will show quantitative comparisons of Green LiDAR surveys against more traditional methods such as rod or sonar surveys. WSI will also discuss advantages and limitations of Green LiDAR surveys for bathymetric modeling including survey accuracy, density, and efficiency along with data processing challenges not inherent with traditional NIR LiDAR processing.

Periodic array-based substrates for surface-enhanced infrared spectroscopy

NASA Astrophysics Data System (ADS)

Mayerhöfer, Thomas G.; Popp, Jürgen

2018-01-01

At the beginning of the 1980s, the first reports of surface-enhanced infrared spectroscopy (SEIRS) surfaced. Probably due to signal-enhancement factors of only 101 to 103, which are modest compared to those of surface-enhanced Raman spectroscopy (SERS), SEIRS did not reach the same significance up to date. However, taking the compared to Raman scattering much larger cross-sections of infrared absorptions and the enhancement factors together, SEIRS reaches about the same sensitivity for molecular species on a surface in terms of the cross-sections as SERS and, due to the complementary nature of both techniques, can valuably augment information gained by SERS. For the first 20 years since its discovery, SEIRS relied completely on metal island films, fabricated by either vapor or electrochemical deposition. The resulting films showed a strong variance concerning their structure, which was essentially random. Therefore, the increase in the corresponding signal-enhancement factors of these structures stagnated in the last years. In the very same years, however, the development of periodic array-based substrates helped SEIRS to gather momentum. This development was supported by technological progress concerning electromagnetic field solvers, which help to understand plasmonic properties and allow targeted design. In addition, the strong progress concerning modern fabrication methods allowed to implement these designs into practice. The aim of this contribution is to critically review the development of these engineered surfaces for SEIRS, to compare the different approaches with regard to their performance where possible, and report further gain of knowledge around and in relation to these structures.

Evaluation of the dimensions of anger reactions-5 (DAR-5) scale in combat veterans with posttraumatic stress disorder.

PubMed

Forbes, David; Alkemade, Nathan; Hopcraft, Dale; Hawthorne, Graeme; O'Halloran, Paul; Elhai, Jon D; McHugh, Tony; Bates, Glen; Novaco, Raymond W; Bryant, Richard; Lewis, Virginia

2014-12-01

After a traumatic event many people experience problems with anger which not only results in significant distress, but can also impede recovery. As such, there is value to include the assessment of anger in routine post-trauma screening procedures. The Dimensions of Anger Reactions-5 (DAR-5), as a concise measure of anger, was designed to meet such a need, its brevity minimizing the burden on client and practitioner. This study examined the psychometric properties of the DAR-5 with a sample of 163 male veterans diagnosed with Posttraumatic Stress Disorder. The DAR-5 demonstrated internal reliability (α=.86), along with convergent, concurrent and discriminant validity against a variety of established measures (e.g., HADS, PCL, STAXI). Support for the clinical cut-point score of 12 suggested by Forbes et al. (2014, Utility of the dimensions of anger reactions-5 (DAR-5) scale as a brief anger measure. Depression and Anxiety, 31, 166-173) was observed. The results support considering the DAR-5 as a preferred screening and assessment measure of problematic anger. Copyright © 2014 Elsevier Ltd. All rights reserved.

Qualitative and numerical investigations of the impact of a novel pathogen on a seabird colony

NASA Astrophysics Data System (ADS)

O'Regan, S. M.; Kelly, T. C.; Korobeinikov, A.; O'Callaghan, M. J. A.; Pokrovskii, A. V.

2008-11-01

Understanding the dynamics of novel pathogens in dense populations is crucial to public and veterinary health as well as wildlife ecology. Seabirds live in crowded colonies numbering several thousands of individuals. The long-term dynamics of avian influenza H5N1 virus in a seabird colony with no existing herd immunity are investigated using sophisticated mathematical techniques. The key characteristics of seabird population biology and the H5N1 virus are incorporated into a Susceptible-Exposed-Infected-Recovered (SEIR) model. Using the theory of integral manifolds, the SEIR model is reduced to a simpler system of two differential equations depending on the infected and recovered populations only, termed the IR model. The results of numerical experiments indicate that the IR model and the SEIR model are in close agreement. Using Lyapunov's direct method, the equilibria of the SEIR and the IR models are proven to be globally asymptotically stable in the positive quadrant.

Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping.

PubMed

Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

2016-12-31

For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.

Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping

PubMed Central

Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

2016-01-01

For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable. PMID:28042855

Integration of airborne LiDAR data and voxel-based ray tracing to determine high-resolution solar radiation dynamics at the forest floor: implications for improving stand-scale distributed snowmelt models

NASA Astrophysics Data System (ADS)

Musselman, K. N.; Molotch, N. P.; Margulis, S. A.

2012-12-01

Forest architecture dictates sub-canopy solar irradiance and the resulting patterns can vary seasonally and over short spatial distances. These radiation dynamics are thought to have significant implications on snowmelt processes, regional hydrology, and remote sensing signatures. The variability calls into question many assumptions inherent in traditional canopy models (e.g. Beer's Law) when applied at high resolution (i.e. 1 m). We present a method of estimating solar canopy transmissivity using airborne LiDAR data. The canopy structure is represented in 3-D voxel space (i.e. a cubic discretization of a 3-D domain analogous to a pixel representation of a 2-D space). The solar direct beam canopy transmissivity (DBT) is estimated with a ray-tracing algorithm and the diffuse component is estimated from LiDAR-derived effective LAI. Results from one year at five-minute temporal and 1 m spatial resolutions are presented from Sequoia National Park. Compared to estimates from 28 hemispherical photos, the ray-tracing model estimated daily mean DBT with a 10% average error, while the errors from a Beer's-type DBT estimate exceeded 20%. Compared to the ray-tracing estimates, the Beer's-type transmissivity method was unable to resolve complex spatial patterns resulting from canopy gaps, individual tree canopies and boles, and steep variable terrain. The snowmelt model SNOWPACK was applied at locations of ultrasonic snow depth sensors. Two scenarios were tested; 1) a nominal case where canopy model parameters were obtained from hemispherical photographs, and 2) an explicit scenario where the model was modified to accept LiDAR-derived time-variant DBT. The bulk canopy treatment was generally unable to simulate the sub-canopy snowmelt dynamics observed at the depth sensor locations. The explicit treatment reduced error in the snow disappearance date by one week and both positive and negative melt-season SWE biases were reduced. The results highlight the utility of LiDAR canopy measurements and physically based snowmelt models to simulate spatially distributed stand- and slope-scale snowmelt dynamics at resolutions necessary to capture the inherent underlying variability.iDAR-derived solar direct beam canopy transmissivity computed as the daily average for March 1st and May 1st.

Bayesian inference in an extended SEIR model with nonparametric disease transmission rate: an application to the Ebola epidemic in Sierra Leone.

PubMed

Frasso, Gianluca; Lambert, Philippe

2016-10-01

SummaryThe 2014 Ebola outbreak in Sierra Leone is analyzed using a susceptible-exposed-infectious-removed (SEIR) epidemic compartmental model. The discrete time-stochastic model for the epidemic evolution is coupled to a set of ordinary differential equations describing the dynamics of the expected proportions of subjects in each epidemic state. The unknown parameters are estimated in a Bayesian framework by combining data on the number of new (laboratory confirmed) Ebola cases reported by the Ministry of Health and prior distributions for the transition rates elicited using information collected by the WHO during the follow-up of specific Ebola cases. The time-varying disease transmission rate is modeled in a flexible way using penalized B-splines. Our framework represents a valuable stochastic tool for the study of an epidemic dynamic even when only irregularly observed and possibly aggregated data are available. Simulations and the analysis of the 2014 Sierra Leone Ebola data highlight the merits of the proposed methodology. In particular, the flexible modeling of the disease transmission rate makes the estimation of the effective reproduction number robust to the misspecification of the initial epidemic states and to underreporting of the infectious cases. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The distribution of near-axis seamounts at intermediate spreading ridges

NASA Astrophysics Data System (ADS)

Howell, J. K.; Bohnenstiehl, D. R.; White, S. M.; Supak, S. K.

2008-12-01

The ridge axes along the intermediate-spreading rate Galapagos Spreading Center (GSC, 46-56 mm/yr) and South East Indian Ridge (SEIR, 72-76 mm/yr) vary from rifted axial valleys to inflated axial highs independent of spreading rate. The delivery and storage of melt is believed to control axial morphology, with axial highs typically observed in areas underlain by a shallow melt lens and axial valleys in areas without a significant melt lens [e.g., Baran et al., 2005 G-cubed; Detrick et al. 2002 G-cubed]. To investigate a possible correlation between the style of seafloor volcanism and axial morphology, a closed contour algorithm is used to identify near axis (2.5km off axis) semi-circular seamounts of heights greater than 20m from shipboard multibeam bathymetry. In areas characterized by an axial high, more seamounts are formed at the ends of the segments than in the center. This is consistent with observations at fast-spreading ridges and suggests a tendency of lavas to erupt at lower effusion rates near second-order segment boundaries. Segments with a rift valley along the GSC show the opposite trend, with more seamounts at the center of second-order segments. Both patterns however are observed along SEIR segments with rift valleys where magma supply may be reflected in size and not their abundance.

Clustering of Multispectral Airborne Laser Scanning Data Using Gaussian Decomposition

NASA Astrophysics Data System (ADS)

Morsy, S.; Shaker, A.; El-Rabbany, A.

2017-09-01

With the evolution of the LiDAR technology, multispectral airborne laser scanning systems are currently available. The first operational multispectral airborne LiDAR sensor, the Optech Titan, acquires LiDAR point clouds at three different wavelengths (1.550, 1.064, 0.532 μm), allowing the acquisition of different spectral information of land surface. Consequently, the recent studies are devoted to use the radiometric information (i.e., intensity) of the LiDAR data along with the geometric information (e.g., height) for classification purposes. In this study, a data clustering method, based on Gaussian decomposition, is presented. First, a ground filtering mechanism is applied to separate non-ground from ground points. Then, three normalized difference vegetation indices (NDVIs) are computed for both non-ground and ground points, followed by histograms construction from each NDVI. The Gaussian function model is used to decompose the histograms into a number of Gaussian components. The maximum likelihood estimate of the Gaussian components is then optimized using Expectation - Maximization algorithm. The intersection points of the adjacent Gaussian components are subsequently used as threshold values, whereas different classes can be clustered. This method is used to classify the terrain of an urban area in Oshawa, Ontario, Canada, into four main classes, namely roofs, trees, asphalt and grass. It is shown that the proposed method has achieved an overall accuracy up to 95.1 % using different NDVIs.

The Registration and Segmentation of Heterogeneous Laser Scanning Data

NASA Astrophysics Data System (ADS)

Al-Durgham, Mohannad M.

Light Detection And Ranging (LiDAR) mapping has been emerging over the past few years as a mainstream tool for the dense acquisition of three dimensional point data. Besides the conventional mapping missions, LiDAR systems have proven to be very useful for a wide spectrum of applications such as forestry, structural deformation analysis, urban mapping, and reverse engineering. The wide application scope of LiDAR lead to the development of many laser scanning technologies that are mountable on multiple platforms (i.e., airborne, mobile terrestrial, and tripod mounted), this caused variations in the characteristics and quality of the generated point clouds. As a result of the increased popularity and diversity of laser scanners, one should address the heterogeneous LiDAR data post processing (i.e., registration and segmentation) problems adequately. Current LiDAR integration techniques do not take into account the varying nature of laser scans originating from various platforms. In this dissertation, the author proposes a methodology designed particularly for the registration and segmentation of heterogeneous LiDAR data. A data characterization and filtering step is proposed to populate the points' attributes and remove non-planar LiDAR points. Then, a modified version of the Iterative Closest Point (ICP), denoted by the Iterative Closest Projected Point (ICPP) is designed for the registration of heterogeneous scans to remove any misalignments between overlapping strips. Next, a region-growing-based heterogeneous segmentation algorithm is developed to ensure the proper extraction of planar segments from the point clouds. Validation experiments show that the proposed heterogeneous registration can successfully align airborne and terrestrial datasets despite the great differences in their point density and their noise level. In addition, similar testes have been conducted to examine the heterogeneous segmentation and it is shown that one is able to identify common planar features in airborne and terrestrial data without resampling or manipulating the data in any way. The work presented in this dissertation provides a framework for the registration and segmentation of airborne and terrestrial laser scans which has a positive impact on the completeness of the scanned feature. Therefore, the derived products from these point clouds have higher accuracy as seen in the full manuscript.

Mapping canopy defoliation by herbivorous insects at the individual tree level using bi-temporal airborne imaging spectroscopy and LiDAR measurements

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

Meng, Ran; Dennison, Philip E.; Zhao, Feng

Defoliation by herbivorous insects is a widespread forest disturbance driver, affecting global forest health and ecosystem dynamics. Additionally, compared with time- and labor-intensive field surveys, remote sensing provides the only realistic approach to mapping canopy defoliation by herbivorous insects over large spatial and temporal scales. However, the spectral and structural signatures of defoliation by insects at the individual tree level have not been well studied. Additionally, the predictive power of spectral and structural metrics for mapping canopy defoliation has seldom been compared. These critical knowledge gaps prevent us from consistently detecting and mapping canopy defoliation by herbivorous insects across multiplemore » scales. During the peak of a gypsy moth outbreak in Long Island, New York in summer 2016, we leveraged bi-temporal airborne imaging spectroscopy (IS, i.e., hyperspectral imaging) and LiDAR measurements at 1m spatial resolution to explore the spectral and structural signatures of canopy defoliation in a mixed oak-pine forest. We determined that red edge and near-infrared spectral regions within the IS data were most sensitive to crown-scale defoliation severity. LiDAR measurements including B70 (i.e., 70th bincentile height), intensity skewness, and kurtosis were effectively able to detect structural changes caused by herbivorous insects. In addition to canopy leaf loss, increased exposure of understory and non-photosynthetic materials contributed to the detected spectral and structural signatures. Comparing the ability of individual sensors to map canopy defoliation, the LiDAR-only Ordinary Least-Square (OLS) model performed better than the IS-only model (Adj. R-squared = 0.77, RMSE = 15.37% vs. Adj. R- squared = 0.63, RMSE = 19.11%). The IS+LiDAR model improved on performance of the individual sensors (Adj. R-squared = 0.81, RMSE = 14.46%). Our study improves our understanding of spectral and structural signatures of defoliation by herbivorous insects and presents a novel approach for mapping insect defoliation at the individual tree level. Furthermore, with the current and next generation of spaceborne sensors (e.g., WorldView-3, Landsat, Sentinel-2, HyspIRI, and GEDI), higher accuracy and frequent monitoring of insect defoliation may become more feasible across a range of spatial scales, which are critical for ecological research and management of forest resources including the economic consequences of forest insect infestations (e.g., reduced growth and increased mortality), as well as for informing and testing of carbon cycle models.« less

Mapping canopy defoliation by herbivorous insects at the individual tree level using bi-temporal airborne imaging spectroscopy and LiDAR measurements

DOE PAGES

Meng, Ran; Dennison, Philip E.; Zhao, Feng; ...

2018-06-19

Defoliation by herbivorous insects is a widespread forest disturbance driver, affecting global forest health and ecosystem dynamics. Additionally, compared with time- and labor-intensive field surveys, remote sensing provides the only realistic approach to mapping canopy defoliation by herbivorous insects over large spatial and temporal scales. However, the spectral and structural signatures of defoliation by insects at the individual tree level have not been well studied. Additionally, the predictive power of spectral and structural metrics for mapping canopy defoliation has seldom been compared. These critical knowledge gaps prevent us from consistently detecting and mapping canopy defoliation by herbivorous insects across multiplemore » scales. During the peak of a gypsy moth outbreak in Long Island, New York in summer 2016, we leveraged bi-temporal airborne imaging spectroscopy (IS, i.e., hyperspectral imaging) and LiDAR measurements at 1m spatial resolution to explore the spectral and structural signatures of canopy defoliation in a mixed oak-pine forest. We determined that red edge and near-infrared spectral regions within the IS data were most sensitive to crown-scale defoliation severity. LiDAR measurements including B70 (i.e., 70th bincentile height), intensity skewness, and kurtosis were effectively able to detect structural changes caused by herbivorous insects. In addition to canopy leaf loss, increased exposure of understory and non-photosynthetic materials contributed to the detected spectral and structural signatures. Comparing the ability of individual sensors to map canopy defoliation, the LiDAR-only Ordinary Least-Square (OLS) model performed better than the IS-only model (Adj. R-squared = 0.77, RMSE = 15.37% vs. Adj. R- squared = 0.63, RMSE = 19.11%). The IS+LiDAR model improved on performance of the individual sensors (Adj. R-squared = 0.81, RMSE = 14.46%). Our study improves our understanding of spectral and structural signatures of defoliation by herbivorous insects and presents a novel approach for mapping insect defoliation at the individual tree level. Furthermore, with the current and next generation of spaceborne sensors (e.g., WorldView-3, Landsat, Sentinel-2, HyspIRI, and GEDI), higher accuracy and frequent monitoring of insect defoliation may become more feasible across a range of spatial scales, which are critical for ecological research and management of forest resources including the economic consequences of forest insect infestations (e.g., reduced growth and increased mortality), as well as for informing and testing of carbon cycle models.« less

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

NASA Technical Reports Server (NTRS)

Gastellu-Etchegorry, Jean-Philippe; Yin, Tiangang; Lauret, Nicolas; Grau, Eloi; Rubio, Jeremy; Cook, Bruce D.; Morton, Douglas C.; Sun, Guoqing

2016-01-01

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

47 CFR 25.403 - Bidding application and certification procedures.

Code of Federal Regulations, 2010 CFR

2010-10-01

... CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.403 Bidding...'s name; (b) Mailing Address (no Post Office boxes); (c) City; (d) State; (e) ZIP Code; (f) Auction...

47 CFR 25.403 - Bidding application and certification procedures.

Code of Federal Regulations, 2011 CFR

2011-10-01

... CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.403 Bidding...'s name; (b) Mailing Address (no Post Office boxes); (c) City; (d) State; (e) ZIP Code; (f) Auction...

Preliminary Results from an Hydroacoustic Experiment in the Indian Ocean

NASA Astrophysics Data System (ADS)

Royer, J.; Dziak, R. P.; Delatre, M.; Brachet, C.; Haxel, J. H.; Matsumoto, H.; Goslin, J.; Brandon, V.; Bohnenstiehl, D. R.; Guinet, C.; Samaran, F.

2008-12-01

We report initial results from a 14-month hydroacoustic experiment in the Indian Ocean conducted by CNRS/University of Brest and NOAA/Oregon State University. The objective was to monitor the low-level seismic activity associated with the three contrasting spreading ridges and deforming zones in the Indian Ocean. Three autonomous hydrophones, moored in the SOFAR channel, were deployed in October 2006 and recovered early 2008 by R/V Marion Dufresne, in the Madagascar Basin, and northeast and southwest of Amsterdam Island, complementing the two permanent hydroacoustic stations of the Comprehensive nuclear-Test-Ban Treaty Organization (CTBTO) located near Diego Garcia Island and off Cape Leeuwin. Our temporary network detected more than 2000 events. Inside the array, we located 592 events (compared to 49 in the NEIC earthquake catalog) with location errors less than 5 km and time error less than 2s. The hydrophone array detected on average 5 to 40 times more events per month than land-based networks. First-order observations indicate that hydroacoustic seismicity along the Southeast Indian ridge (SEIR) occurs predominantly along the transform faults. The Southwest Indian Ridge exhibits some periodicity in earthquake activity between adjacent ridge segments. Two large tectonic/volcanic earthquake swarms are observed along the Central Indian Ridge (near the triple junction) in September and December 2007. Moreover, many off ridge-axis events are also observed both south and north of the SEIR axis. Improved localization using the CTBTO records will help refine these preliminary results and further investigate extended volcanic sequences along the SEIR east of 80°E and other events outside of the temporary array. The records also display numerous vocalizations of baleen whales in the 20-40Hz bandwidth. The calls are attributed to fin whales, Antarctic blue whales and pygmy blue whales of Madagascar and Australian type. Their vocal activity is found to be highly seasonal, occurring mainly from April to October with subspecies variations. This array thus provides a unique data set to improve our understanding of the seismic activity in this region and to establish the occurrence and migration pattern of critically endangered whale species.

Object-based habitat mapping using very high spatial resolution multispectral and hyperspectral imagery with LiDAR data

NASA Astrophysics Data System (ADS)

Onojeghuo, Alex Okiemute; Onojeghuo, Ajoke Ruth

2017-07-01

This study investigated the combined use of multispectral/hyperspectral imagery and LiDAR data for habitat mapping across parts of south Cumbria, North West England. The methodology adopted in this study integrated spectral information contained in pansharp QuickBird multispectral/AISA Eagle hyperspectral imagery and LiDAR-derived measures with object-based machine learning classifiers and ensemble analysis techniques. Using the LiDAR point cloud data, elevation models (such as the Digital Surface Model and Digital Terrain Model raster) and intensity features were extracted directly. The LiDAR-derived measures exploited in this study included Canopy Height Model, intensity and topographic information (i.e. mean, maximum and standard deviation). These three LiDAR measures were combined with spectral information contained in the pansharp QuickBird and Eagle MNF transformed imagery for image classification experiments. A fusion of pansharp QuickBird multispectral and Eagle MNF hyperspectral imagery with all LiDAR-derived measures generated the best classification accuracies, 89.8 and 92.6% respectively. These results were generated with the Support Vector Machine and Random Forest machine learning algorithms respectively. The ensemble analysis of all three learning machine classifiers for the pansharp QuickBird and Eagle MNF fused data outputs did not significantly increase the overall classification accuracy. Results of the study demonstrate the potential of combining either very high spatial resolution multispectral or hyperspectral imagery with LiDAR data for habitat mapping.

Genomic Characterization of DArT Markers Based on High-Density Linkage Analysis and Physical Mapping to the Eucalyptus Genome

PubMed Central

Petroli, César D.; Sansaloni, Carolina P.; Carling, Jason; Steane, Dorothy A.; Vaillancourt, René E.; Myburg, Alexander A.; da Silva, Orzenil Bonfim; Pappas, Georgios Joannis; Kilian, Andrzej; Grattapaglia, Dario

2012-01-01

Diversity Arrays Technology (DArT) provides a robust, high throughput, cost-effective method to query thousands of sequence polymorphisms in a single assay. Despite the extensive use of this genotyping platform for numerous plant species, little is known regarding the sequence attributes and genome-wide distribution of DArT markers. We investigated the genomic properties of the 7,680 DArT marker probes of a Eucalyptus array, by sequencing them, constructing a high density linkage map and carrying out detailed physical mapping analyses to the Eucalyptus grandis reference genome. A consensus linkage map with 2,274 DArT markers anchored to 210 microsatellites and a framework map, with improved support for ordering, displayed extensive collinearity with the genome sequence. Only 1.4 Mbp of the 75 Mbp of still unplaced scaffold sequence was captured by 45 linkage mapped but physically unaligned markers to the 11 main Eucalyptus pseudochromosomes, providing compelling evidence for the quality and completeness of the current Eucalyptus genome assembly. A highly significant correspondence was found between the locations of DArT markers and predicted gene models, while most of the 89 DArT probes unaligned to the genome correspond to sequences likely absent in E. grandis, consistent with the pan-genomic feature of this multi-Eucalyptus species DArT array. These comprehensive linkage-to-physical mapping analyses provide novel data regarding the genomic attributes of DArT markers in plant genomes in general and for Eucalyptus in particular. DArT markers preferentially target the gene space and display a largely homogeneous distribution across the genome, thereby providing superb coverage for mapping and genome-wide applications in breeding and diversity studies. Data reported on these ubiquitous properties of DArT markers will be particularly valuable to researchers working on less-studied crop species who already count on DArT genotyping arrays but for which no reference genome is yet available to allow such detailed characterization. PMID:22984541

D-arabinose metabolism in Escherichia coli B: induction and cotransductional mapping of the L-fucose-D-arabinose pathway enzymes.

PubMed

Elsinghorst, E A; Mortlock, R P

1988-12-01

D-Arabinose is degraded by Escherichia coli B via some of the L-fucose pathway enzymes and a D-ribulokinase which is distinct from the L-fuculokinase of the L-fucose pathway. We found that L-fucose and D-arabinose acted as the apparent inducers of the enzymes needed for their degradation. These enzymes, including D-ribulokinase, appeared to be coordinately regulated, and mutants which constitutively synthesized the L-fucose enzymes also constitutively synthesized D-ribulokinase. In contrast to D-arabinose-positive mutants of E. coli K-12, in which L-fuculose-1-phosphate and D-ribulose-1-phosphate act as inducers of the L-fucose pathway, we found that these intermediates did not act as inducers in E. coli B. To further characterize the E. coli B system, some of the L-fucose-D-arabinose genes were mapped by using bacteriophage P1 transduction. A transposon Tn10 insertion near the E. coli B L-fucose regulon was used in two- and three-factor reciprocal crosses. The gene encoding D-ribulokinase, designated darK, was found to map within the L-fucose regulon, and the partial gene order was found to be Tn10-fucA-darK-fucI-fucK-thyA.

D-arabinose metabolism in Escherichia coli B: induction and cotransductional mapping of the L-fucose-D-arabinose pathway enzymes.

PubMed Central

Elsinghorst, E A; Mortlock, R P

1988-01-01

D-Arabinose is degraded by Escherichia coli B via some of the L-fucose pathway enzymes and a D-ribulokinase which is distinct from the L-fuculokinase of the L-fucose pathway. We found that L-fucose and D-arabinose acted as the apparent inducers of the enzymes needed for their degradation. These enzymes, including D-ribulokinase, appeared to be coordinately regulated, and mutants which constitutively synthesized the L-fucose enzymes also constitutively synthesized D-ribulokinase. In contrast to D-arabinose-positive mutants of E. coli K-12, in which L-fuculose-1-phosphate and D-ribulose-1-phosphate act as inducers of the L-fucose pathway, we found that these intermediates did not act as inducers in E. coli B. To further characterize the E. coli B system, some of the L-fucose-D-arabinose genes were mapped by using bacteriophage P1 transduction. A transposon Tn10 insertion near the E. coli B L-fucose regulon was used in two- and three-factor reciprocal crosses. The gene encoding D-ribulokinase, designated darK, was found to map within the L-fucose regulon, and the partial gene order was found to be Tn10-fucA-darK-fucI-fucK-thyA. PMID:3056899

LiDAR Applications in Resource Geology and Benefits for Land Management

NASA Astrophysics Data System (ADS)

Mikulovsky, R. P.; De La Fuente, J. A.

2013-12-01

The US Forest Service (US Department of Agriculture) manages a broad range of geologic resources and hazards on National Forests and Grass Lands throughout the United States. Resources include rock and earth materials, groundwater, caves and paleontological resources, minerals, energy resources, and unique geologic areas. Hazards include landslides, floods, earthquakes, volcanic eruptions, and naturally hazardous materials (e.g., asbestos, radon). Forest Service Geologists who address these issues are Resource Geologists. They have been exploring LiDAR as a revolutionary tool to efficiently manage all of these hazards and resources. However, most LiDAR applications for management have focused on timber and fuels management, rather than landforms. This study shows the applications and preliminary results of using LiDAR for managing geologic resources and hazards on public lands. Applications shown include calculating sediment budgets, mapping and monitoring landslides, mapping and characterizing borrow pits or mines, determining landslide potential, mapping faults, and characterizing groundwater dependent ecosystems. LiDAR can be used to model potential locations of groundwater dependent ecosystems with threatened or endangered plant species such as Howellia aquatilis. This difficult to locate species typically exists on the Mendocino National Forest within sag ponds on landslide benches. LiDAR metrics of known sites are used to model potential habitat. Thus LiDAR can link the disciplines of geology, hydrology, botany, archaeology and others for enhanced land management. As LiDAR acquisition costs decrease and it becomes more accessible, land management organizations will find a wealth of applications with potential far-reaching benefits for managing geologic resources and hazards.

Delineation of peatland lagg boundaries from airborne LiDAR

NASA Astrophysics Data System (ADS)

Langlois, Melanie N.; Richardson, Murray C.; Price, Jonathan S.

2017-09-01

In Canada, peatlands are the most common type of wetland, but boundary delineation in peatland complexes has received little attention in the scientific literature. Typically, peatland boundaries are mapped as crisp, absolute features, and the transitional lagg zone—the ecotone found between a raised bog and the surrounding mineral land—is often overlooked. In this study, we aim (1) to advance existing approaches for detecting and locating laggs and lagg boundaries using airborne LiDAR surveys and (2) to describe the spatial distribution of laggs around raised bog peatlands. Two contrasting spatial analytical approaches for lagg detection were tested using five LiDAR-derived topographic and vegetation indices: topography, vegetation height, topographic wetness index, the standard deviation of the vegetation's height (as a proxy for the complexity of the vegetation's structure), and local indices of elevation variance. Using a dissimilarity approach (edge-detection, split-moving window analysis), no one variable accurately depicted both the lagg-mineral land and bog-lagg boundaries. Some indicators were better at predicting the bog-lagg boundary (i.e., vegetation height) and others at finding the lagg-mineral land boundary (i.e., topography). Dissimilarity analysis reinforces the usefulness of derived variables (e.g., wetness indices) in locating laggs, especially for those with weak topographic and vegetation gradients. When the lagg was confined between the bog and the adjacent upland, it took a linear form, parallel to the peatland's edge and was easier to predict. When the adjacent mineral land was flat or sloping away from the peatland, the lagg was discontinuous and intermittent and more difficult to predict.

Bridging gaps: On the performance of airborne LiDAR to model wood mouse-habitat structure relationships in pine forests.

PubMed

Jaime-González, Carlos; Acebes, Pablo; Mateos, Ana; Mezquida, Eduardo T

2017-01-01

LiDAR technology has firmly contributed to strengthen the knowledge of habitat structure-wildlife relationships, though there is an evident bias towards flying vertebrates. To bridge this gap, we investigated and compared the performance of LiDAR and field data to model habitat preferences of wood mouse (Apodemus sylvaticus) in a Mediterranean high mountain pine forest (Pinus sylvestris). We recorded nine field and 13 LiDAR variables that were summarized by means of Principal Component Analyses (PCA). We then analyzed wood mouse's habitat preferences using three different models based on: (i) field PCs predictors, (ii) LiDAR PCs predictors; and (iii) both set of predictors in a combined model, including a variance partitioning analysis. Elevation was also included as a predictor in the three models. Our results indicate that LiDAR derived variables were better predictors than field-based variables. The model combining both data sets slightly improved the predictive power of the model. Field derived variables indicated that wood mouse was positively influenced by the gradient of increasing shrub cover and negatively affected by elevation. Regarding LiDAR data, two LiDAR PCs, i.e. gradients in canopy openness and complexity in forest vertical structure positively influenced wood mouse, although elevation interacted negatively with the complexity in vertical structure, indicating wood mouse's preferences for plots with lower elevations but with complex forest vertical structure. The combined model was similar to the LiDAR-based model and included the gradient of shrub cover measured in the field. Variance partitioning showed that LiDAR-based variables, together with elevation, were the most important predictors and that part of the variation explained by shrub cover was shared. LiDAR derived variables were good surrogates of environmental characteristics explaining habitat preferences by the wood mouse. Our LiDAR metrics represented structural features of the forest patch, such as the presence and cover of shrubs, as well as other characteristics likely including time since perturbation, food availability and predation risk. Our results suggest that LiDAR is a promising technology for further exploring habitat preferences by small mammal communities.

Aerosols in coastal and inland areas in the equatorial African belt.

PubMed

Ssenyonga, Taddeo; Muyimbwa, Dennis; Okullo, Willy; Chen, Yi-Chun; Frette, Øvyind; Hamre, Børge; Steigen, Andreas; Dahlback, Arne; Stamnes, Jakob J

2014-05-10

Aerosols affect the climate directly through absorption and reflection of sunlight back to space and indirectly by acting as cloud condensation nuclei. This paper is based on more than three decades of satellite data (1979-1994 and 1996-2012) from total ozone mapping spectrometer (TOMS) and ozone monitoring instrument (OMI), which have provided measurements of backscattered radiances in the wavelength range from 331 to 380 nm. These data have been used to determine the aerosol climatology and to investigate the influence of the aerosol index (AI) on the ultraviolet index (UVI) in coastal land areas in Serrekunda (13.28°N, 16.34°W), The Gambia, and Dar-es-Salaam (6.8°S, 39.26°E), Tanzania, as well as in inland areas in Kampala (0.19°N, 32.34°E), Uganda. Heavy aerosol loadings were found to occur in the dry seasons at all three locations. To reduce the influence of clouds, we disregarded TOMS and OMI data for days during which the UV reflectivity was larger than 9% and investigated the correlation of the AI with the UVI for the remaining days at the three locations. We found a high correlation coefficient of 0.82 for Serrekunda, but poor correlation for Kampala and Dar-es-Salaam. The average AI for Serrekunda was found to be about three times higher than that for Kampala or Dar-es-Salaam, and a positive trend was found for the AI in Kampala and Dar-es-Salaam, whereas a negative trend was found for the AI in Serrekunda.

SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Deng, Yan-Bin; Huang, Yong-Chang

2017-10-01

Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network. Supported by National Natural Science Foundation of China under Grant Nos. 11275017 and 11173028

A new SEIR epidemic model with applications to the theory of eradication and control of diseases, and to the calculation of R0.

PubMed

Huang, Sen-Zhong

2008-09-01

We present a novel SEIR (susceptible-exposure-infective-recovered) model that is suitable for modeling the eradication of diseases by mass vaccination or control of diseases by case isolation combined with contact tracing, incorporating the vaccine efficacy or the control efficacy into the model. Moreover, relying on this novel SEIR model and some probabilistic arguments, we have found four formulas that are suitable for estimating the basic reproductive numbers R(0) in terms of the ratio of the mean infectious period to the mean latent period of a disease. The ranges of R(0) for most known diseases, that are calculated by our formulas, coincide very well with the values of R(0) estimated by the usual method of fitting the models to observed data.

Urban Classification Techniques Using the Fusion of LiDAR and Spectral Data

DTIC Science & Technology

2012-09-01

Photogrammetry and Remote Sensing, 62, 43–63. Stein, D., Beaven, S., Hoff, L., Winter, E., Schaum, A., & Stocker, A. (2002). Anomaly detection from...TECHNIQUES USING THE FUSION OF LIDAR AND SPECTRAL DATA by Justin E. Mesina September 2012 Thesis Advisor: Richard C . Olsen Second...from shadow anomalies . The fused results however, were not as accurate in differentiating trees from grasses as using only spectral results. Overall the

Analysis of Particulates in the Exhaust Plume of a TF30 Engine at Military Power.

DTIC Science & Technology

1984-05-01

DIADAH-LCA (2) flHDAR LCAI1’ 2, D)AfI-L(:E (21 DRtDAR-LCE-C. Cieistry Branch (1 DRtDAB-LCE-D (2) D1IDAR-LCNI (2) DRDAR-LCM-SA. R. Westerdahl (1) DRDAR...DRDAR-LCM-SA, R. Westerdahl (1) DBRDAR-LCN-C, Concepts and Analysis Branch (4) DRDAR-LCU (2) DFIDAB-LCU-E (1) 4 Army Ballistic Research Laboratory

Flying Under the LiDAR: Relating Forest Structure to Bat Community Diversity

NASA Astrophysics Data System (ADS)

Swanson, A. C.; Weishampel, J. F.

2015-12-01

Bats are important to many ecological processes such as pollination, insect (and by proxy, disease) control, and seed dispersal and can be used to monitor ecosystem health. However, they are facing unprecedented extinction risks from habitat degradation as well as pressures from pathogens (e.g., white-nose syndrome) and wind turbines. LiDAR allows ecologists to measure structural variables of forested landscapes with increased precision and accuracy at broader spatial scales than previously possible. This study used airborne LiDAR to classify forest habitat/canopy structure at the Ordway-Swisher Biological Station (OSBS) in north central Florida. LiDAR data were acquired by the NEON airborne observation platform in summer 2014. OSBS consists of open-canopy pine savannas, closed-canopy hardwood hammocks, and seasonally wet prairies. Multiple forest structural parameters (e.g., mean, maximum, and standard deviation of height returns) were derived from LiDAR point clouds using the USDA software program FUSION. K-means clustering was used to segregate each 5x5 m raster across the ~3765 ha OSBS area into six different clusters based on the derived canopy metrics. Cluster averages for maximum, mean, and standard deviation of return heights ranged from 0 to 19.4 m, 0 to 15.3 m, and 0 to 3.0 m, respectively. To determine the relationships among these landscape-canopy features and bat species diversity and abundances, AnaBat II bat detectors were deployed from May to September in 2015 stratified by these distinct clusters. Bat calls were recorded from sunset to sunrise during each sampling period. Species were identified using AnalookW. A statistical regression model selection approach was performed in order to evaluate how forest attributes such as understory clutter, open regions, open and closed canopy, etc. influence bat communities. This knowledge provides a deeper understanding of habitat-species interactions to better manage survival of these species.

elecTUM: Umsetzung der eLearning-Strategie der Technischen Universität München

NASA Astrophysics Data System (ADS)

Rathmayer, Sabine; Gergintchev, Ivan

An der TUM wurde ein umfassendes und integriertes eLearning-Konzept umgesetzt, welches Präsenzstudium und eLearning in allen Leistungsbereichen der Universität miteinander verzahnt. Ein besonderer Schwerpunkt lag dabei in der Schaffung einer effizienten und wettbewerbsfähigen integrierten eLearning Infrastruktur in Hinblick auf die noch weiter steigenden Studienanfängerzahlen ab dem Jahr 2011 sowie die Umsetzung von eBologna. Die Etablierung einer hochschulweiten Lernplattform stellte eine wesentliche Basis für die Umsetzung der eLearning-Strategie dar. Die wissenschaftliche und wirtschaftliche Anschlussfähigkeit im Hinblick auf eine Verwertung der Projektergebnisse wurde durch die aktive Beteiligung an einer Vielzahl hochschulübergreifender Arbeitskreise, Fachtagungen und Kooperationen, vor allem über Organisations- und Dienstleistungsmodelle sowie innovative technische Entwicklungen, sichergestellt.

Approximate Bayesian computation for spatial SEIR(S) epidemic models.

PubMed

Brown, Grant D; Porter, Aaron T; Oleson, Jacob J; Hinman, Jessica A

2018-02-01

Approximate Bayesia n Computation (ABC) provides an attractive approach to estimation in complex Bayesian inferential problems for which evaluation of the kernel of the posterior distribution is impossible or computationally expensive. These highly parallelizable techniques have been successfully applied to many fields, particularly in cases where more traditional approaches such as Markov chain Monte Carlo (MCMC) are impractical. In this work, we demonstrate the application of approximate Bayesian inference to spatially heterogeneous Susceptible-Exposed-Infectious-Removed (SEIR) stochastic epidemic models. These models have a tractable posterior distribution, however MCMC techniques nevertheless become computationally infeasible for moderately sized problems. We discuss the practical implementation of these techniques via the open source ABSEIR package for R. The performance of ABC relative to traditional MCMC methods in a small problem is explored under simulation, as well as in the spatially heterogeneous context of the 2014 epidemic of Chikungunya in the Americas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulating the water budget of a Prairie Potholes complex from LiDAR and hydrological models in North Dakota, USA

USGS Publications Warehouse

Huang, Shengli; Young, Claudia; Abdul-Aziz, Omar I.; Dahal, Devendra; Feng, Min; Liu, Shuguang

2013-01-01

Hydrological processes of the wetland complex in the Prairie Pothole Region (PPR) are difficult to model, partly due to a lack of wetland morphology data. We used Light Detection And Ranging (LiDAR) data sets to derive wetland features; we then modelled rainfall, snowfall, snowmelt, runoff, evaporation, the “fill-and-spill” mechanism, shallow groundwater loss, and the effect of wet and dry conditions. For large wetlands with a volume greater than thousands of cubic metres (e.g. about 3000 m3), the modelled water volume agreed fairly well with observations; however, it did not succeed for small wetlands (e.g. volume less than 450 m3). Despite the failure for small wetlands, the modelled water area of the wetland complex coincided well with interpretation of aerial photographs, showing a linear regression with R2 of around 0.80 and a mean average error of around 0.55 km2. The next step is to improve the water budget modelling for small wetlands.

Buildings classification from airborne LiDAR point clouds through OBIA and ontology driven approach

NASA Astrophysics Data System (ADS)

Tomljenovic, Ivan; Belgiu, Mariana; Lampoltshammer, Thomas J.

2013-04-01

In the last years, airborne Light Detection and Ranging (LiDAR) data proved to be a valuable information resource for a vast number of applications ranging from land cover mapping to individual surface feature extraction from complex urban environments. To extract information from LiDAR data, users apply prior knowledge. Unfortunately, there is no consistent initiative for structuring this knowledge into data models that can be shared and reused across different applications and domains. The absence of such models poses great challenges to data interpretation, data fusion and integration as well as information transferability. The intention of this work is to describe the design, development and deployment of an ontology-based system to classify buildings from airborne LiDAR data. The novelty of this approach consists of the development of a domain ontology that specifies explicitly the knowledge used to extract features from airborne LiDAR data. The overall goal of this approach is to investigate the possibility for classification of features of interest from LiDAR data by means of domain ontology. The proposed workflow is applied to the building extraction process for the region of "Biberach an der Riss" in South Germany. Strip-adjusted and georeferenced airborne LiDAR data is processed based on geometrical and radiometric signatures stored within the point cloud. Region-growing segmentation algorithms are applied and segmented regions are exported to the GeoJSON format. Subsequently, the data is imported into the ontology-based reasoning process used to automatically classify exported features of interest. Based on the ontology it becomes possible to define domain concepts, associated properties and relations. As a consequence, the resulting specific body of knowledge restricts possible interpretation variants. Moreover, ontologies are machinable and thus it is possible to run reasoning on top of them. Available reasoners (FACT++, JESS, Pellet) are used to check the consistency of the developed ontologies, and logical reasoning is performed to infer implicit relations between defined concepts. The ontology for the definition of building is specified using the Ontology Web Language (OWL). It is the most widely used ontology language that is based on Description Logics (DL). DL allows the description of internal properties of modelled concepts (roof typology, shape, area, height etc.) and relationships between objects (IS_A, MEMBER_OF/INSTANCE_OF). It captures terminological knowledge (TBox) as well as assertional knowledge (ABox) - that represents facts about concept instances, i.e. the buildings in airborne LiDAR data. To assess the classification accuracy, ground truth data generated by visual interpretation and calculated classification results in terms of precision and recall are used. The advantages of this approach are: (i) flexibility, (ii) transferability, and (iii) extendibility - i.e. ontology can be extended with further concepts, data properties and object properties.

Effects of Reduced Terrestrial LiDAR Point Density on High-Resolution Grain Crop Surface Models in Precision Agriculture

PubMed Central

Hämmerle, Martin; Höfle, Bernhard

2014-01-01

3D geodata play an increasingly important role in precision agriculture, e.g., for modeling in-field variations of grain crop features such as height or biomass. A common data capturing method is LiDAR, which often requires expensive equipment and produces large datasets. This study contributes to the improvement of 3D geodata capturing efficiency by assessing the effect of reduced scanning resolution on crop surface models (CSMs). The analysis is based on high-end LiDAR point clouds of grain crop fields of different varieties (rye and wheat) and nitrogen fertilization stages (100%, 50%, 10%). Lower scanning resolutions are simulated by keeping every n-th laser beam with increasing step widths n. For each iteration step, high-resolution CSMs (0.01 m2 cells) are derived and assessed regarding their coverage relative to a seamless CSM derived from the original point cloud, standard deviation of elevation and mean elevation. Reducing the resolution to, e.g., 25% still leads to a coverage of >90% and a mean CSM elevation of >96% of measured crop height. CSM types (maximum elevation or 90th-percentile elevation) react differently to reduced scanning resolutions in different crops (variety, density). The results can help to assess the trade-off between CSM quality and minimum requirements regarding equipment and capturing set-up. PMID:25521383

Studies on the synthesis, spectra, catalytic and antibacterial activities of binuclear ruthenium(II) complexes.

PubMed

Krishnamoorthy, P; Sathyadevi, P; Deepa, K; Dharmaraj, N

2010-09-15

A new series of stable binuclear ruthenium(II) carbonyl complexes of the general formula [{RuX(CO)(EPh(3))(2)}(2)L] (where X=H or Cl; E=P or As and L=dibasic tetradentate diacetyl resorcinol (H(2)-DAR)) have been synthesised by reacting ruthenium(II) starting complexes [RuHX(CO)(EPh(3))(3)] (where X=H or Cl; E=P or As) and 4,6-diacetylresorcinol (H(2)-DAR) ligand in benzene medium. The structure of the new binuclear ruthenium(II) carbonyl complexes was established using elemental analysis, spectra (FT-IR, UV-vis and (1)H NMR), electrochemical and thermal studies. In these reactions, the 4,6-diacetylresorcinol (H(2)-DAR) ligand behaves as a binegative tetradentate chelating ligand coordinating through O,O atoms of both the carbonyl and phenolic C-O groups by replacing a molecule of PPh(3)/AsPh(3) and a hydride ion from the starting complexes. Further, all these complexes were also employed as new catalysts for the oxidation of primary and secondary alcohols in the presence of N-methylmorpholine-N-oxide (NMO) as a more viable co-oxidant. The free ligand and their metal complexes have also been screened for their antibacterial activity against the growth of gram +ve and gram -ve bacterial cultures. Copyright 2010 Elsevier B.V. All rights reserved.

The Effect of DEM Source and Grid Size on the Index of Connectivity in Savanna Catchments

NASA Astrophysics Data System (ADS)

Jarihani, Ben; Sidle, Roy; Bartley, Rebecca; Roth, Christian

2017-04-01

The term "hydrological connectivity" is increasingly used instead of sediment delivery ratio to describe the linkage between the sources of water and sediment within a catchment to the catchment outlet. Sediment delivery ratio is an empirical parameter that is highly site-specific and tends to lump all processes, whilst hydrological connectivity focuses on the spatially-explicit hydrologic drivers of surficial processes. Detailed topographic information plays a fundamental role in geomorphological interpretations as well as quantitative modelling of sediment fluxes and connectivity. Geomorphometric analysis permits a detailed characterization of drainage area and drainage pattern together with the possibility of characterizing surface roughness. High resolution topographic data (i.e., LiDAR) are not available for all areas; however, remotely sensed topographic data from multiple sources with different grid sizes are used to undertake geomorphologic analysis in data-sparse regions. The Index of Connectivity (IC), a geomorphometric model based only on DEM data, is applied in two small savanna catchments in Queensland, Australia. The influence of the scale of the topographic data is explored by using DEMs from LiDAR ( 1 m), WorldDEM ( 10 m), raw SRTM and hydrologically corrected SRTM derived data ( 30 m) to calculate the index of connectivity. The effect of the grid size is also investigated by resampling the high resolution LiDAR DEM to multiple grid sizes (e.g. 5, 10, 20 m) and comparing the extracted IC.

G-LiHT: Goddard's LiDAR, Hyperspectral and Thermal Airborne Imager

NASA Technical Reports Server (NTRS)

Cook, Bruce; Corp, Lawrence; Nelson, Ross; Morton, Douglas; Ranson, Kenneth J.; Masek, Jeffrey; Middleton, Elizabeth

2012-01-01

Scientists at NASA's Goddard Space Flight Center have developed an ultra-portable, low-cost, multi-sensor remote sensing system for studying the form and function of terrestrial ecosystems. G-LiHT integrates two LIDARs, a 905 nanometer single beam profiler and 1550 nm scanner, with a narrowband (1.5 nanometers) VNIR imaging spectrometer and a broadband (8-14 micrometers) thermal imager. The small footprint (approximately 12 centimeters) LIDAR data and approximately 1 meter ground resolution imagery are advantageous for high resolution applications such as the delineation of canopy crowns, characterization of canopy gaps, and the identification of sparse, low-stature vegetation, which is difficult to detect from space-based instruments and large-footprint LiDAR. The hyperspectral and thermal imagery can be used to characterize species composition, variations in biophysical variables (e.g., photosynthetic pigments), surface temperature, and responses to environmental stressors (e.g., heat, moisture loss). Additionally, the combination of LIDAR optical, and thermal data from G-LiHT is being used to assess forest health by sensing differences in foliage density, photosynthetic pigments, and transpiration. Low operating costs (approximately $1 ha) have allowed us to evaluate seasonal differences in LiDAR, passive optical and thermal data, which provides insight into year-round observations from space. Canopy characteristics and tree allometry (e.g., crown height:width, canopy:ground reflectance) derived from G-LiHT data are being used to generate realistic scenes for radiative transfer models, which in turn are being used to improve instrument design and ensure continuity between LiDAR instruments. G-LiHT has been installed and tested in aircraft with fuselage viewports and in a custom wing-mounted pod that allows G-LiHT to be flown on any Cessna 206, a common aircraft in use throughout the world. G-LiHT is currently being used for forest biomass and growth estimation in the CONUS and Mexico in support of NASA's Carbon Monitoring System (CMS) and AMIGA-Carb (AMerican Icesat Glas Assessment of Carbon). For NASA's CMS, wall-to-wall G-LiHT data have been acquired over intensive study sites with historic LiDAR datasets, dense inventory data, stem maps and flux tower observations. For AMIGA-Carb, G-LiHT transects have been acquired over ICESat tracks and USDA-FS inventory plots throughout the CONUS, and similar data will be acquired in Mexico during 2013. This talk will highlight recent science results from continental-scale transects landscape-scale deployments of G-LiHT, as well as seasonal forest dynamics from repeat pass G-LiHT acquisitions.

Estimating forest structural characteristics using the airborne LiDAR scanning system and a near-real time profiling laser system

NASA Astrophysics Data System (ADS)

Zhao, Kaiguang

LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatially-explicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for real-time remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real-time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real-time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for real-time forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of airborne scanning or profiling laser systems for remotely measuring various forest structural attributes at a range of scales, i.e., from individual tree, plot, stand and up to regional levels. The system not only provides a regional assessment tool, one that can be used to repeatedly, remotely measure hundreds or thousands of square kilometers with little/no analyst interaction or interpretation, but also serves as a paradigm for future efforts in building more advanced airborne laser systems such as real-time laser scanners.

Estimating KC-137 Aircraft Ownership Costs in the Brazilian Air Force

DTIC Science & Technology

1997-06-01

Cycle Costing A-1 M manpower m meter Maint. Maintenance Mainten. Maintenance O&S Operation and Support OPAC Online Public Access Catalog PAMAGL Parque ...1.2 e 1.3. ))as informag6es quanto a pagarnento dar~o urn pouco de trabaiho, mas creio que podern ser conseguidas na tesouraria do Parque . N~o basta...pela Base na manutengo das aeronaves (e que n~o sejam fornecidos pelo Parque ), tais como gaxetas, componentes eletr6nicos, brocas, produtos qufmicos, etc

Quantifying biomass consumption and carbon release from the California Rim fire by integrating airborne LiDAR and Landsat OLI data.

PubMed

Garcia, Mariano; Saatchi, Sassan; Casas, Angeles; Koltunov, Alexander; Ustin, Susan; Ramirez, Carlos; Garcia-Gutierrez, Jorge; Balzter, Heiko

2017-02-01

Quantifying biomass consumption and carbon release is critical to understanding the role of fires in the carbon cycle and air quality. We present a methodology to estimate the biomass consumed and the carbon released by the California Rim fire by integrating postfire airborne LiDAR and multitemporal Landsat Operational Land Imager (OLI) imagery. First, a support vector regression (SVR) model was trained to estimate the aboveground biomass (AGB) from LiDAR-derived metrics over the unburned area. The selected model estimated AGB with an R 2 of 0.82 and RMSE of 59.98 Mg/ha. Second, LiDAR-based biomass estimates were extrapolated to the entire area before and after the fire, using Landsat OLI reflectance bands, Normalized Difference Infrared Index, and the elevation derived from LiDAR data. The extrapolation was performed using SVR models that resulted in R 2 of 0.73 and 0.79 and RMSE of 87.18 (Mg/ha) and 75.43 (Mg/ha) for the postfire and prefire images, respectively. After removing bias from the AGB extrapolations using a linear relationship between estimated and observed values, we estimated the biomass consumption from postfire LiDAR and prefire Landsat maps to be 6.58 ± 0.03 Tg (10 12  g), which translate into 12.06 ± 0.06 Tg CO2 e released to the atmosphere, equivalent to the annual emissions of 2.57 million cars.

Determination of the Optimal Chromosomal Location(s) for a DNA Element in Escherichia coli Using a Novel Transposon-mediated Approach.

PubMed

Frimodt-Møller, Jakob; Charbon, Godefroid; Krogfelt, Karen A; Løbner-Olesen, Anders

2017-09-11

The optimal chromosomal position(s) of a given DNA element was/were determined by transposon-mediated random insertion followed by fitness selection. In bacteria, the impact of the genetic context on the function of a genetic element can be difficult to assess. Several mechanisms, including topological effects, transcriptional interference from neighboring genes, and/or replication-associated gene dosage, may affect the function of a given genetic element. Here, we describe a method that permits the random integration of a DNA element into the chromosome of Escherichia coli and select the most favorable locations using a simple growth competition experiment. The method takes advantage of a well-described transposon-based system of random insertion, coupled with a selection of the fittest clone(s) by growth advantage, a procedure that is easily adjustable to experimental needs. The nature of the fittest clone(s) can be determined by whole-genome sequencing on a complex multi-clonal population or by easy gene walking for the rapid identification of selected clones. Here, the non-coding DNA region DARS2, which controls the initiation of chromosome replication in E. coli, was used as an example. The function of DARS2 is known to be affected by replication-associated gene dosage; the closer DARS2 gets to the origin of DNA replication, the more active it becomes. DARS2 was randomly inserted into the chromosome of a DARS2-deleted strain. The resultant clones containing individual insertions were pooled and competed against one another for hundreds of generations. Finally, the fittest clones were characterized and found to contain DARS2 inserted in close proximity to the original DARS2 location.

Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

NASA Technical Reports Server (NTRS)

Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

2012-01-01

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized forest AGB sampling errors by 15 - 38%. Furthermore, spaceborne global scale accuracy requirements were achieved. At least 80% of the grid cells at 100m, 250m, 500m, and 1km grid levels met AGB density accuracy requirements using a combination of passive optical and SAR along with machine learning methods to predict vegetation structure metrics for forested areas without LiDAR samples. Finally, using either passive optical or SAR, accuracy requirements were met at the 500m and 250m grid level, respectively.

Does Personalized Water and Hand Quality Information Affect Attitudes, Behavior, and Health in Dar es Salaam, Tanzania?

NASA Astrophysics Data System (ADS)

Davis, J.; Pickering, A.; Horak, H.; Boehm, A.

2008-12-01

Tanzania (TZ) has one of the highest rates of child mortality due to enteric disease in the world. NGOs and local agencies have introduced numerous technologies (e.g., chlorine tablets, borewells) to increase the quantity and quality of water in Dar es Salaam, the capital of Tanzania, in hopes of reducing morbidity and mortality of waterborne disease. The objective of the present study is to determine if providing personalized information about water quality and hand surface quality, as determined by concentrations of enterococci and E. coli, results in improved health and water quality in households. A cohort study was completed in June-September 2008 in 3 communities ranging from urban to per-urban in Dar es Salaam, Tanzania to achieve our objective. The study consisted of 4 cohorts that were visited 4 times over the 3 month study. One cohort received no information about water and hand quality until the end of the summer, while the other groups received either just information on hand surface quality, just information on water quality, and information on both hand surface and water quality after the first (baseline) household visit. We report concentrations of enterococci and E. coli in water sources (surface waters and bore wells), water stored in households, and environmental waters were children and adults swim and bathe. In addition, we report concentrations of enterococci and E. coli on hands of caregivers and children in households. Preliminary results of surveys on health and perceptions of water quality and illness from the households are provided. Ongoing work will integrate the microbiological and sociological data sets to determine if personalized information interventions resulted in changes in health, water quality in the household, or perceptions of water quality, quantity and relation to human health. Future work will analyze DNA samples from hands and water for human-specific Bacteroides bacteria which are only present in human feces. Our study has the potential to provide empirical evidence to promote large scale monitoring and education campaigns in Africa to improve health and reduce the burden of waterborne disease.

Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

PubMed Central

Vierling, Lee A.; Vierling, Kerri T.; Adam, Patrick; Hudak, Andrew T.

2013-01-01

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2 mission) with the goal of improving wildlife modeling for more locations across the globe. PMID:24324655

Shuttle radar DEM hydrological correction for erosion modelling in small catchments

NASA Astrophysics Data System (ADS)

Jarihani, Ben; Sidle, Roy; Bartley, Rebecca

2016-04-01

Digital Elevation Models (DEMs) that accurately replicate both landscape form and processes are critical to support modelling of environmental processes. Catchment and hillslope scale runoff and sediment processes (i.e., patterns of overland flow, infiltration, subsurface stormflow and erosion) are all topographically mediated. In remote and data-scarce regions, high resolution DEMs (LiDAR) are often not available, and moderate to course resolution digital elevation models (e.g., SRTM) have difficulty replicating detailed hydrological patterns, especially in relatively flat landscapes. Several surface reconditioning algorithms (e.g., Smoothing) and "Stream burning" techniques (e.g., Agree or ANUDEM), in conjunction with representation of the known stream networks, have been used to improve DEM performance in replicating known hydrology. Detailed stream network data are not available at regional and national scales, but can be derived at local scales from remotely-sensed data. This research explores the implication of high resolution stream network data derived from Google Earth images for DEM hydrological correction, instead of using course resolution stream networks derived from topographic maps. The accuracy of implemented method in producing hydrological-efficient DEMs were assessed by comparing the hydrological parameters derived from modified DEMs and limited high-resolution airborne LiDAR DEMs. The degree of modification is dominated by the method used and availability of the stream network data. Although stream burning techniques improve DEMs hydrologically, these techniques alter DEM characteristics that may affect catchment boundaries, stream position and length, as well as secondary terrain derivatives (e.g., slope, aspect). Modification of a DEM to better reflect known hydrology can be useful, however, knowledge of the magnitude and spatial pattern of the changes are required before using a DEM for subsequent analyses.

Strata-based forest fuel classification for wild fire hazard assessment using terrestrial LiDAR

NASA Astrophysics Data System (ADS)

Chen, Yang; Zhu, Xuan; Yebra, Marta; Harris, Sarah; Tapper, Nigel

2016-10-01

Fuel structural characteristics affect fire behavior including fire intensity, spread rate, flame structure, and duration, therefore, quantifying forest fuel structure has significance in understanding fire behavior as well as providing information for fire management activities (e.g., planned burns, suppression, fuel hazard assessment, and fuel treatment). This paper presents a method of forest fuel strata classification with an integration between terrestrial light detection and ranging (LiDAR) data and geographic information system for automatically assessing forest fuel structural characteristics (e.g., fuel horizontal continuity and vertical arrangement). The accuracy of fuel description derived from terrestrial LiDAR scanning (TLS) data was assessed by field measured surface fuel depth and fuel percentage covers at distinct vertical layers. The comparison of TLS-derived depth and percentage cover at surface fuel layer with the field measurements produced root mean square error values of 1.1 cm and 5.4%, respectively. TLS-derived percentage cover explained 92% of the variation in percentage cover at all fuel layers of the entire dataset. The outcome indicated TLS-derived fuel characteristics are strongly consistent with field measured values. TLS can be used to efficiently and consistently classify forest vertical layers to provide more precise information for forest fuel hazard assessment and surface fuel load estimation in order to assist forest fuels management and fire-related operational activities. It can also be beneficial for mapping forest habitat, wildlife conservation, and ecosystem management.

A novel amperometric biosensor based on covalently attached multilayer assemblies of gold nanoparticles, diazo-resins and acetylcholinesterase for the detection of organophosphorus pesticides.

PubMed

Jiang, Bin; Dong, Pei; Zheng, Jianbin

2018-06-01

Using an ionic layer-by-layer self-assembly technique, colloidal gold nanoparticles (AuNPs) and diazo-resins (DAR) were immobilised on the surface of a p-aminobenzenesulfonic acid-modified glassy carbon electrode to form a matrix composite membrane for acetylcholinesterase (AChE) immobilisation. Photo-sensitive DAR was used as the assembly interlayer to convert the ionic bond into a covalent bond to improve the biosensor stability. These fabrication processes were followed by electrochemical impedance spectroscopy and cyclic voltammetry to verify the membrane formation. Because of the introduction of AuNPs/DAR/AChE biofilms, the modified electrode exhibited excellent electron transfer mediation and electrical conductivity. In addition, it exhibited high sensitivity in the range of linear concentration from 1.0 × 10 -8 to 1.0 × 10 -12 g L -1 with the detection limit of 5.12 × 10 -13 and 5.85 × 10 -13 g L -1 for malathion and methyl parathion, respectively. More importantly, the presented biosensor considerably improved stability because the electrostatic interaction was converted into covalent bonds by UV irradiation. It is a simple, cheap and stable method for quantitative detection of organophosphorus pesticides, and this method may pave a way for the sensitive, simple detection of different analytes without the need of expensive instrumentation. Copyright © 2018 Elsevier B.V. All rights reserved.

On the use of airborne LiDAR for braided river monitoring and water surface delineation

NASA Astrophysics Data System (ADS)

Vetter, M.; Höfle, B.; Pfeifer, N.; Rutzinger, M.; Stötter, J.

2009-04-01

Airborne LiDAR is an established technology for Earth surface surveying. With LiDAR data sets it is possible to derive maps with different land use classes, which are important for hydraulic simulations. We present a 3D point cloud based method for automatic water surface delineation using single as well as multitemporal LiDAR data sets. With the developed method it is possible to detect the location of the water surface with high planimetric accuracy. The multitemporal analysis of different LiDAR data sets makes it possible to visualize, monitor and quantify the changes of the flow path of braided rivers as well as derived water surface land use classes. The reflection properties from laser beams (1064 nm wavelength) on water surfaces are characterized by strong absorption or specular reflection resulting in a dominance of low signal amplitude values and a high number of laser shot dropouts (i.e. non-recorded laser echoes). The occurrence of dropouts is driven by (i) the incidence angle, (ii) the surface reflectance and (iii) the roughness of the water body. The input data of the presented delineation method are the modeled dropouts and the point cloud attributes of geometry and signal amplitude. A terrestrial orthophoto is used to explore the point cloud in order to find proper information about the geometry and amplitude attributes that are characteristic for water surfaces. The delineation method is divided into five major steps. (a) We compute calibrated amplitude values by reducing the atmospheric, topographic influences and the scan geometry for each laser echo. (b) Then, the dropouts are modeled by using the information from the time stamps, the pulse repetition frequency, the inertial measurement unit and the GPS information of the laser shots and the airplane. The next step is to calculate the standard deviation of the heights for all reflections and all modeled dropouts (c) in a specific radius around the points. (d) We compute the amplitude ratio density for all shots. The amplitude density ratio is the relation between the number of laser echoes having an amplitude within a specific interval (i.e. very low amplitudes) plus the dropouts (i.e. with amplitude of zero) divided by the number of all laser shots in a fixed search distance of a point. (e) We classify each point in water or a non-water by using the attributes of (i) the standard deviation of the height and (ii) the amplitude density ratio. For validation, a terrestrial orthophoto is used, which was taken at the same time as the laser campaign. A major advantage of this new approach is the ability of a point cloud based delineation of water and non-water areas. We demonstrate the results at the glacier forefield of the Hintereisferner (Ötztal, Tyrol, Austria) with multitemporal data sets. The multitemporal analysis demonstrates the strength of the delineation method for mapping the watercourse and monitoring the changes in the flow path of the braided river between the different epochs.

Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico.

PubMed

Urbazaev, Mikhail; Thiel, Christian; Cremer, Felix; Dubayah, Ralph; Migliavacca, Mirco; Reichstein, Markus; Schmullius, Christiane

2018-02-21

Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed for understanding and managing processes involved in the carbon cycle and supporting international policies for climate change mitigation and adaption. Furthermore, these products provide important baseline data for the development of sustainable management strategies to local stakeholders. The use of remote sensing data can provide spatially explicit information of AGB from local to global scales. In this study, we mapped national Mexican forest AGB using satellite remote sensing data and a machine learning approach. We modelled AGB using two scenarios: (1) extensive national forest inventory (NFI), and (2) airborne Light Detection and Ranging (LiDAR) as reference data. Finally, we propagated uncertainties from field measurements to LiDAR-derived AGB and to the national wall-to-wall forest AGB map. The estimated AGB maps (NFI- and LiDAR-calibrated) showed similar goodness-of-fit statistics (R 2 , Root Mean Square Error (RMSE)) at three different scales compared to the independent validation data set. We observed different spatial patterns of AGB in tropical dense forests, where no or limited number of NFI data were available, with higher AGB values in the LiDAR-calibrated map. We estimated much higher uncertainties in the AGB maps based on two-stage up-scaling method (i.e., from field measurements to LiDAR and from LiDAR-based estimates to satellite imagery) compared to the traditional field to satellite up-scaling. By removing LiDAR-based AGB pixels with high uncertainties, it was possible to estimate national forest AGB with similar uncertainties as calibrated with NFI data only. Since LiDAR data can be acquired much faster and for much larger areas compared to field inventory data, LiDAR is attractive for repetitive large scale AGB mapping. In this study, we showed that two-stage up-scaling methods for AGB estimation over large areas need to be analyzed and validated with great care. The uncertainties in the LiDAR-estimated AGB propagate further in the wall-to-wall map and can be up to 150%. Thus, when a two-stage up-scaling method is applied, it is crucial to characterize the uncertainties at all stages in order to generate robust results. Considering the findings mentioned above LiDAR can be used as an extension to NFI for example for areas that are difficult or not possible to access.

Understanding viral video dynamics through an epidemic modelling approach

NASA Astrophysics Data System (ADS)

Sachak-Patwa, Rahil; Fadai, Nabil T.; Van Gorder, Robert A.

2018-07-01

Motivated by the hypothesis that the spread of viral videos is analogous to the spread of a disease epidemic, we formulate a novel susceptible-exposed-infected-recovered-susceptible (SEIRS) delay differential equation epidemic model to describe the popularity evolution of viral videos. Our models incorporate time-delay, in order to accurately describe the virtual contact process between individuals and the temporary immunity of individuals to videos after they have grown tired of watching them. We validate our models by fitting model parameters to viewing data from YouTube music videos, in order to demonstrate that the model solutions accurately reproduce real behaviour seen in this data. We use an SEIR model to describe the initial growth and decline of daily views, and an SEIRS model to describe the long term behaviour of the popularity of music videos. We also analyse the decay rates in the daily views of videos, determining whether they follow a power law or exponential distribution. Although we focus on viral videos, the modelling approach may be used to understand dynamics emergent from other areas of science which aim to describe consumer behaviour.

Impact of time delay on the dynamics of SEIR epidemic model using cellular automata

NASA Astrophysics Data System (ADS)

Sharma, Natasha; Gupta, Arvind Kumar

2017-04-01

The delay of an infectious disease is significant when aiming to predict its strength and spreading patterns. In this paper the SEIR ​(susceptible-exposed-infected-recovered) epidemic spread with time delay is analyzed through a two-dimensional cellular automata model. The time delay corresponding to the infectious span, predominantly, includes death during the latency period in due course of infection. The advancement of whole system is described by SEIR transition function complemented with crucial factors like inhomogeneous population distribution, birth and disease independent mortality. Moreover, to reflect more realistic population dynamics some stochastic parameters like population movement and connections at local level are also considered. The existence and stability of disease free equilibrium is investigated. Two prime behavioral patterns of disease dynamics is found depending on delay. The critical value of delay, beyond which there are notable variations in spread patterns, is computed. The influence of important parameters affecting the disease dynamics on basic reproduction number is also examined. The results obtained show that delay plays an affirmative role to control disease progression in an infected host.

3D turbulence measurements using three intersecting Doppler LiDAR beams: validation against sonic anemometry

NASA Astrophysics Data System (ADS)

Carbajo Fuertes, Fernando; Valerio Iungo, Giacomo; Porté-Agel, Fernando

2013-04-01

Nowadays communities of researchers and industry in the wind engineering and meteorology sectors demand extensive and accurate measurements of atmospheric boundary layer turbulence for a better understanding of its role in a wide range of onshore and offshore applications: wind resource evaluation, wind turbine wakes, meteorology forecast, pollution and urban climate studies, etc. Atmospheric turbulence has been traditionally investigated through sonic anemometers installed on meteorological masts. However, the setup and maintenance of instrumented masts is generally very costly and the available location for the measurements is limited by the fixed position and height of the facility. In order to overcome the above-mentioned shortcomings, a measurement technique is proposed, based on the reconstruction of the three-dimensional velocity vector from simultaneous measurements of three intersecting Doppler wind LiDARs. This measuring technique presents the main advantage of being able to measure the wind velocity at any point in space inside a very large volume, which can be set and optimized for each test. Furthermore, it is very flexible regarding its transportation, installation and operation in any type of terrain. On the other hand, LiDAR measurements are strongly affected by the aerosol concentration in the air, precipitation, and the spatial and temporal resolution is poorer than that of a sonic anemometer. All this makes the comparison between these two kinds of measurements a complex task. The accuracy of the technique has been assessed by this study against sonic anemometer measurements carried out at different heights on the KNMI's meteorological mast at Cabauw's experimental site for atmospheric research (CESAR) in the Netherlands. An early uncertainty analysis shows that one of the most important parameters to be taken into account is the relative angles between the intersecting laser beams, i.e., the position of each LiDAR on the terrain and their elevation and azimuth angles. Following this analysis, different LiDAR layouts have been tested, e.g., one vertical beam and the other two almost horizontal, all three equidistant with the same elevation angle, etc. Preliminary results show different degrees of agreement between the proposed technique and the sonic anemometers depending on the LiDARs layout, which is in agreement with the uncertainty analysis carried out. The best configurations show a good agreement for the three components of the velocity and turbulence spectra, thus proving the ability of the technique to measure accurately atmospheric turbulence, consolidating it as a very interesting alternative to meteorological masts for many different applications.

A 3D convolutional neural network approach to land cover classification using LiDAR and multi-temporal Landsat imagery

NASA Astrophysics Data System (ADS)

Xu, Z.; Guan, K.; Peng, B.; Casler, N. P.; Wang, S. W.

2017-12-01

Landscape has complex three-dimensional features. These 3D features are difficult to extract using conventional methods. Small-footprint LiDAR provides an ideal way for capturing these features. Existing approaches, however, have been relegated to raster or metric-based (two-dimensional) feature extraction from the upper or bottom layer, and thus are not suitable for resolving morphological and intensity features that could be important to fine-scale land cover mapping. Therefore, this research combines airborne LiDAR and multi-temporal Landsat imagery to classify land cover types of Williamson County, Illinois that has diverse and mixed landscape features. Specifically, we applied a 3D convolutional neural network (CNN) method to extract features from LiDAR point clouds by (1) creating occupancy grid, intensity grid at 1-meter resolution, and then (2) normalizing and incorporating data into a 3D CNN feature extractor for many epochs of learning. The learned features (e.g., morphological features, intensity features, etc) were combined with multi-temporal spectral data to enhance the performance of land cover classification based on a Support Vector Machine classifier. We used photo interpretation for training and testing data generation. The classification results show that our approach outperforms traditional methods using LiDAR derived feature maps, and promises to serve as an effective methodology for creating high-quality land cover maps through fusion of complementary types of remote sensing data.

Automatic construction of aerial corridor for navigation of unmanned aircraft systems in class G airspace using LiDAR

NASA Astrophysics Data System (ADS)

Feng, Dengchao; Yuan, Xiaohui

2016-05-01

According to the airspace classification by the Federal Aviation Agency, Class G airspace is the airspace at 1,200 feet or less to the ground, which is beneath class E airspace and between classes B-D cylinders around towered airstrips. However, the lack of flight supervision mechanism in this airspace, unmanned aerial system (UAS) missions pose many safety issues. Collision avoidance and route planning for UASs in class G airspace is critical for broad deployment of UASs in commercial and security applications. Yet, unlike road network, there is no stationary marker in airspace to identify corridors that are available and safe for UASs to navigate. In this paper, we present an automatic LiDAR-based airspace corridor construction method for navigation in class G airspace and a method for route planning to minimize collision and intrusion. Our idea is to combine LiDAR to automatically identify ground objects that pose navigation restrictions such as airports and high-rises. Digital terrain model (DTM) is derived from LiDAR point cloud to provide an altitude-based class G airspace description. Following the FAA Aeronautical Information Manual, the ground objects that define the restricted airspaces are used together with digital surface model derived from LiDAR data to construct the aerial corridor for navigation of UASs. Preliminary results demonstrate competitive performance and the construction of aerial corridor can be automated with much great efficiency.

Complex dynamics of an SEIR epidemic model with saturated incidence rate and treatment

NASA Astrophysics Data System (ADS)

Khan, Muhammad Altaf; Khan, Yasir; Islam, Saeed

2018-03-01

In this paper, we describe the dynamics of an SEIR epidemic model with saturated incidence, treatment function, and optimal control. Rigorous mathematical results have been established for the model. The stability analysis of the model is investigated and found that the model is locally asymptotically stable when R0 < 1. The model is locally as well as globally asymptotically stable at endemic equilibrium when R0 > 1. The proposed model may possess a backward bifurcation. The optimal control problem is designed and obtained their necessary results. Numerical results have been presented for justification of theoretical results.

Semi-automated stand delineation in Mediterranean Pinus sylvestris plantations through segmentation of LiDAR data: The influence of pulse density

NASA Astrophysics Data System (ADS)

Varo-Martínez, Mª Ángeles; Navarro-Cerrillo, Rafael M.; Hernández-Clemente, Rocío; Duque-Lazo, Joaquín

2017-04-01

Traditionally, forest-stand delineation has been assessed based on orthophotography. The application of LiDAR has improved forest management by providing high-spatial-resolution data on the vertical structure of the forest. The aim of this study was to develop and test a semi-automated algorithm for stands delineation in a plantation of Pinus sylvestris L. using LiDAR data. Three specific objectives were evaluated, i) to assess two complementary LiDAR metrics, Assmann dominant height and basal area, for the characterization of the structure of P. sylvestris Mediterranean forests based on object-oriented segmentation, ii) to evaluate the influence of the LiDAR pulse density on forest-stand delineation accuracy, and iii) to investigate the algorithmś effectiveness in the delineation of P. sylvestris stands for map prediction of Assmann dominant height and basal area. Our results show that it is possible to generate accurate P. sylvestris forest-stand segmentations using multiresolution or mean shift segmentation methods, even with low-pulse-density LiDAR - which is an important economic advantage for forest management. However, eCognition multiresolution methods provided better results than the OTB (Orfeo Tool Box) for stand delineation based on dominant height and basal area estimations. Furthermore, the influence of pulse density on the results was not statistically significant in the basal area calculations. However, there was a significant effect of pulse density on Assmann dominant height [F2,9595 = 5.69, p = 0.003].for low pulse density. We propose that the approach shown here should be considered for stand delineation in other large Pinus plantations in Mediterranean regions with similar characteristics.

Canadian and U.S. Cooperation for the development of standards and specifications for emerging mapping technologies

USGS Publications Warehouse

Habib, A.; Jarvis, A.; Al-Durgham, M. M.; Lay, J.; Quackenbush, P.; Stensaas, G.; Moe, D.

2007-01-01

The mapping community is witnessing significant advances in available sensors, such as medium format digital cameras (MFDC) and Light Detection and Ranging (LiDAR) systems. In this regard, the Digital Photogrammetry Research Group (DPRG) of the Department of Geomatics Engineering at the University of Calgary has been actively involved in the development of standards and specifications for regulating the use of these sensors in mapping activities. More specifically, the DPRG has been working on developing new techniques for the calibration and stability analysis of medium format digital cameras. This research is essential since these sensors have not been developed with mapping applications in mind. Therefore, prior to their use in Geomatics activies, new standards should be developed to ensure the quality of the developed products. In another front, the persistent improvement in direct geo-referencing technology has led to an expansion in the use of LiDAR systems for the acquisition of dense and accurate surface information. However, the processing of the raw LiDAR data (e.g., ranges, mirror angles, and navigation data) remains a non-transparent process that is proprietary to the manufacturers of LiDAR systems. Therefore, the DPRG has been focusing on the development of quality control procedures to quantify the accuracy of LiDAR output in the absence of initial system measurements. This paper presents a summary of the research conducted by the DPRG together with the British Columbia Base Mapping and Geomatic Services (BMGS) and the United States Geological Survey (USGS) for the development of quality assurance and quality control procedures for emerging mapping technologies. The outcome of this research will allow for the possiblity of introducing North American Standards and Specifications to regulate the use of MFDC and LiDAR systems in the mapping industry.

South[ern] Africa's "Dar ul-'Ulums": Institutions of Social Change for the Common Good?

ERIC Educational Resources Information Center

Haron, Muhammed

2014-01-01

Muslim communities in principally non-Muslim nation states (e.g. South Africa, United States of America, the United Kingdom and the Netherlands) established a plethora of Muslim theological institutions. They have done so with the purpose of educating and reinforcing their Muslim identity. These educational structures have given rise to numerous…

Mapping Understory Trees Using Airborne Discrete-Return LIDAR Data

NASA Astrophysics Data System (ADS)

Korpela, I.; Hovi, A.; Morsdorf, F.

2011-09-01

Understory trees in multi-layer stands are often ignored in forest inventories. Information about them would benefit silviculture, wood procurement and biodiversity management. Cost-efficient inventory methods for the assessment of the presence, density, species- and size-distributions are called for. LiDAR remote sensing is a promising addition to field work. Unlike in passive image data, in which the signals from multiple layers mix, the 3D position of each hot-spot reflection is known in LiDAR data. The overstory however prevents from obtaining a wall-to-wall sample of understory, and measurements are subject to transmission losses. Discriminating between the crowns of dominant and suppressed trees can also be challenging. We examined the potential of LiDAR for the mapping of the understory trees in Scots pine stands (62°N, 24°E), using carefully georeferenced reference data and several LiDAR data sets. We present results that highlight differences in echo-triggering between sensors that affect the near-ground height data. A conceptual model for the transmission losses in the overstory was created and formulated into simple compensation models that reduced the intensity variation in second- and third return data. The task is highly ill-posed in discrete-return LiDAR data, and our models employed the geometry of the overstory as well as the intensity of previous returns. We showed that even first-return data in the understory is subject to losses in the overstory that did not trigger an echo. Even with compensation of the losses, the intensity data was deemed of low value in species discrimination. Area-based LiDAR height metrics that were derived from the data belonging to the crown volume of the understory showed reasonable correlation with the density and mean height of the understory trees. Assessment of the species seems out of reach in discrete-return LiDAR data, which is a drastic drawback.

Features of Point Clouds Synthesized from Multi-View ALOS/PRISM Data and Comparisons with LiDAR Data in Forested Areas

NASA Technical Reports Server (NTRS)

Ni, Wenjian; Ranson, Kenneth Jon; Zhang, Zhiyu; Sun, Guoqing

2014-01-01

LiDAR waveform data from airborne LiDAR scanners (ALS) e.g. the Land Vegetation and Ice Sensor (LVIS) havebeen successfully used for estimation of forest height and biomass at local scales and have become the preferredremote sensing dataset. However, regional and global applications are limited by the cost of the airborne LiDARdata acquisition and there are no available spaceborne LiDAR systems. Some researchers have demonstrated thepotential for mapping forest height using aerial or spaceborne stereo imagery with very high spatial resolutions.For stereo imageswith global coverage but coarse resolution newanalysis methods need to be used. Unlike mostresearch based on digital surface models, this study concentrated on analyzing the features of point cloud datagenerated from stereo imagery. The synthesizing of point cloud data from multi-view stereo imagery increasedthe point density of the data. The point cloud data over forested areas were analyzed and compared to small footprintLiDAR data and large-footprint LiDAR waveform data. The results showed that the synthesized point clouddata from ALOSPRISM triplets produce vertical distributions similar to LiDAR data and detected the verticalstructure of sparse and non-closed forests at 30mresolution. For dense forest canopies, the canopy could be capturedbut the ground surface could not be seen, so surface elevations from other sourceswould be needed to calculatethe height of the canopy. A canopy height map with 30 m pixels was produced by subtracting nationalelevation dataset (NED) fromthe averaged elevation of synthesized point clouds,which exhibited spatial featuresof roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlationwith RH50 of LVIS data with a slope of 1.04 and R2 of 0.74 indicating that the canopy height derived fromPRISM triplets can be used to estimate forest biomass at 30 m resolution.

Tree Canopy Cover Mapping Using LiDAR in Urban Barangays of Cebu City, Central Philippines

NASA Astrophysics Data System (ADS)

Ejares, J. A.; Violanda, R. R.; Diola, A. G.; Dy, D. T.; Otadoy, J. B.; Otadoy, R. E. S.

2016-06-01

This paper investigates tree canopy cover mapping of urban barangays (smallest administrative division in the Philippines) in Cebu City using LiDAR (Light Detection and Ranging). Object-Based Image Analysis (OBIA) was used to extract tree canopy cover. Multi-resolution segmentation and a series of assign-class algorithm in eCognition software was also performed to extract different land features. Contextual features of tree canopies such as height, area, roundness, slope, length-width and elliptic fit were also evaluated. The results showed that at the time the LiDAR data was collected (June 24, 2014), the tree cover was around 25.11 % (or 15,674,341.8 m2) of the city's urban barangays (or 62,426,064.6 m2). Among all urban barangays in Cebu City, Barangay Busay had the highest cover (55.79 %) while barangay Suba had the lowest (0.8 %). The 16 barangays with less than 10 % tree cover were generally located in the coastal area, presumably due to accelerated urbanization. Thirty-one barangays have tree cover ranging from 10.59--27.3 %. Only 3 barangays (i.e., Lahug, Talamban, and Busay) have tree cover greater than 30 %. The overall accuracy of the analysis was 96.6 % with the Kappa Index of Agreement or KIA of 0.9. From the study, a grouping can be made of the city's urban barangays with regards to tree cover. The grouping will be useful to urban planners not only in allocating budget to the tree planting program of the city but also in planning and creation of urban parks and playgrounds.

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics

PubMed Central

Krylova, Olga; Earn, David J. D.

2013-01-01

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced ‘susceptible–exposed–infectious–removed’ (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible–infectious–removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions. PMID:23676892

ASEI-SEIR model with vaccination for dengue control in Shah Alam, Malaysia

NASA Astrophysics Data System (ADS)

Tay, Chai Jian; Teh, Su Yean; Koh, Hock Lye

2018-03-01

Epidemiology modelling provides an understanding of the underlying mechanisms that influence the spread of dengue disease. The most common mathematical models used are the compartment models abbreviated by ASI-SIR, ASEI-SIR and ASEI-SEIR. This paper starts with a discussion of these common models, followed by the derivation of the basic reproduction number (Ro) of each model. The value of Ro in ASI-SIR model is higher than that in ASEI-SIR and ASEI-SEIR models due to the exclusion of exposed adult mosquito in ASI-SIR model. Further, sensitivity analysis on Ro indicates that natural mortality and biting rate of adult mosquito have significant effects on dengue transmission dynamics. Next, an in-house mathematical model named MOSSEIR is developed, based upon the ASEI-SEIR compartment model, in which both mosquito and human populations are considered. The mosquito population is divided into four compartments consisting of aquatic mosquito, susceptible, exposed and infected adult mosquito; while the human population is classified into four compartments comprising susceptible, exposed, infected and recovered human. MOSSEIR is then used to replicate the number of dengue cases in 2010 for Shah Alam, a capital city of Selangor with high incidence of dengue fever. Finally, effectiveness of control strategies, including mosquito breeding sites control, fogging and vaccination, are evaluated for Shah Alam. Simulation results indicate that these three control strategies can significantly reduce dengue transmission, in theory. In reality, the effectiveness of traditional control methods such as elimination of mosquito breeding sites and fogging is below expectation due to non-compliance. Therefore, the adoption of a safe, effective and affordable vaccine remains the best prospect for controlling dengue.

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics.

PubMed

Krylova, Olga; Earn, David J D

2013-07-06

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced 'susceptible-exposed-infectious-removed' (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible-infectious-removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions.

Mapping of past stand-level forest disturbances and estimation of time since disturbance using simulated spaceborne LiDAR data

NASA Astrophysics Data System (ADS)

Sanchez Lopez, N.; Hudak, A. T.; Boschetti, L.

2017-12-01

Explicit information on the location, the size or the time since disturbance (TSD) at the forest stand level complements field inventories, improves the monitoring of forest attributes and the estimation of biomass and carbon stocks. Even-aged stands display homogenous structural parameters that have often been used as a proxy of stand age. Consequently, performing object-oriented analysis on Light Detection and Ranging (LiDAR) data has potential to detect historical stand-replacing disturbances. Recent research has shown good results in the delineation of forest stands as well as in the prediction of disturbance occurrence and TSD using airborne LiDAR data. Nevertheless, the use of airborne LiDAR for systematic monitoring of forest stands is limited by the sporadic availability of data and its high cost compared to satellite instruments. NASA's forthcoming Global Ecosystem Dynamics Investigations (GEDI) mission will provide systematically data on the vertical structure of the vegetation, but its use presents some challenges compared to the common discrete-return airborne LiDAR. GEDI will be a waveform instrument, hence the summary metrics will be different to those obtained with airborne LiDAR, and the sampling configuration could limit the utility of the data, especially on heterogeneous landscapes. The potential use of GEDI data for forest characterization at the stand level would therefore depend on the predictive power of the GEDI footprint metrics, and on the density of point samples relative to forest stand size (i.e. the number of observation/footprints per stand).In this study, we assess the performance of simulated GEDI-derived metrics for stand characterization and estimation of TSD, and the point density needed to adequately identify forest stands, which translates - due to the fixed sampling configuration - into the minimum temporal interval needed to collect a sufficient number of points. The study area was located in the Clear Creek, Selway River, and Elk Creek watersheds ( 54,000 ha) within the Nez Perce-Clearwater National Forest in Idaho, where airborne LiDAR and reference maps on TSD were available. Simulated GEDI footprints and waveforms were obtained from airborne LiDAR point clouds and the results were compared to similar analysis performed with airborne LiDAR.

Evaluating UAV and LiDAR Retrieval of Snow Depth in a Coniferous Forest in Arizona

NASA Astrophysics Data System (ADS)

Van Leeuwen, W. J. D.; Broxton, P.; Biederman, J. A.

2017-12-01

Remote sensing of snow depth and cover in forested environments is challenging. Trees interfere with the remote sensing of snowpack below the canopy and cause large variations in the spatial distribution of the snowpack itself (e.g. between below canopy environments to shaded gaps to open clearings). The distribution of trees and topographic variation make it challenging to monitor the snowpack with in-situ observations. Airborne LiDAR has improved our ability to monitor snowpack over large areas in montane and forested environments because of its high sampling rate and ability to penetrate the canopy. However, these LiDAR flights can be too expensive and time-consuming to process, making it hard to use them for real-time snow monitoring. In this research, we evaluate Structure from Motion (SfM) as an alternative to Airborne LiDAR to generate high-resolution snow depth data in forested environments. This past winter, we conducted a snow field campaign over Arizona's Mogollon Rim where we acquired aerial LiDAR, multi-angle aerial photography from a UAV, and extensive field observations of snow depth at two sites. LiDAR and SFM derived snow depth maps were generated by comparing "snow-on" and "snow-off" LiDAR and SfM data. The SfM- and LiDAR-generated snow depth maps were similar at a site with fewer trees, though there were more discrepancies at a site with more trees. Both compared reasonably well with the field observations at the sparser forested site, with poorer agreement at the denser forested site. Finally, although the SfM produced point clouds with much higher point densities than the aerial LiDAR, the SfM was not able to produce meaningful snow depth estimates directly underneath trees and had trouble in areas with deep shadows. Based on these findings, we are optimizing our UAV data acquisition strategies for this upcoming field season. We are using these data, along with high-resolution hydrological modeling, to gain a better understanding of how different forest structural, climatic and topographic conditions affect the snowpack and consequently the water resources available to the Salt River Project, a water utility providing power and water to millions of customers in the Phoenix area

Sensitive Optical and Microfluidic Systems for Cellular Analyses

NASA Astrophysics Data System (ADS)

Schiro, Perry G.

Investigating rare cells and heterogeneous subpopulations is challenging for a myriad reasons. This dissertation describes novel techniques to analyze single molecules, synaptic vesicles, and rare circulating tumor cells. The eDAR platform for isolating rare cells in fluids provides a new method to monitor breast cancer status in patients as well as to guide research for personalized treatment and efficacy. In a side-by-side comparison with CellSearch, eDAR detected CTCs in all 20 Stage IV metastatic breast cancer patients while the CellSearch system found CTCs in just 8 patients. The single-molecule capillary electrophoresis technology is a method to characterize an entire sample one molecule at a time, providing detailed information about the absolute number and nature of molecules present in a sample. The nFASS platform has the potential to apply the advantages that currently exist in flow cytometry to the study of items on a much smaller scale such as subcellular organelles and nanometer-sized objects. For example, the isolation of subpopulations of synaptic vesicles will allow for detailed protein quantification and identification in the study of neurological diseases. These tools facilitate fundamental investigation of objects ranging from single molecules to single cells.

3D turbulence measurements in inhomogeneous boundary layers with three wind LiDARs

NASA Astrophysics Data System (ADS)

Carbajo Fuertes, Fernando; Valerio Iungo, Giacomo; Porté-Agel, Fernando

2014-05-01

One of the most challenging tasks in atmospheric anemometry is obtaining reliable turbulence measurements of inhomogeneous boundary layers at heights or in locations where is not possible or convenient to install tower-based measurement systems, e.g. mountainous terrain, cities, wind farms, etc. Wind LiDARs are being extensively used for the measurement of averaged vertical wind profiles, but they can only successfully accomplish this task under the limiting conditions of flat terrain and horizontally homogeneous flow. Moreover, it has been shown that common scanning strategies introduce large systematic errors in turbulence measurements, regardless of the characteristics of the flow addressed. From the point of view of research, there exist a variety of techniques and scanning strategies to estimate different turbulence quantities but most of them rely in the combination of raw measurements with atmospheric models. Most of those models are only valid under the assumption of horizontal homogeneity. The limitations stated above can be overcome by a new triple LiDAR technique which uses simultaneous measurements from three intersecting Doppler wind LiDARs. It allows for the reconstruction of the three-dimensional velocity vector in time as well as local velocity gradients without the need of any turbulence model and with minimal assumptions [EGU2013-9670]. The triple LiDAR technique has been applied to the study of the flow over the campus of EPFL in Lausanne (Switzerland). The results show the potential of the technique for the measurement of turbulence in highly complex boundary layer flows. The technique is particularly useful for micrometeorology and wind engineering studies.

Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests

NASA Astrophysics Data System (ADS)

Liu, Jing; Skidmore, Andrew K.; Heurich, Marco; Wang, Tiejun

2017-10-01

As an important metric for describing vertical forest structure, the plant area index (PAI) profile is used for many applications including biomass estimation and wildlife habitat assessment. PAI profiles can be estimated with the vertically resolved gap fraction from airborne LiDAR data. Most research utilizes a height normalization algorithm to retrieve local or relative height by assuming the terrain to be flat. However, for many forests this assumption is not valid. In this research, the effect of topographic normalization of airborne LiDAR data on the retrieval of PAI profile was studied in a mountainous forest area in Germany. Results show that, although individual tree height may be retained after topographic normalization, the spatial arrangement of trees is changed. Specifically, topographic normalization vertically condenses and distorts the PAI profile, which consequently alters the distribution pattern of plant area density in space. This effect becomes more evident as the slope increases. Furthermore, topographic normalization may also undermine the complexity (i.e., canopy layer number and entropy) of the PAI profile. The decrease in PAI profile complexity is not solely determined by local topography, but is determined by the interaction between local topography and the spatial distribution of each tree. This research demonstrates that when calculating the PAI profile from airborne LiDAR data, local topography needs to be taken into account. We therefore suggest that for ecological applications, such as vertical forest structure analysis and modeling of biodiversity, topographic normalization should not be applied in non-flat areas when using LiDAR data.

Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory

USGS Publications Warehouse

Junttila, Virpi; Finley, Andrew O.; Bradford, John B.; Kauranne, Tuomo

2013-01-01

Recently airborne Light Detection And Ranging (LiDAR) has emerged as a highly accurate remote sensing modality to be used in operational scale forest inventories. Inventories conducted with the help of LiDAR are most often model-based, i.e. they use variables derived from LiDAR point clouds as the predictive variables that are to be calibrated using field plots. The measurement of the necessary field plots is a time-consuming and statistically sensitive process. Because of this, current practice often presumes hundreds of plots to be collected. But since these plots are only used to calibrate regression models, it should be possible to minimize the number of plots needed by carefully selecting the plots to be measured. In the current study, we compare several systematic and random methods for calibration plot selection, with the specific aim that they be used in LiDAR based regression models for forest parameters, especially above-ground biomass. The primary criteria compared are based on both spatial representativity as well as on their coverage of the variability of the forest features measured. In the former case, it is important also to take into account spatial auto-correlation between the plots. The results indicate that choosing the plots in a way that ensures ample coverage of both spatial and feature space variability improves the performance of the corresponding models, and that adequate coverage of the variability in the feature space is the most important condition that should be met by the set of plots collected.

Evaluation of LiDAR Imagery as a Tool for Mapping the Northern San Andreas Fault in Heavily Forested Areas of Mendocino and Sonoma Counties, California

NASA Astrophysics Data System (ADS)

Prentice, C. S.; Koehler, R. D.; Baldwin, J. N.; Harding, D. J.

2004-12-01

We are mapping in detail active traces of the San Andreas Fault in Mendocino and Sonoma Counties in northern California, using recently acquired airborne LiDAR (also known as ALSM) data. The LiDAR data set provides a powerful new tool for mapping geomorphic features related to the San Andreas Fault because it can be used to produce high-resolution images of the ground surfaces beneath the forest canopy along the 70-km-long section of the fault zone encompassed by the data. Our effort represents the first use of LiDAR data to map active fault traces in a densely vegetated region along the San Andreas Fault. We are using shaded relief images generated from bare-earth DEMs to conduct detailed mapping of fault-related geomorphic features (e.g. scarps, offset streams, linear valleys, shutter ridges, and sag ponds) between Fort Ross and Point Arena. Initially, we map fault traces digitally, on-screen, based only on the geomorphology interpreted from LiDAR images. We then conduct field reconnaissance using the initial computer-based maps in order to verify and further refine our mapping. We found that field reconnaissance is of utmost importance in producing an accurate and detailed map of fault traces. Many lineaments identified as faults from the on-screen images were determined in the field to be old logging roads or other features unrelated to faulting. Also, in areas where the resolution of LiDAR data is poor, field reconnaissance, coupled with topographic maps and aerial photographs, permits a more accurate location of fault-related geomorphic features. LiDAR images are extremely valuable as a base for field mapping in this heavily forested area, and the use of LiDAR is far superior to traditional mapping techniques relying only on aerial photography and 7.5 minute USGS quadrangle topographic maps. Comparison with earlier mapping of the northern San Andreas fault (Brown and Wolfe, 1972) shows that in some areas the LiDAR data allow a correction of the fault trace location of up to several hundred meters. To date we have field checked approximately 24 km of the 70-km-long section of the fault for which LiDAR data is available. The remaining 46 km will be field checked in 2005. The result will be a much more accurate map of the active traces of the northern San Andreas Fault, which will be of great use for future fault studies.

CONHECIMENTO DA LEI GERAL DE SAÚDE – RESPEITO ÀS TRANSFUSÕES SANGUÍNEAS EM MÉDICOS E PACIENTES TESTEMUNHAS DE JEOVÁ DO HOSPITAL DR. DARÍO CONTRERAS DA REPÚBLICA DOMINICANA

PubMed Central

SANTANA, ELSA DÍAZ

2010-01-01

Este estudo avalia quanto o corpo médico do Hospital Dr. Darío Contreras de República Dominicana conhece, respeita, informa e aplica a Lei Geral de Saúde em relação aos direitos do paciente Testemunha de Jeová de negar-se a ser transfundido (respeito a sua autonomia); também se os Testemunhas de Jeová conhecem a Lei Geral de Saúde e até que ponto têm se beneficiado diante dessa proposição. O estudo revelou que nem médicos, nem Testemunhas de Jeová conhecem de fato essa lei. PMID:20689657

Detecting Inspection Objects of Power Line from Cable Inspection Robot LiDAR Data

PubMed Central

Qin, Xinyan; Wu, Gongping; Fan, Fei

2018-01-01

Power lines are extending to complex environments (e.g., lakes and forests), and the distribution of power lines in a tower is becoming complicated (e.g., multi-loop and multi-bundle). Additionally, power line inspection is becoming heavier and more difficult. Advanced LiDAR technology is increasingly being used to solve these difficulties. Based on precise cable inspection robot (CIR) LiDAR data and the distinctive position and orientation system (POS) data, we propose a novel methodology to detect inspection objects surrounding power lines. The proposed method mainly includes four steps: firstly, the original point cloud is divided into single-span data as a processing unit; secondly, the optimal elevation threshold is constructed to remove ground points without the existing filtering algorithm, improving data processing efficiency and extraction accuracy; thirdly, a single power line and its surrounding data can be respectively extracted by a structured partition based on a POS data (SPPD) algorithm from “layer” to “block” according to power line distribution; finally, a partition recognition method is proposed based on the distribution characteristics of inspection objects, highlighting the feature information and improving the recognition effect. The local neighborhood statistics and the 3D region growing method are used to recognize different inspection objects surrounding power lines in a partition. Three datasets were collected by two CIR LIDAR systems in our study. The experimental results demonstrate that an average 90.6% accuracy and average 98.2% precision at the point cloud level can be achieved. The successful extraction indicates that the proposed method is feasible and promising. Our study can be used to obtain precise dimensions of fittings for modeling, as well as automatic detection and location of security risks, so as to improve the intelligence level of power line inspection. PMID:29690560

Joint Offshore Wind Field Monitoring with Spaceborne SAR and Platform-Based Doppler LIDAR Measurements

NASA Astrophysics Data System (ADS)

Jacobsen, S.; Lehner, S.; Hieronimus, J.; Schneemann, J.; Kuhn, M.

2015-04-01

The increasing demand for renewable energy resources has promoted the construction of offshore wind farms e.g. in the North Sea. While the wind farm layout consists of an array of large turbines, the interrelation of wind turbine wakes with the remaining array is of substantial interest. The downstream spatial evolution of turbulent wind turbine wakes is very complex and depends on manifold parameters such as wind speed, wind direction and ambient atmospheric stability conditions. To complement and validate existing numerical models, corresponding observations are needed. While in-situ measurements with e.g. anemometers provide a time-series at the given location, the merits of ground-based and space- or airborne remote sensing techniques are indisputable in terms of spatial coverage. Active microwave devices, such as Scatterometer and Synthetic Aperture Radar (SAR), have proven their capabilities of providing sea surface wind measurements and particularly SAR images reveal wind variations at a high spatial resolution while retaining the large coverage area. Platform-based Doppler LiDAR can resolve wind fields with a high spatial coverage and repetition rates of seconds to minutes. In order to study the capabilities of both methods for the investigation of small scale wind field structures, we present a direct comparison of observations obtained by high resolution TerraSAR-X (TS-X) X-band SAR data and platform-based LiDAR devices at the North Sea wind farm alpha ventus. We furthermore compare the results with meteorological data from the COSMO-DE model run by the German Weather Service DWD. Our study indicates that the overall agreement between SAR and LiDAR wind fields is good and that under appropriate conditions small scale wind field variations compare significantly well.

A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

PubMed

Mascaro, Joseph; Asner, Gregory P; Knapp, David E; Kennedy-Bowdoin, Ty; Martin, Roberta E; Anderson, Christopher; Higgins, Mark; Chadwick, K Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

A Tale of Two “Forests”: Random Forest Machine Learning Aids Tropical Forest Carbon Mapping

PubMed Central

Mascaro, Joseph; Asner, Gregory P.; Knapp, David E.; Kennedy-Bowdoin, Ty; Martin, Roberta E.; Anderson, Christopher; Higgins, Mark; Chadwick, K. Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including—in the latter case—x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called “out-of-bag”), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha−1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation. PMID:24489686

Detecting Inspection Objects of Power Line from Cable Inspection Robot LiDAR Data.

PubMed

Qin, Xinyan; Wu, Gongping; Lei, Jin; Fan, Fei; Ye, Xuhui

2018-04-22

Power lines are extending to complex environments (e.g., lakes and forests), and the distribution of power lines in a tower is becoming complicated (e.g., multi-loop and multi-bundle). Additionally, power line inspection is becoming heavier and more difficult. Advanced LiDAR technology is increasingly being used to solve these difficulties. Based on precise cable inspection robot (CIR) LiDAR data and the distinctive position and orientation system (POS) data, we propose a novel methodology to detect inspection objects surrounding power lines. The proposed method mainly includes four steps: firstly, the original point cloud is divided into single-span data as a processing unit; secondly, the optimal elevation threshold is constructed to remove ground points without the existing filtering algorithm, improving data processing efficiency and extraction accuracy; thirdly, a single power line and its surrounding data can be respectively extracted by a structured partition based on a POS data (SPPD) algorithm from "layer" to "block" according to power line distribution; finally, a partition recognition method is proposed based on the distribution characteristics of inspection objects, highlighting the feature information and improving the recognition effect. The local neighborhood statistics and the 3D region growing method are used to recognize different inspection objects surrounding power lines in a partition. Three datasets were collected by two CIR LIDAR systems in our study. The experimental results demonstrate that an average 90.6% accuracy and average 98.2% precision at the point cloud level can be achieved. The successful extraction indicates that the proposed method is feasible and promising. Our study can be used to obtain precise dimensions of fittings for modeling, as well as automatic detection and location of security risks, so as to improve the intelligence level of power line inspection.

Government Furnished Property: Management and Accounting.

DTIC Science & Technology

1986-06-01

PROCUREMENT INSTRUMENT IDENTIFICATION NUMBER ORGANIZATION I(if applicable) %J 8c ADDRESS (City. State, anid ZIP Code) 10 SOURCE OF FUNDING NUMBERS e...DAR), Armed Services Procurement Regulation (ASPR), GAO aid service comptroller guidelines, and contract administration procedures. D. SCOPE OF STUDY...Contractor-acquired property is property procured or otherwise provided by the contractor for the performance of a . contract, title to which is vested in

A multi-scale problem arising in a model of avian flu virus in a seabird colony

NASA Astrophysics Data System (ADS)

Clancy, C. F.; O'Callaghan, M. J. A.; Kelly, T. C.

2006-12-01

Understanding the dynamics of epidemics of novel pathogens such as the H5N1 strain of avian influenza is of crucial importance to public and veterinary health as well as wildlife ecology. We model the effect of a new virus on a seabird colony, where no pre-existing Herd Immunity exists. The seabirds in question are so-called K-strategists, i.e. they have a relatively long life expectancy and very low reproductive output. They live in isolated colonies which typically contain tens of thousands of birds. These densely populated colonies, with so many birds competing for nesting space, would seem to provide perfect conditions for the entry and spread of an infection. Yet there are relatively few reported cases of epidemics among these seabirds. We develop a SEIR model which incorporates some of the unusual features of seabird population biology and examine the effects of introducing a pathogen into the colony.

Gene expression analysis in zebrafish embryos: a potential approach to predict effect concentrations in the fish early life stage test.

PubMed

Weil, Mirco; Scholz, Stefan; Zimmer, Michaela; Sacher, Frank; Duis, Karen

2009-09-01

Based on the hypothesis that analysis of gene expression could be used to predict chronic fish toxicity, the zebrafish (Danio rerio) embryo test (DarT), developed as a replacement method for the acute fish test, was expanded to a gene expression D. rerio embryo test (Gene-DarT). The effects of 14 substances on lethal and sublethal endpoints of the DarT and on expression of potential marker genes were investigated: the aryl hydrocarbon receptor 2, cytochrome P450 1A (cypla), heat shock protein 70, fizzy-related protein 1, the transcription factors v-maf musculoaponeurotic fibrosarcoma oncogene family protein g (avian) 1 and NF-E2-p45-related factor, and heme oxygenase 1 (hmox1). After exposure of zebrafish embryos for 48 h, differential gene expression was evaluated using reverse transcriptase-polymerase chain reaction, gel electrophoresis, and densitometric analysis of the gels. All tested compounds significantly affected the expression of at least one potential marker gene, with cyp1a and hmox1 being most sensitive. Lowest-observed-effect concentrations (LOECs) for gene expression were below concentrations resulting in 10% lethal effects in the DarT. For 10 (3,4- and 3,5-dichloroaniline, 1,4-dichlorobenzene, 2,4-dinitrophenol, atrazine, parathion-ethyl, chlorotoluron, genistein, 4-nitroquinoline-1-oxide, and cadmium) out of the 14 tested substances, LOEC values derived with the Gene-DarT differ by a factor of less than 10 from LOEC values of fish early life stage tests with zebrafish. For pentachloroaniline and pentachlorobenzene, the Gene-DarT showed a 23- and 153-fold higher sensitivity, respectively, while for lindane, it showed a 13-fold lower sensitivity. For ivermectin, the Gene-DarT was by a factor of more than 1,000 less sensitive than the acute fish test. The results of the present study indicate that gene expression analysis in zebrafish embryos could principally be used to predict effect concentrations in the fish early life stage test.

Modelling vertical error in LiDAR-derived digital elevation models

NASA Astrophysics Data System (ADS)

Aguilar, Fernando J.; Mills, Jon P.; Delgado, Jorge; Aguilar, Manuel A.; Negreiros, J. G.; Pérez, José L.

2010-01-01

A hybrid theoretical-empirical model has been developed for modelling the error in LiDAR-derived digital elevation models (DEMs) of non-open terrain. The theoretical component seeks to model the propagation of the sample data error (SDE), i.e. the error from light detection and ranging (LiDAR) data capture of ground sampled points in open terrain, towards interpolated points. The interpolation methods used for infilling gaps may produce a non-negligible error that is referred to as gridding error. In this case, interpolation is performed using an inverse distance weighting (IDW) method with the local support of the five closest neighbours, although it would be possible to utilize other interpolation methods. The empirical component refers to what is known as "information loss". This is the error purely due to modelling the continuous terrain surface from only a discrete number of points plus the error arising from the interpolation process. The SDE must be previously calculated from a suitable number of check points located in open terrain and assumes that the LiDAR point density was sufficiently high to neglect the gridding error. For model calibration, data for 29 study sites, 200×200 m in size, belonging to different areas around Almeria province, south-east Spain, were acquired by means of stereo photogrammetric methods. The developed methodology was validated against two different LiDAR datasets. The first dataset used was an Ordnance Survey (OS) LiDAR survey carried out over a region of Bristol in the UK. The second dataset was an area located at Gador mountain range, south of Almería province, Spain. Both terrain slope and sampling density were incorporated in the empirical component through the calibration phase, resulting in a very good agreement between predicted and observed data (R2 = 0.9856 ; p < 0.001). In validation, Bristol observed vertical errors, corresponding to different LiDAR point densities, offered a reasonably good fit to the predicted errors. Even better results were achieved in the more rugged morphology of the Gador mountain range dataset. The findings presented in this article could be used as a guide for the selection of appropriate operational parameters (essentially point density in order to optimize survey cost), in projects related to LiDAR survey in non-open terrain, for instance those projects dealing with forestry applications.

To the Application of LiDAR to Detect the Geological Structures in Sulphurets Property, British Columbia, Canada

NASA Astrophysics Data System (ADS)

Koohzare, A.; Rezaeian, M.; McIntosh, A.

2009-05-01

The Kerr Sulphurets property in North Western British Columbia has been explored primarily as a placer gold holding since the 1880s; and, potentially includes one of Canada's largest gold deposits (e.g. the Mitchell Zone). The Sulphurets camp has been classified by Taylor in 2007 as a prominent global epithermal high-sulphidation subtype with 10 million tonnes of ore (reserves + production) containing approximately 10 g/t gold. The geological and geophysical observations of this deposit indicate intrusion- related mineralized veins which are known to overlap as the result of structural complexities. Faulting predates mineralization and alteration and dramatically dominates the location of the mineralization for this porphyry- epithermal high-sulphidation deposit (Britton and Alldrick 1988, British Columbia Ministry of Energy, Mines and Petroleum Resources, 1992; Margolis, 1993). However, the surface trace of these structures and lineaments within the site is obscured by vegetation, glacial cover and steep topographic relief. We used high resolution LiDAR airborne bare-earth sensing (vegetative data deleted) in an effort to detect the surface geological features and lineaments in the Kerr Sulphurets site. The LiDAR flight was designed to acquire high density data with 2 points per square meter using a 150 kHz multipulse system. High resolution LiDAR data provides a level of detail not achievable by other digital terrain modelling techniques, whether extracted from aerial photography, low-resolution topographic contour maps, 10-30 meter USGS, or SRTM digital elevation models. LiDAR bare-earth data spectacularly revealed hidden geological structures within the property district, which in turn assisted in identifying the high potential zones for mineralization in Sulphurets.

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

NASA Astrophysics Data System (ADS)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

National Dam Inspection Program. Perrins Marsh Dam (NDI I.D. PA-0886, DER I.D. 066-005), Susquehanna River Basin Whitelock Creek, Wyoming County, Pennsylvania. Phase I Inspection Report,

DTIC Science & Technology

1981-01-01

4c sw- 0mr- w <L -- 0 I- 0. .1 I0 W ’- -o’ -3 w XLW 8 0 WW 4CFO .-. .- -4 >(lJ K 0 E-#F-0 c...2 -. 4-; In cnz KW cc 8 0 0 I f4 (z~ 0- 0- 0- -- .10 ’ 4c 0z J It’ 00 it w .C 0 W 040 ~񕋘 LL. i ao0000 11.4 Or. z ZOO 3- LCW J- zw a J Cz 4 WW L...a* o darDf Ma r, in ori~e s.Vsaa rsnre (’,. mi ,-te ~ b . C, ."s ...... .- - - - ln,V,,i:e, .’ ,. . "(’ hrm ,..,o lrda hind ’ ,++r!l, hert.

Multi-component wind measurements of wind turbine wakes performed with three LiDARs

NASA Astrophysics Data System (ADS)

Iungo, G. V.; Wu, Y.-T.; Porté-Agel, F.

2012-04-01

Field measurements of the wake flow produced from the interaction between atmospheric boundary layer and a wind turbine are performed with three wind LiDARs. The tested wind turbine is a 2 MW Enercon E-70 located in Collonges, Switzerland. First, accuracy of mean values and frequency resolution of the wind measurements are surveyed as a function of the number of laser rays emitted for each measurement. Indeed, measurements performed with one single ray allow maximizing sampling frequency, thus characterizing wake turbulence. On the other hand, if the number of emitted rays is increased accuracy of mean wind is increased due to the longer sampling period. Subsequently, two-dimensional measurements with a single LiDAR are carried out over vertical sections of the wind turbine wake and mean wake flow is obtained by averaging 2D measurements consecutively performed. The high spatial resolution of the used LiDAR allows characterizing in details velocity defect present in the central part of the wake and its downstream recovery. Single LiDAR measurements are also performed by staring the laser beam at fixed directions for a sampling period of about ten minutes and maximizing the sampling frequency in order to characterize wake turbulence. From these tests wind fluctuation peaks are detected in the wind turbine wake at blade top-tip height for different downstream locations. The magnitude of these turbulence peaks is generally reduced by moving downstream. This increased turbulence level at blade top-tip height observed for a real wind turbine has been already detected from previous wind tunnel tests and Large Eddy simulations, thus confirming the presence of a source of dangerous fatigue loads for following wind turbines within a wind farm. Furthermore, the proper characterization of wind fluctuations through LiDAR measurements is proved by the detection of the inertial subrange from spectral analysis of these velocity signals. Finally, simultaneous measurements with two LiDARs are performed over the mean vertical symmetry plane of the wind turbine wake, while a third LiDAR measures the incoming wind over a vertical plane parallel to the mean wind direction and lying outside of the wake. One LiDAR is placed in proximity of the wind turbine location and measures pointing downstream, whereas a second LiDAR is located along the mean wind direction at a downstream distance of 6.5 diameters and measures pointing upstream. For these measurements axial and vertical velocity components are retrieved only for measurement points where the two laser beams result to be roughly orthogonal. Statistics of the two velocity components show in the near wake at hub height strong flow fluctuations with magnitudes about 30% of the mean value, and a gradual reduction for downstream distances larger than three rotor diameters.

Change detection of riverbed movements using river cross-sections and LiDAR data

NASA Astrophysics Data System (ADS)

Vetter, Michael; Höfle, Bernhard; Mandlburger, Gottfried; Rutzinger, Martin

2010-05-01

Today, Airborne LiDAR derived digital terrain models (DTMs) are used for several aspects in different scientific disciplines, such as hydrology, geomorphology or archaeology. In the field of river geomorphology, LiDAR data sets can provide information on the riverine vegetation, the level and boundary of the water body, the elevation of the riparian foreland and their roughness. The LiDAR systems in use for topographic data acquisition mainly operate with wavelengths of at least 1064nm and, thus, are not able to penetrate water. LiDAR sensors with two wavelengths are available (bathymetric LiDAR), but they can only provide elevation information of riverbeds or lakes, if the water is clear and the minimum water depth exceeds 1.5m. In small and shallow rivers it is impossible to collect information of the riverbed, regardless of the used LiDAR sensor. In this article, we present a method to derive a high-resolution DTM of the riverbed and to combine it with the LiDAR DTM resulting in a watercourse DTM (DTM-W) as a basis for calculating the changes in the riverbed during several years. To obtain such a DTM-W we use river cross-sections acquired by terrestrial survey or echo-sounding. First, a differentiation between water and land has to be done. A highly accurate water surface can be derived by using a water surface delineation algorithm, which incorporates the amplitude information of the LiDAR point cloud and additional geometrical features (e.g. local surface roughness). The second step is to calculate a thalweg line, which is the lowest flow path in the riverbed. This is achieved by extracting the lowest point of each river cross section and by fitting a B-spline curve through those points. In the next step, the centerline of the river is calculated by applying a shrinking algorithm of the water boundary polygon. By averaging the thalweg line and the centerline, a main flow path line can be computed. Subsequently, a dense array of 2D-profiles perpendicular to the flow path line is defined and the heights are computed by linear interpolation of the original cross sections. Thus, a very dense 3D point cloud of the riverbed is obtained from which a grid model of the river bed can be calculated applying any suitable interpolation technique like triangulation, linear prediction or inverse distance mapping. In a final step, the river bed model and the LiDAR DTM are combined resulting in a watercourse DTM. By computing different DTM-Ws from multiple cross section data sets, the volume and the magnitude of changes in the riverbed can be estimated. Hence, the erosion or accumulation areas and their volume changes during several years can be quantified.

Contract Incentives for Product Quality

DTIC Science & Technology

1980-06-01

incurred by the contractor, i.e., cost reimbursement contracts. It differs also in that the product may only be definable in general terms, thus...government employees. There are other fiscal motivations as well since if government quality personnel do not accept their system, reimbursement will not... reimbursement contracts in the DAR, Paragraph 3-808.1 as follows: 3-808 Profit, Including Fees Under Cost- Reimbursement Type Contracts 3-808.1 Policy (a

Forest inventory with LiDAR and stereo DSM on Washington department of natural resources lands

Treesearch

Jacob L. Strunk; Peter J. Gould

2015-01-01

DNR’s forest inventory group has completed its first version of a new remote-sensing based forest inventory system covering 1.4 million acres of DNR forest lands. We use a combination of field plots, lidar, NAIP, and a NAIP-derived canopy surface DSM. Given that height drives many key inventory variables (e.g. height, volume, biomass, carbon), remote-sensing derived...

Performance Evaluation of sUAS Equipped with Velodyne HDL-32E LiDAR Sensor

NASA Astrophysics Data System (ADS)

Jozkow, G.; Wieczorek, P.; Karpina, M.; Walicka, A.; Borkowski, A.

2017-08-01

The Velodyne HDL-32E laser scanner is used more frequently as main mapping sensor in small commercial UASs. However, there is still little information about the actual accuracy of point clouds collected with such UASs. This work evaluates empirically the accuracy of the point cloud collected with such UAS. Accuracy assessment was conducted in four aspects: impact of sensors on theoretical point cloud accuracy, trajectory reconstruction quality, and internal and absolute point cloud accuracies. Theoretical point cloud accuracy was evaluated by calculating 3D position error knowing errors of used sensors. The quality of trajectory reconstruction was assessed by comparing position and attitude differences from forward and reverse EKF solution. Internal and absolute accuracies were evaluated by fitting planes to 8 point cloud samples extracted for planar surfaces. In addition, the absolute accuracy was also determined by calculating point 3D distances between LiDAR UAS and reference TLS point clouds. Test data consisted of point clouds collected in two separate flights performed over the same area. Executed experiments showed that in tested UAS, the trajectory reconstruction, especially attitude, has significant impact on point cloud accuracy. Estimated absolute accuracy of point clouds collected during both test flights was better than 10 cm, thus investigated UAS fits mapping-grade category.

Accuracy Assessment of Crown Delineation Methods for the Individual Trees Using LIDAR Data

NASA Astrophysics Data System (ADS)

Chang, K. T.; Lin, C.; Lin, Y. C.; Liu, J. K.

2016-06-01

Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.

VPAC1 targeted 64Cu-TP3805 PET imaging of prostate cancer: preliminary evaluation in man

PubMed Central

Tripathi, Sushil; Trabulsi, Edouard J; Gomella, Leonard; Kim, Sung; McCue, Peter; Intenzo, Charles; Birbe, Ruth; Gandhe, Ashish; Kumar, Pardeep; Thakur, Mathew

2015-01-01

Objectives To evaluate 64Cu-TP3805 as a novel biomolecule, to PET image prostate cancer (PC), at the onset of which VPAC1, the superfamily of G-protein coupled receptors, is expressed in high density on PC cells, but not on normal cells. Methods 25 patients undergoing radical prostatectomy were PET/CT imaged preoperatively with 64Cu-TP3805. Standardized uptake values (SUVmax) were determined, malignant lesions (SUV > 1.0) counted, and compared with histologic findings. Whole mount pathology slides from 6 VPAC1 PET imaged patients, 3 BPH patients, one malignant and one benign lymph node underwent digital autoradiography (DAR) after 64Cu-TP3805 incubation and compared to H&E stained slides. Results In 25 patient PET imaging, 212 prostate gland lesions had SUVmax > 1.0 vs.127 lesions identified by histology of biopsy tissues. The status of the additional 85 PET identified prostate lesions remains to be determined. In 68 histological slides from 6 PET imaged patients, DAR identified 105/107 PC foci, 19/19 HGPIN, and ejaculatory ducts and verumontanum involved with cancer. Additionally, DAR found 9 PC lesions not previously identified histologically. The positive and negative lymph nodes were correctly identified and in 3/3 BPH patients and 5/5 cysts, DAR was negative. Conclusion This feasibility study demonstrated that 64Cu-TP3805 delineates PC in vivo and ex vivo, provided normal images for benign masses, and is worthy of further studies. PMID:26519886

Quantifying biomass consumption and carbon release from the California Rim fire by integrating airborne LiDAR and Landsat OLI data

PubMed Central

Saatchi, Sassan; Casas, Angeles; Koltunov, Alexander; Ustin, Susan; Ramirez, Carlos; Garcia‐Gutierrez, Jorge; Balzter, Heiko

2017-01-01

Abstract Quantifying biomass consumption and carbon release is critical to understanding the role of fires in the carbon cycle and air quality. We present a methodology to estimate the biomass consumed and the carbon released by the California Rim fire by integrating postfire airborne LiDAR and multitemporal Landsat Operational Land Imager (OLI) imagery. First, a support vector regression (SVR) model was trained to estimate the aboveground biomass (AGB) from LiDAR‐derived metrics over the unburned area. The selected model estimated AGB with an R 2 of 0.82 and RMSE of 59.98 Mg/ha. Second, LiDAR‐based biomass estimates were extrapolated to the entire area before and after the fire, using Landsat OLI reflectance bands, Normalized Difference Infrared Index, and the elevation derived from LiDAR data. The extrapolation was performed using SVR models that resulted in R 2 of 0.73 and 0.79 and RMSE of 87.18 (Mg/ha) and 75.43 (Mg/ha) for the postfire and prefire images, respectively. After removing bias from the AGB extrapolations using a linear relationship between estimated and observed values, we estimated the biomass consumption from postfire LiDAR and prefire Landsat maps to be 6.58 ± 0.03 Tg (1012 g), which translate into 12.06 ± 0.06 Tg CO2e released to the atmosphere, equivalent to the annual emissions of 2.57 million cars. PMID:28405539

Integration of LiDAR and cropmark remote sensing for the study of fluvial and anthropogenic landforms in the Brenta-Bacchiglione alluvial plain (NE Italy)

NASA Astrophysics Data System (ADS)

Ninfo, Andrea; Mozzi, Paolo; Abbà, Tiziano

2016-05-01

The geomorphological study of alluvial plains takes great advantage from the integration of detailed altimetry with high-resolution images, especially in the lower-relief sectors, like those in the distal plain of the Brenta and Bacchiglione rivers near the city of Padua (mean slope 1-0.8‰). The LiDAR data which were specifically acquired for this research (Riegl LMS-Q560, mean density 7 points/m2, overall area 123 km2), were classified and interpolated in order to map fluvial and anthropogenic landforms. The acquisition was carried out in a moment of minimal vegetation luxuriance (March 2011), in order to minimize ground cover. The DEM (z accuracy < 5-10 cm) was processed and analyzed in integration with high resolution oblique and vertical, multispectral (VIS + IR) and panchromatic aerial images. These latter were acquired during the summer crop season, with the aim of maximizing the detection of vegetation response to different soils, sediments and landforms (cropmarks). A detailed field survey was conducted with soil observation, hand augerings and description of stratigraphic sections in pits, in order to validate the remote sensing interpretations. The detailed topography allowed the identification and mapping of low rise interfluves and scarps (< 1-2 m), paleochannels, scroll bars and crevasse splays. The reconstruction of a precise "ground" surface in the narrow medieval streets detailed the morphology of the multi-stratified archeological mound in the historical center of Padua. The remote sensing of cropmarks is the most appropriate method to complete the mapping of the numerous fluvial forms that have little or no topographic expression being too small (i.e. minor crevasse channels and splays) and/or flattened by anthropogenic activity (mainly plowing). LiDAR intensity permitted a precise mapping of LGM deposits that have shown peculiar reflectivity related to specific soil characteristics (i.e., presence of calcic horizons in well-drained, elevated position). High resolution images and LiDAR DEM allow the analysis of this largely anthropized low-plain environment at cell-size scale of 0.5-1 m, i.e. approximating the original complexity of the alluvial sedimentary environment. The results bring advances in the comprehension of the Last Glacial Maximum and Holocene evolution of the Brenta-Bacchiglione plain. The large-scale mapping of paleohydrographic features led to the recognition of different fluvial styles adopted by the Brenta River: i) braided to wandering paleochannels, 100-300 m wide, in fine-sediment dominated fluvioglacial LGM distal alluvial plain, ii) meandering (up to ~ 3.5) single channels, 50-100 m wide, with evidence of lateral migration in early and middle Holocene channel belts, and iii) low to medium sinuosity (~ 1.15-1.5) single channels with vertical aggradation, associated with ridges and widespread crevasse channels and splays during the middle Holocene. The derived maps provide significant support to land and urban planning, e.g., in the definition of appropriate geotechnical analysis, the estimation of buried archeological deposits in the city center, and the assessment of flooding hazard.

Coastal and tidal landform detection from high resolution topobathymetric LiDAR data

NASA Astrophysics Data System (ADS)

Skovgaard Andersen, Mikkel; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Brandbyge Ernstsen, Verner

2016-04-01

Coastal and tidal environments are valuable ecosystems, which, however, are under pressure in many areas around the world due to globalisation and/or climate change. Detailed mapping of these environments is required in order to manage the coastal zone in a sustainable way. However, historically these transition zones between land and water are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. The new generation of airborne topobathymetric light detection and ranging (LiDAR) potentially enables full-coverage and high-resolution mapping of these land-water transition zones. We have carried out topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the LiDAR point cloud with a mean point density in the order of 20 points/m2. The DEM was analysed morphometrically using a modification of the tool Benthic Terrain Modeler (BTM) developed by Wright et al. (2005). Initially, stage (the elevation in relation to tidal range) was used to divide the area of investigation into the different tidal zones, i.e. subtidal, intertidal and supratidal. Subsequently, morphometric units were identified and characterised by a combination of statistical neighbourhood analysis with varying window sizes (using the Bathymetric Positioning Index (BPI) from the BTM, moving average and standard deviation), slope parameters and area/perimeter ratios. Finally, these morphometric units were classified into six different types of landforms based on their stage and morphometric characteristics, i.e. either subtidal channel, intertidal flat, intertidal creek, linear bar, swash bar or beach dune. We hereby demonstrate the potential of using airborne topobathymetric LiDAR for seamless mapping of land-water transition zones in challenging coastal environments with high water column turbidity and continuously varying water levels due to tides. Furthermore, we demonstrate the potential of morphometric analysis on high-resolution topobathymetric LiDAR data for automatic identification, characterisation and classification of different landforms present in coastal land-water transition zones. Acknowledgements This work was funded by the Danish Council for Independent Research | Natural Sciences through the project "Process-based understanding and prediction of morphodynamics in a natural coastal system in response to climate change" (Steno Grant no. 10-081102) and by the Geocenter Denmark through the project "Closing the gap! - Coherent land-water environmental mapping (LAWA)" (Grant no. 4-2015). References Wright DJ, Lundblad ER, Larkin EM, Rinehart RW, Murphy J, Cary-Kothera L, Draganov K, 2005. ArcGIS Benthic Terrain Modeler. Corvallis, Oregon, Oregon State University, Davey Jones Locker Seafloor Mapping/Marine GIS Laboratory and NOAA Coastal Services Center.

Combining High Spatial Resolution Optical and LIDAR Data for Object-Based Image Classification

NASA Astrophysics Data System (ADS)

Li, R.; Zhang, T.; Geng, R.; Wang, L.

2018-04-01

In order to classify high spatial resolution images more accurately, in this research, a hierarchical rule-based object-based classification framework was developed based on a high-resolution image with airborne Light Detection and Ranging (LiDAR) data. The eCognition software is employed to conduct the whole process. In detail, firstly, the FBSP optimizer (Fuzzy-based Segmentation Parameter) is used to obtain the optimal scale parameters for different land cover types. Then, using the segmented regions as basic units, the classification rules for various land cover types are established according to the spectral, morphological and texture features extracted from the optical images, and the height feature from LiDAR respectively. Thirdly, the object classification results are evaluated by using the confusion matrix, overall accuracy and Kappa coefficients. As a result, a method using the combination of an aerial image and the airborne Lidar data shows higher accuracy.

Sand Fly Fever-Naples Infection in Egypt

DTIC Science & Technology

1987-02-02

residents of metropolitan Cairo: Dar- Mammalian cell lines were blind-passed once af- wish and Hoogstraal, applying the complement ter 10 days. All...cultures of C6/36 cells and those fixation (CF) test to human sera collected from of mammalian cell lines with CPE were screened Sharqiya in 1976. found a...measurement of specific anti- 9. Riggs, J. L.. 1979. Immunofluorescent staining, bodies in Bolivian hemorrhagic fever by neu- Pages 141-151 in E. H

Study of the stability of a SEIRS model for computer worm propagation

NASA Astrophysics Data System (ADS)

Hernández Guillén, J. D.; Martín del Rey, A.; Hernández Encinas, L.

2017-08-01

Nowadays, malware is the most important threat to information security. In this sense, several mathematical models to simulate malware spreading have appeared. They are compartmental models where the population of devices is classified into different compartments: susceptible, exposed, infectious, recovered, etc. The main goal of this work is to propose an improved SEIRS (Susceptible-Exposed-Infectious-Recovered-Susceptible) mathematical model to simulate computer worm propagation. It is a continuous model whose dynamic is ruled by means of a system of ordinary differential equations. It considers more realistic parameters related to the propagation; in fact, a modified incidence rate has been used. Moreover, the equilibrium points are computed and their local and global stability analyses are studied. From the explicit expression of the basic reproductive number, efficient control measures are also obtained.

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

NASA Technical Reports Server (NTRS)

Morton, D. C.; Keller, M.; Cook, B. D.; Hunter, Maria; Sales, Marcio; Spinelli, L.; Victoria, D.; Andersen, H.-E.; Saleska, S.

2012-01-01

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Fire Impacts on Mixed Pine-oak Forests Assessed with High Spatial Resolution Imagery, Imaging Spectroscopy, and LiDAR

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Kathy, S. L.; Dennison, P. E.; Cook, B.; Hanavan, R. P.; Serbin, S.

2016-12-01

As a primary disturbance agent, fire significantly influences forest ecosystems, including the modification or resetting of vegetation composition and structure, which can then significantly impact landscape-scale plant function and carbon stocks. Most ecological processes associated with fire effects (e.g. tree damage, mortality, and vegetation recovery) display fine-scale, species specific responses but can also vary spatially within the boundary of the perturbation. For example, both oak and pine species are fire-adapted, but fire can still induce changes in composition, structure, and dominance in a mixed pine-oak forest, mainly because of their varying degrees of fire adaption. Evidence of post-fire shifts in dominance between oak and pine species has been documented in mixed pine-oak forests, but these processes have been poorly investigated in a spatially explicit manner. In addition, traditional field-based means of quantifying the response of partially damaged trees across space and time is logistically challenging. Here we show how combining high resolution satellite imagery (i.e. Worldview-2,WV-2) and airborne imaging spectroscopy and LiDAR (i.e. NASA Goddard's Lidar, Hyperspectral and Thermal airborne imager, G-LiHT) can be effectively used to remotely quantify spatial and temporal patterns of vegetation recovery following a top-killing fire that occurred in 2012 within mixed pine-oak forests in the Long Island Central Pine Barrens Region, New York. We explore the following questions: 1) what are the impacts of fire on species composition, dominance, plant health, and vertical structure; 2) what are the recovery trajectories of forest biomass, structure, and spectral properties for three years following the fire; and 3) to what extent can fire impacts be captured and characterized by multi-sensor remote sensing techniques from active and passive optical remote sensing.

Intraday monitoring of granitic exfoliation sheets with LiDAR and thermal imaging (Yosemite Valley, California, USA)

NASA Astrophysics Data System (ADS)

Guerin, Antoine; Derron, Marc-Henri; Jaboyedoff, Michel; Abellán, Antonio; Dubas, Olivier; Collins, Brian D.; Stock, Greg M.

2016-04-01

Rockfall activity in Yosemite Valley is often linked to the presence of exfoliation sheets associated with other structures such as faults, joints or geological contacts. Daily and seasonal temperature variations or freeze-thaw cycles may strongly promote crack propagation along discontinuities, ultimately leading to rockfalls (Stock et al., 2013). However, little is known concerning the impact of thermal variations on rock face deformation, despite its occurrence at all times of year. To understand the influence of daily temperature fluctuations on the behavior of exfoliation joints (i.e., fractures separating exfoliation sheets), we carried out two different experiments in October 2015: (a) We first monitored a sub-vertical granodiorite flake (19 m by 4 m by 0.1 m ; Collins and Stock, 2014) for 24 consecutive hours using LiDAR and infrared thermal sensors; (b) We monitored a rock cliff (60 m by 45 m) composed of tens of exfoliation sheets located on the southeast face of El Capitan (an ~1000-m-tall cliff located in western Yosemite Valley) for several hours (from 05:30 pm to 01:30 am) to investigate the diurnal cooling effect on rocks of different lithologies. To calibrate the raw apparent temperature measured by the thermal imager (FLIR T660 infrared camera), we fixed pieces of reflective paper (aluminum foil) and black duct tape on both monitored cliffs to measure the reflected temperature and the emissivity of the different rocks. In addition, ambient temperature and relative humidity readings were performed for each acquisition. We then compared the calibrated temperatures to the values registered by resistance temperature detectors (Pt100 sensors), also attached to the rock. Finally, we compared the millimeter scale deformations observed with LiDAR to the values measured by manual crackmeters (standard analog comparators with springs) installed beforehand in the fractures. For the first experiment (24-hour monitoring), a series of measurements were carried out: (a) thermal pictures were collected every 20 minutes, (b) LiDAR scans (4 mm point spacing) were collected every hour and (c) the measurements provided by the crackmeters and thermoresistances were recorded every two hours. The thermal images were then draped on the LiDAR triangular meshes to quantify the lateral propagation of temperature during the warming and cooling periods. Results show that the flake edge is cooler than the surrounding areas and that this part undergoes the most significant daily temperature variations. Furthermore, the comparison of point clouds allowed observing and quantifying one full contraction-expansion cycle of the monitored exfoliation sheet, confirming the observations of Collins and Stock, 2014. The maximum deformation (17.5 mm in total) occurred between 04:00 am and 03:00 pm, when temperatures were respectively minimum (16 °C) and maximum (28 °C); this deformation value is consistent with those measured by the crackmeters. Regarding the second experiment, we collected a series of thermal images and LiDAR scans with the same time interval (20 minutes) but with a lower spatial resolution (point spacing of about 7 mm). Here, we also observed that the edge of exfoliation sheets were cooler in this test, and not dependent on the length of the analyzed flakes (from a few tens of cm to several m). Our experiment indicates that the infrared thermography can be used to remotely detect exfoliations sheets in the cliff at short distances (within 100 m), and to generate a 3D map of partially detached unstable rocky compartments. For some flakes, we locally observed a decrease of temperature of a few °C in surface, suggesting the presence of rock bridges. Finally, our thermal comparisons show that the cooling amplitude varies depending on lithologies: the cooling is more important for dark rocks (e.g., diorites) than for light-coloured rocks (e.g., granites) which reflect more incident radiation.

Predicting forest height using the GOST, Landsat 7 ETM+, and airborne LiDAR for sloping terrains in the Greater Khingan Mountains of China

NASA Astrophysics Data System (ADS)

Gu, Chengyan; Clevers, Jan G. P. W.; Liu, Xiao; Tian, Xin; Li, Zhouyuan; Li, Zengyuan

2018-03-01

Sloping terrain of forests is an overlooked factor in many models simulating the canopy bidirectional reflectance distribution function, which limits the estimation accuracy of forest vertical structure parameters (e.g., forest height). The primary objective of this study was to predict forest height on sloping terrain over large areas with the Geometric-Optical Model for Sloping Terrains (GOST) using airborne Light Detection and Ranging (LiDAR) data and Landsat 7 imagery in the western Greater Khingan Mountains of China. The Sequential Maximum Angle Convex Cone (SMACC) algorithm was used to generate image endmembers and corresponding abundances in Landsat imagery. Then, LiDAR-derived forest metrics, topographical factors and SMACC abundances were used to calibrate and validate the GOST, which aimed to accurately decompose the SMACC mixed forest pixels into sunlit crown, sunlit background and shade components. Finally, the forest height of the study area was retrieved based on a back-propagation neural network and a look-up table. Results showed good performance for coniferous forests on all slopes and at all aspects, with significant coefficients of determination above 0.70 and root mean square errors (RMSEs) between 0.50 m and 1.00 m based on ground observed validation data. Higher RMSEs were found in areas with forest heights below 5 m and above 17 m. For 90% of the forested area, the average RMSE was 3.58 m. Our study demonstrates the tremendous potential of the GOST for quantitative mapping of forest height on sloping terrains with multispectral and LiDAR inputs.

UAV-LiDAR accuracy and comparison to Structure from Motion photogrammetry

NASA Astrophysics Data System (ADS)

Kucharczyk, M.; Hugenholtz, C.; Zou, X.; Nesbit, P. R.; Barchyn, T.

2016-12-01

We compare the spatial accuracy of a UAV-LiDAR system with Structure from Motion (SfM) photogrammetry. UAV-based LiDAR remote sensing potentially offers advantages over SfM photogrammetry in vegetated terrain, particularly with respect to canopy penetration and related measurements of ground surface elevation and vegetation height; however, little quantitative evidence has been presented to date. To address this, we performed a case study at a field site in Alberta, Canada with six different land cover types: short grass, tall grass, short shrubs, tall shrubs, deciduous trees, and coniferous trees. Both UAV datasets were acquired on the same day. The SfM dataset was derived from images acquired by a senseFly eBee fixed-wing UAV equipped with a 16.1 megapixel RGB camera. The UAV-LiDAR system is a proprietary design that consists of a single-rotor helicopter (2-m rotor diameter) equipped with a Riegl VUX-1UAV laser scanner, KVH 1750 inertial measurement unit, and dual NovAtel GNSS receivers. We measured vegetation height from at least 30 samples in each land cover type and acquired check point measurements to determine horizontal and vertical accuracy. Vegetation height was measured manually for grasses and shrubs with a level staff, and with a total station for trees. Coordinates of horizontal and vertical check points were surveyed with real-time kinematic (RTK) GNSS. We followed standard methods for computing horizontal and vertical accuracies based on the 2015 guidelines from the American Society of Photogrammetry and Remote Sensing. Results will be presented at the AGU Fall Meeting.

Identifying slow-moving landslides using LiDAR DEM and SAR interferometry: An Example of 2006 Meinong Earthquake

NASA Astrophysics Data System (ADS)

Chen, R. F.; Lin, C. W.; Hsu, Y. J.; Zhang, L.; Liang, H. Y.

2017-12-01

The February 6 Meinong Earthquake of 2016 (ML=6.4; at 23.85ºN, 120.81ºE), with a focal depth of 16.7 km, was triggered by an unknown blind thrust in southern Taiwan. The earthquake not only induced coseismic crustal deformation, but also triggered slow-moving landslides nearby the Longchuan active fault. In this study, high-resolution LiDAR derived DEM of 2010 is used to recognize locations of previous slow-moving landslides according to their topographic signatures, such as main escarpment, trench, double ridge, and crown cracks. Within an area of 4.5 km x 1.8 km along Longchuan fault near the ridge of Longchuan mountain, over 50 sites with landslide signatures are recognized, and three of them are over 10 ha. These earthquake-induced landslide deformations are detected from InSAR (synthetic aperture radar interferometry) images using Advanced Land Observing Satellite ALOS2/Phased-array L band and Sentinel 1 C-band SAR (PALSAR) data taken before and after the earthquake; some significant landslide deformation are even overlapped with areas where previous slow moving landslides were identified on the LiDAR DEM. Additionally, field investigation right after the earthquake in the study area also support that these previously identified landslides reactivated in the earthquake. Although these landslides do not cause serious damage due to their minor displacement in the Meinong Earthquake, the study results prove that LiDAR DEM is a powerful tool to identify and continuously monitor slow-motion landslides for preventing catastrophic failures that may be caused by hazardous earthquake or heavy rainfall.

Tropical Airborne LiDAR for Landslide Assessment in Malaysia: a technical perspective

NASA Astrophysics Data System (ADS)

Abd Manap, Mohamad; Azhari Razak, Khamarrul; Mohamad, Zakaria; Ahmad, Azhari; Ahmad, Ferdaus; Mohamad Zin, Mazlan; A'zad Rosle, Qalam

2015-04-01

Malaysia has faced a substantial number of landslide events every year. Cameron Highlands, Pahang is one of the badly areas affected by slope failures characterized by extreme climate, rugged topographic and weathered geological structures in a tropical environment. A high frequency of landslide occurrence in the hilly areas is predominantly due to the geological materials, tropical monsoon seasons and uncontrolled agricultural activities. Therefore the Government of Malaysia through the Prime Minister Department has allocated a special budget to conduct national level hazard and risk mapping project through Minerals and Geoscience Department Malaysia, the Ministry of Natural Resources and Environment. The primary aim of this project is to provide slope hazard risk information for a better slope management in Malaysia. In addition this project will establish national infrastructure for geospatial information on the geological terrain and slope by emphasizing the disaster risk throughout the country. The areas of interest are located in the three different selected areas i.e. Cameron Highlands (275 square kilometers), Ipoh (200 square kilometers) and Cheras Kajang -- Batang kali (650 square kilometers). These areas are selected based on National Slope Master Plan (2009 -- 2023) that endorsed by Malaysia Government Cabinet. The national hazard and risk mapping project includes six parts of major tasks: (1) desk study and mobilization, (2) airborne LiDAR data acquisition and analysis, (3) field data acquisition and verification, (4) hazard and risk for natural terrain, (5) hazard and risk analysis for man-made slope and (6) Man-made slope mitigation/preventive measures. The project was authorized in September, 2014 and will be ended in March, 2016. In this paper, the main focus is to evaluate the suitability of integrated capability of airborne- and terrestrial LiDAR data acquisition and analysis, and also digital photography for regional landslide assessment. The results of the study produced 4 point/m2 density of LiDAR data point cloud, very detailed DEM and DSM of 0.5 m grid and high resolution digital aerial photograph of 7 cm grid, as well as an inventory of the landslide. A reliable landslide inventory has been critically developed with the input of LIDAR derivatives data and field investigation emphasizing on its crucial attributes, e.g., the landslide types, depth, style-, states and distribution of landslide activity. As a result of this study, guidelines and recommendation on the technical aspect of LIDAR-derived landslide assessment are explicitly presented and critically discussed. The finding of this project will be very useful for future planning of slope management, sustainable land use planning and development by related government agencies and local authorities in Malaysia. Keywords: Airborne LiDAR; landslide assessment; hazard and risk analysis; 3D point cloud density; slope failures; Malaysia

Using Adult Mosquitoes to Transfer Insecticides to Aedes Aegypti Larval Habitats

DTIC Science & Technology

2009-07-14

Playa , a municipality belonging to Ciudad de La Habana, Cuba. Rev Panam Salud Publica Pan Am J Public Health 19:379–384. 33. Harrington LC, et al...United Kingdom; bLaboratorio de Salud Publica, Iquitos, Peru; cIfakara Health Institute, Dar es Salaam, United Republic of Tanzania; dVector Group...Liverpool School of Tropical Medicine, Liverpool L3 5QA, United Kingdom; eNaval Medical Research Center Detachment, United States Navy, Lima , Peru; and f

How integrating 3D LiDAR data in the dike surveillance protocol: The French case

NASA Astrophysics Data System (ADS)

Bretar, F.; Mériaux, P.; Fauchard, C.

2012-04-01

The recent and dramatic floods of the last years in Europe (e.g. Rhône river major flood, December 2003, Windstorm Xynthia, February 2010, in France) and in the United-States (Hurricane Katrina, August 2005) showed the vulnerability of flood or coastal defence systems. The first key point for avoiding these dramatic damages and the high cost of a failure and its consequences lies in the appropriate conception and construction of the dikes, but above all in the relevance of the surveillance protocol. Many factors introduce weaknesses in the fluvial or maritime dikes. Most of them are old embankment structures. For instance, some of the French Loire River dikes were built several centuries ago. They may have been rebuilt, modified, heightened several times, with some materials that do not necessarily match the original conception of the structure. In other respects, tree roots or animal burrows could modify the structure of the dike and reduce the watertightness or mechanical properties. The French government has built a national database, "BarDigues", since 1999 to inventory and characterize dikes. Today, there are approx. 9000 km of dikes protecting 1.5 to 2 millions of people. In the meantime, a GIS application, called « Dike SIRS » [Maurel P., 2004] , provides an operational and accurate tool to several great stakeholders in charge of managing more than 100 km of dikes. Today, the dike surveillance and diagnosis protocol consists in identifying the weaknesses of the structure and providing the degree of safety by making a preliminary study (historical research, geological and morphodynamic study, topography), geophysical study (e.g. electromagnetic methods and electrical resistivity tomography) and at last geotechnical study (e.g. drillings and stability modelling) at the very local scale when necessary [Mériaux P. & Royet P, 2007] . Considering the stretch of hundreds of kilometres, rapid, cost-effective and reliable techniques for surveying the dike must be carried out. A LiDAR system is able to acquire data on a dike structure of up to 80 km per day, which makes the use of this technique also valuable in case of emergency situations. It provides additional valuable products like precious information on dike slopes and crest or their near environment (river banks, etc.). Moreover, in case of vegetation, LiDAR data makes possible to study hidden structures or defaults from images like the erosion of riverbanks under forestry vegetation. The possibility of studying the vegetation is also of high importance: the development of woody vegetation near or onto the dike is a major risk factor. Surface singularities are often signs of disorder or suspected disorder in the dike itself: for example a subsidence or a sinkhole on a ridge may result from internal erosion collapse. Finally, high resolution topographic data contribute to build specific geomechanical model of the dike that, after incorporating data provided by geophysical and geotechnical surveys, are integrated in the calculations of the structure stability. Integrating the regular use of LiDAR data in the dike surveillance protocol is not yet operational in France. However, the high number of French stakeholders at the national level (on average, there is one stakeholder for only 8-9km of dike !) and the real added value of LiDAR data makes a spatial data infrastructure valuable (webservices for processing the data, consulting and filling the database on the field when performing the local diagnosis)

3D free-air gravity anomaly modeling for the Southeast Indian Ridge

NASA Astrophysics Data System (ADS)

Girolami, Chiara; Heyde, Ingo; Rinaldo Barchi, Massimiliano; Pauselli, Cristina

2016-04-01

In this study we analyzed the free-air gravity anomalies measured on the northwestern part of the Southeast Indian Ridge (hereafter SEIR) during the BGR cruise INDEX2012 with RV FUGRO GAUSS. The survey area covered the ridge from the Rodriguez Triple Junction along about 500 km towards the SSE direction. Gravity and magnetic data were measured along 65 profiles with a mean length of 60 km running approximately perpendicular to the ridge axis. The final gravity data were evaluated every 20 seconds along each profile. This results in a sampling interval of about 100 m. The mean spacing of the profiles is about 7 km. Together with the geophysical data also the bathymetry was measured along all profiles with a Kongsberg Simrad EM122 multibeam echosounder system. Previous studies reveal that the part of the ridge covered by the high resolution profiles is characterized by young geologic events (the oldest one dates back to 1 Ma) and that the SEIR is an intermediate spreading ridge. We extended the length of each profile to the area outside the ridge, integrating INDEX2012 high resolution gravity and bathymetric data with low resolution data derived from satellite radar altimeter measurements. The 3D forward gravity modeling made it possible to reconstruct a rough crustal density model for an extended area (about 250000 km2) of the SEIR. We analyzed the gravity signal along those 2D sections which cross particular geological features (uplifted areas, accommodation zones, hydrothermal fields and areas with hints for extensional processes e.g. OCCs) in order to establish a correlation between the gravity anomaly signal and the surface geology. We started with a simple "layer-cake" geologic model consisting of four density bodies which represent the sea, upper oceanic crust, lower oceanic crust and the upper mantle. Considering that in the study area the oceanic crust is young, we did not include the sediment layer. We assumed the density values of these bodies considering the relation between the density and the seismic P-wave velocity VP. We choose the velocity data from the scientific literature. We found that the "layer-cake" model does not explain the measured anomalies satisfyingly and lateral density changes have to be considered for the area beneath the ridge axis. Accordingly we reduced the density values of the lower crust and the upper mantle beneath the axial ridge introducing in the model two additional bodies called partial melted crust and anomalous mantle. Finally we present isobaths maps of the anomalous mantle which highlight the lateral heterogeneity of the oceanic crust beneath the ridge axis. In particular there are areas characterized by crustal thickening related to magmatic accretion and areas of crustal thinning related to depleted accretion of the mantle which can lead to the exposure of OCCs.

Complex Tectono-Magmatic Interaction along the George V Transform Fault, South-East Indian Ridge, 140°E, and Implications for Mantle Dynamics

NASA Astrophysics Data System (ADS)

Briais, A.; Ruellan, E.; Ceuleneer, G.; Maia, M.

2017-12-01

The 300 km-offset George V Transform Fault (TF) is the westernmost of the major, right-stepping transform faults that offset the South-East Indian Ridge between 140°E and 155°E. All these TFs have multiple shear zones with intra-transform ridge segments (ITRS), mostly unmapped yet. We present the results of the analysis of geophysical and petrological data collected during the STORM cruise (South Tasmania Ocean Ridge and Mantle). The data cover the western shear zone and part of two ITRSs. They reveal a complex interaction between tectonic processes at the plate boundary and near-axis volcanic activity along and across the transform fault. The western TF shear zone consists of two segments offset by a 50 km-long, 15 km-wide, up to 2000 m-high serpentinite massif. We infer that the massif is a push-up resulting from transpression along the transform, due to the lengthening of the western ITRS, with a mechanism similar to the processes currently uplifting the mylonitic massif along the St. Paul TF in the Equatorial Atlantic (1). The western ITRS is relatively shallow and magmatically robust, which is unexpected in a TF system. The bathymetric and backscatter maps also reveal a series of recent off-axis oblique volcanic ridges. Rocks dredged on one of these ridges consist of picrites (i.e. basalts rich in olivine phenocrysts). These observations suggest that the TF there is not magma starved like many mid-ocean ridge transforms, but is the locus of significant primitive melt supply. Such an unexpected production of high-Mg melt might be related to the presence of a mantle thermal anomaly beneath the easternmost SEIR, and/or to a western flow of mantle across the TF. *STORM cruise scientific party: A. Briais, F. Barrere, C. Boulart, D. Brunelli, G. Ceuleneer, N. Ferreira, B. Hanan, C. Hémond, S. Macleod, M. Maia, A. Maillard, S. Merkuryev, S.H. Park, S. Révillon, E. Ruellan, A. Schohn, S. Watson, and Y.S. Yang. (1) Maia et al. 2016 Nature Geo. doi:10.1038/ngeo2759

Mapping and Monitoring Delmarva Fox Squirrel Habitat Using an Airborne LiDAR Profiler

NASA Technical Reports Server (NTRS)

Nelson, Ross; Ratnaswamy, Mary; Keller, Cherry

2004-01-01

Twenty five hundred thirty nine kilometers of airborne laser profiling and videography data were acquired over the state of Delaware during the summer of 2000. The laser ranging measurements and video from approximately one-half of that data set (1304 km) were analyzed to identify and locate forested sites that might potentially support populations of Delmarva fox squirrel (DFS, Sciurus niger cinereus). The DFS is an endangered species previously endemic to tall, dense, mature forests with open understories on the Eastern Shore of the Chesapeake Bay. The airborne LiDAR employed in this study can measure forest canopy height and canopy closure, but cannot measure or infer understory canopy conditions. Hence the LiDAR must be viewed as a tool to map potential, not actual, habitat. Fifty-three potentially suitable DFS sites were identified in the 1304 km of flight transect data. Each of the 53 sites met the following criteria according to the LiDAR and video record: (1 ) at least 120m of contiguous forest; (2) an average canopy height greater than 20m; (3) an average canopy closure of >80%; and (4) no roofs, impervious surface (e.g., asphalt, concrete), and/or open water anywhere along the 120m length of the laser segment. Thirty-two of the 53 sites were visited on the ground and measurements taken for a DFS habitat suitability model. Seventy eight percent of the sites (25 of 32) were judged by the model to be suited to supporting a DFS population. Twenty-eight of the 32 sites visited in the field were in forest cover types (hardwood, mixed wood, conifer, wetlands) according to a land cover GIS map. Of these, 23 (82%) were suited to support DFS. The remaining 4 sites were located in nonforest cover types - agricultural or residential areas. Two of the four, or 50% were suited to the DFS. All of the LiDAR flight data, 2539 km, were analyzed to

Characterizing stand-level forest canopy cover and height using Landsat time series, samples of airborne LiDAR, and the Random Forest algorithm

NASA Astrophysics Data System (ADS)

Ahmed, Oumer S.; Franklin, Steven E.; Wulder, Michael A.; White, Joanne C.

2015-03-01

Many forest management activities, including the development of forest inventories, require spatially detailed forest canopy cover and height data. Among the various remote sensing technologies, LiDAR (Light Detection and Ranging) offers the most accurate and consistent means for obtaining reliable canopy structure measurements. A potential solution to reduce the cost of LiDAR data, is to integrate transects (samples) of LiDAR data with frequently acquired and spatially comprehensive optical remotely sensed data. Although multiple regression is commonly used for such modeling, often it does not fully capture the complex relationships between forest structure variables. This study investigates the potential of Random Forest (RF), a machine learning technique, to estimate LiDAR measured canopy structure using a time series of Landsat imagery. The study is implemented over a 2600 ha area of industrially managed coastal temperate forests on Vancouver Island, British Columbia, Canada. We implemented a trajectory-based approach to time series analysis that generates time since disturbance (TSD) and disturbance intensity information for each pixel and we used this information to stratify the forest land base into two strata: mature forests and young forests. Canopy cover and height for three forest classes (i.e. mature, young and mature and young (combined)) were modeled separately using multiple regression and Random Forest (RF) techniques. For all forest classes, the RF models provided improved estimates relative to the multiple regression models. The lowest validation error was obtained for the mature forest strata in a RF model (R2 = 0.88, RMSE = 2.39 m and bias = -0.16 for canopy height; R2 = 0.72, RMSE = 0.068% and bias = -0.0049 for canopy cover). This study demonstrates the value of using disturbance and successional history to inform estimates of canopy structure and obtain improved estimates of forest canopy cover and height using the RF algorithm.

The effects of strain heterology on the epidemiology of equine influenza in a vaccinated population.

PubMed Central

Park, A. W.; Wood, J. L. N.; Daly, J. M.; Newton, J. R.; Glass, K.; Henley, W.; Mumford, J. A.; Grenfell, B. T.

2004-01-01

We assess the effects of strain heterology (strains that are immunologically similar but not identical) on equine influenza in a vaccinated population. Using data relating to individual animals, for both homologous and heterologous vaccinees, we estimate distributions for the latent and infectious periods, quantify the risk of becoming infected in terms of the quantity of cross-reactive antibodies to a key surface protein of the virus (haemagglutinin) and estimate the probability of excreting virus (i.e. becoming infectious) given that infection has occurred. The data suggest that the infectious period, the risk of becoming infected (for a given vaccine-induced level of cross-reactive antibodies) and the probability of excreting virus are increased for heterologously vaccinated animals when compared with homologously vaccinated animals. The data are used to parameterize a modified susceptible, exposed, infectious and recovered/resistant (SEIR) model, which shows that these relatively small differences combine to have a large effect at the population level, where populations of heterologous vaccinees face a significantly increased risk of an epidemic occurring. PMID:15306299

On the discretization and control of an SEIR epidemic model with a periodic impulsive vaccination

NASA Astrophysics Data System (ADS)

Alonso-Quesada, S.; De la Sen, M.; Ibeas, A.

2017-01-01

This paper deals with the discretization and control of an SEIR epidemic model. Such a model describes the transmission of an infectious disease among a time-varying host population. The model assumes mortality from causes related to the disease. Our study proposes a discretization method including a free-design parameter to be adjusted for guaranteeing the positivity of the resulting discrete-time model. Such a method provides a discrete-time model close to the continuous-time one without the need for the sampling period to be as small as other commonly used discretization methods require. This fact makes possible the design of impulsive vaccination control strategies with less burden of measurements and related computations if one uses the proposed instead of other discretization methods. The proposed discretization method and the impulsive vaccination strategy designed on the resulting discretized model are the main novelties of the paper. The paper includes (i) the analysis of the positivity of the obtained discrete-time SEIR model, (ii) the study of stability of the disease-free equilibrium point of a normalized version of such a discrete-time model and (iii) the existence and the attractivity of a globally asymptotically stable disease-free periodic solution under a periodic impulsive vaccination. Concretely, the exposed and infectious subpopulations asymptotically converge to zero as time tends to infinity while the normalized subpopulations of susceptible and recovered by immunization individuals oscillate in the context of such a solution. Finally, a numerical example illustrates the theoretic results.

Historical Inflation Program. A Computer Program Generating Historical Inflation Indices for Army Aircraft. Revision.

DTIC Science & Technology

1984-01-01

data comes in three published formats: (1) a cumulative history coverina past years on a monthly basis, 5 (2) yearly supplements (such as wage and...all fisca. ea’r :. ma. Outzu: _ dNx’resse as monthly, quarterly, fiscal vear, and .-r ear 4n- :~n.e (in calen- dar year 1967 base) and inflation faCt...These indices and factors provide a means of adjusting historical cost data for the procurement of Army aircraft to constant year dollars. Additional

Development of Technologies for Early Detection and Stratification of Breast Cancer

DTIC Science & Technology

2014-10-01

cancer. Similar screening has been done in urine samples with CYR61 and LCN2 (Figure 2a-b). The Moses lab provided breast cancer urine samples and two ...diseased samples, while CYR61 appears to have two different populations whereas diseased urine samples have lower levels of the protein present. More... system for eDAR so that each isolated cell can be deposited into a well of a 96-well plate for high-throughput downstream single-cell digital

Results from a 14-month hydroacoustic monitoring of the three mid-oceanic ridges in the Indian Ocean

NASA Astrophysics Data System (ADS)

Royer, J.-Y.; Dziak, R. P.; Delatre, M.; Chateau, R.; Brachet, C.; Haxel, J. H.; Matsumoto, H.; Goslin, J.; Brandon, V.; Bohnenstielh, D. R.

2009-04-01

From October 2006 to January 2008, an hydroacoustic experiment in the Indian Ocean was carried out by the CNRS/University of Brest and NOAA/Oregon State University to monitor the low-level seismic activity associated with the three contrasting spreading ridges and deforming zones in the Indian Ocean. Three autonomous hydrophones were moored in the SOFAR channel by R/V Marion Dufresne for 14 months in the Madagascar Basin, and northeast and southwest of Amsterdam Island, complementing the two permanent hydroacoustic stations of the Comprehensive nuclear-Test-Ban Treaty Organization (CTBTO) located near Diego Garcia Island and off Cape Leeuwin. The three instruments successfully collected 14 month of continuous acoustic records. Combined with the records from the permanent stations, the array detected 1780 acoustic events consisting mostly of earthquake generated T-waves, but also of iceberg tremors from Wilkes Land, Antarctica. Within the triangle defined by the temporary array, the three ridges exhibit contrasting seismicity patterns. Along the Southeast Indian ridge (SEIR), the 272 acoustic events (vs 24 events in the NEIC catalog) occur predominantly along the transform faults ; only one ridge segment (76˚E) displays a continuous activity for 10 months. Along the Central Indian Ridge (CIR), seismicity is distributed along fracture zones and ridge segments (269 events vs 45 NEIC events), with two clusters of events near the triple junction (24-25S) and south of Marie-Celeste FZ (18.5S). Along the Southwest Indian Ridge (SWIR), the 222 events (vs 31 NEIC events) are distributed along the ridge segments with a larger number of events west of Melville FZ and a cluster at 58E. The immediate vicinity of the Rodrigues triple junction shows periods of quiescence and of intense activity. Some large earthquakes (Mb>5) near the triple junction (SEIR and CIR) seem to be preceded by several acoustic events that may be precursors. Finally, off-ridge seismicity is mostly detected in the southern part of the Central Indian Basin as a result of the intraplate deformation between the Capricorn and Australian plates. Other signals of interest are identified such as a 6-week long series of broadband (1-125 Hz) explosive signals detected only by the instrument located between Kerguelen and Amsterdam islands, many cryogenic tremors easily recognizable from their varying tones and harmonics, some of which can be precisely located off the Antarctic shelf, and finally whale calls attributed to four different whale species. This vocal activity is found to be highly seasonal, occurring mainly from April to October with subspecies variations. Detailed analyses of this unique data set are still underway.

Uncertainties in mapping forest carbon in urban ecosystems.

PubMed

Chen, Gang; Ozelkan, Emre; Singh, Kunwar K; Zhou, Jun; Brown, Marilyn R; Meentemeyer, Ross K

2017-02-01

Spatially explicit urban forest carbon estimation provides a baseline map for understanding the variation in forest vertical structure, informing sustainable forest management and urban planning. While high-resolution remote sensing has proven promising for carbon mapping in highly fragmented urban landscapes, data cost and availability are the major obstacle prohibiting accurate, consistent, and repeated measurement of forest carbon pools in cities. This study aims to evaluate the uncertainties of forest carbon estimation in response to the combined impacts of remote sensing data resolution and neighborhood spatial patterns in Charlotte, North Carolina. The remote sensing data for carbon mapping were resampled to a range of resolutions, i.e., LiDAR point cloud density - 5.8, 4.6, 2.3, and 1.2 pt s/m 2 , aerial optical NAIP (National Agricultural Imagery Program) imagery - 1, 5, 10, and 20 m. Urban spatial patterns were extracted to represent area, shape complexity, dispersion/interspersion, diversity, and connectivity of landscape patches across the residential neighborhoods with built-up densities from low, medium-low, medium-high, to high. Through statistical analyses, we found that changing remote sensing data resolution introduced noticeable uncertainties (variation) in forest carbon estimation at the neighborhood level. Higher uncertainties were caused by the change of LiDAR point density (causing 8.7-11.0% of variation) than changing NAIP image resolution (causing 6.2-8.6% of variation). For both LiDAR and NAIP, urban neighborhoods with a higher degree of anthropogenic disturbance unveiled a higher level of uncertainty in carbon mapping. However, LiDAR-based results were more likely to be affected by landscape patch connectivity, and the NAIP-based estimation was found to be significantly influenced by the complexity of patch shape. Copyright © 2016 Elsevier Ltd. All rights reserved.

A fighter's comeback: dopamine is necessary for recovery of aggression after social defeat in crickets.

PubMed

Rillich, Jan; Stevenson, Paul A

2014-09-01

Social defeat, i.e. losing an agonistic dispute with a conspecific, is followed by a period of suppressed aggressiveness in many animal species, and is generally regarded as a major stressor, which may play a role in psychiatric disorders such as depression and post-traumatic stress disorder. Despite numerous animal models, the mechanisms underlying loser depression and subsequent recovery are largely unknown. This study on crickets is the first to show that a neuromodulator, dopamine (DA), is necessary for recovery of aggression after social defeat. Crickets avoid any conspecific male just after defeat, but regain their aggressiveness over 3 h. This recovery was prohibited after depleting nervous stores of DA and octopamine (OA, the invertebrate analogue of noradrenaline) with α-methyl-tyrosine (AMT). Loser recovery was also prohibited by the insect DA-receptor (DAR) antagonist fluphenazine, but not the OA-receptor (OAR) blocker epinastine, or yohimbine, which blocks receptors for OA's precursor tyramine. Conversely, aggression was restored prematurely in both untreated and amine depleted losers given either chlordimeform (CDM), a tissue permeable OAR-agonist, or the DA-metabolite homovanillyl alcohol (HVA), a component of the honeybee queen mandibular pheromone. As in honeybees, HVA acts in crickets as a DAR-agonist since its aggression promoting effect on losers was selectively blocked by the DAR-antagonist, but not by the OAR-antagonist. Conversely, CDM's aggression promoting effect was selectively blocked by the OAR-antagonist, but not the DAR-antagonist. Hence, only DA is necessary for recovery of aggressiveness after social defeat, although OA can promote loser aggression independently to enable experience dependent adaptive responses. Copyright © 2014 Elsevier Inc. All rights reserved.

Landslide Investigation by Repeat Airborne LiDAR and Ground Monitoring in the Western Suburb of Sapporo, Japan

NASA Astrophysics Data System (ADS)

Kasai, M.; Marutani, T.; Yoshida, H.

2014-12-01

This study presents landslide investigation using the combination of airborne LiDAR and ground monitoring data. The study site is located on the Teine Landslide (width: 2 km, Length: 6.5 km) in the western suburb of Sapporo city in Hokkaido Island, Japan, which collapsed more than 50,000 years ago. Since then streams have been developing and incising the landslide mass consisted of rock debris and volcanic deposits, presently causing a series of small deep-seated landslides along the banks. Because Sapporo is the economic center of Hokkaido and the suburb is expanding at the toe of the Teine slide, it is important to understand the behaviors of these active slopes to protect residents and infrastructures from unexpected disasters possibly triggered by an intense storm or earthquake. The LiDAR data for the area was first obtained by a manned helicopter in August 2010, and another survey by an unmanned helicopter is planned in autumn 2014 to estimate their activities from changes in the ground surfaces during the period from 2010 to 2014. Ground water level and landslide mass movements have also been monitored on site by using the coring holes for sampling since 2013. The combination of the data sets can make up the deficits of these methods, e.g., errors created through data processing for LiDAR survey and spatially limited information for ground monitoring, enabling to provide a solid three dimensional view of the slope movements. The notion obtained can be utilized to predict their future behaviors as well as to discover active but hiding landslides nearby. This study also showed that repeat monitoring of sites is a way of utilizing UAVs, particularly in terms of cost and convenience.

Mangrove classification through the use of object oriented classification and support vector machine of lidar datasets: a case study in Naawan and Manticao, Misamis Oriental, Philippines

NASA Astrophysics Data System (ADS)

Jalbuena, Rey L.; Peralta, Rudolph V.; Tamondong, Ayin M.

2016-10-01

Mangroves are trees or shrubs that grows at the surface between the land and the sea in tropical and sub-tropical latitudes. Mangroves are essential in supporting various marine life, thus, it is important to preserve and manage these areas. There are many approaches in creating Mangroves maps, one of which is through the use of Light Detection and Ranging (LiDAR). It is a remote sensing technique which uses light pulses to measure distances and to generate three-dimensional point clouds of the Earth's surface. In this study, the topographic LiDAR Data will be used to analyze the geophysical features of the terrain and create a Mangrove map. The dataset that we have were first pre-processed using the LAStools software. It is a software that is used to process LiDAR data sets and create different layers such as DSM, DTM, nDSM, Slope, LiDAR Intensity, LiDAR number of first returns, and CHM. All the aforementioned layers together was used to derive the Mangrove class. Then, an Object-based Image Analysis (OBIA) was performed using eCognition. OBIA analyzes a group of pixels with similar properties called objects, as compared to the traditional pixel-based which only examines a single pixel. Multi-threshold and multiresolution segmentation were used to delineate the different classes and split the image into objects. There are four levels of classification, first is the separation of the Land from the Water. Then the Land class was further dived into Ground and Non-ground objects. Furthermore classification of Nonvegetation, Mangroves, and Other Vegetation was done from the Non-ground objects. Lastly Separation of the mangrove class was done through the Use of field verified training points which was then run into a Support Vector Machine (SVM) classification. Different classes were separated using the different layer feature properties, such as mean, mode, standard deviation, geometrical properties, neighbor-related properties, and textural properties. Accuracy assessment was done using a different set of field validation points. This workflow was applied in the classification of Mangroves to a LiDAR dataset of Naawan and Manticao, Misamis Oriental, Philippines. The process presented in this study shows that LiDAR data and its derivatives can be used in extracting and creating Mangrove maps, which can be helpful in managing coastal environment.

A comparison of water vapor quantities from model short-range forecasts and ARM observations

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

Hnilo, J J

2006-03-17

Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the 'Merged-sounding' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGPmore » and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.« less

A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations (in English; Croatian)

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

Hnilo, J.

2006-03-17

Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the “Mergedsounding” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGPmore » and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.« less

Efficacy of Waterless Hand Hygiene Compared with Handwashing with Soap: A Field Study in Dar es Salaam, Tanzania

PubMed Central

Pickering, Amy J.; Boehm, Alexandria B.; Mwanjali, Mathew; Davis, Jennifer

2010-01-01

Effective handwashing with soap requires reliable access to water supplies. However, more than three billion persons do not have household-level access to piped water. This research addresses the challenge of improving hand hygiene within water-constrained environments. The antimicrobial efficacy of alcohol-based hand sanitizer, a waterless hand hygiene product, was evaluated and compared with handwashing with soap and water in field conditions in Dar es Salaam, Tanzania. Hand sanitizer use by mothers resulted in 0.66 and 0.64 log reductions per hand of Escherichia coli and fecal streptococci, respectively. In comparison, handwashing with soap resulted in 0.50 and 0.25 log reductions per hand of E. coli and fecal streptococci, respectively. Hand sanitizer was significantly better than handwashing with respect to reduction in levels of fecal streptococci (P = 0.01). The feasibility and health impacts of promoting hand sanitizer as an alternative hand hygiene option for water-constrained environments should be assessed. PMID:20134005

Simulation and Analysis of Neutron Activation Risk for the IsoDAR High-Intensity Electron Antineutrino Source

NASA Astrophysics Data System (ADS)

Skuhersky, Michael

2013-04-01

IsoDAR (Isotope Decay-At-Rest) is a proposed high-intensity source of electron antineutrinos intended for use in searches for beyond standard model physics, the main analysis being a short baseline search for sterile neutrinos at a kiloton scale liquid scintillator detector. The source uses a compact cyclotron to deliver 600kW of protons at 60 MeV/nucleon in the form of H2^+ onto a Beryllium target which produces a large intermediate energy neutron flux. These neutrons thermalize and capture on a 99.9% pure ^7Li sleeve, which produces ^8Li at rest, which subsequently beta decays producing νe. Due to the high neutron fluxes, large duty factor, and low background environment surrounding the neutrino detector, we need to understand the activation risk and design a shield to minimize this risk allowing for the safe operation of the source. I will report on my neutron activation studies and the benchmarking of Geant4 for these applications.

Discretization and control of an SEIR epidemic model under equilibrium Wiener noise disturbances

NASA Astrophysics Data System (ADS)

Alonso, Santiago; De la Sen, Manuel; Nistal, Raul; Ibeas, Asier

2017-11-01

A discretized SEIR epidemic model, subject to Wiener noise disturbances of the equilibrium points, is studied. The discrete-time model is got from a general discretization technique applied to its continuous-time counterpart so that its behaviour be close to its continuous-time counterpart irrespective of the size of the discretization period. The positivity and stability of a normalized version of such a discrete-time model are emphasized. The paper also proposes the design of a periodic impulsive vaccination which is periodically injected to the susceptible subpopulation in order to eradicate the propagation of the disease or, at least, to reduce its unsuitable infective effects within the potentially susceptible subpopulation. The existence and asymptotic stability of a disease-free periodic solution are proved. In particular, both the exposed and infectious subpopulations converge asymptotically to zero as time tends to infinity while the normalized subpopulations of susceptible and recovered by immunization oscillate.

Fusion of Remote Sensing Methods, UAV Photogrammetry and LiDAR Scanning products for monitoring fluvial dynamics

NASA Astrophysics Data System (ADS)

Lendzioch, Theodora; Langhammer, Jakub; Hartvich, Filip

2015-04-01

Fusion of remote sensing data is a common and rapidly developing discipline, which combines data from multiple sources with different spatial and spectral resolution, from satellite sensors, aircraft and ground platforms. Fusion data contains more detailed information than each of the source and enhances the interpretation performance and accuracy of the source data and produces a high-quality visualisation of the final data. Especially, in fluvial geomorphology it is essential to get valuable images in sub-meter resolution to obtain high quality 2D and 3D information for a detailed identification, extraction and description of channel features of different river regimes and to perform a rapid mapping of changes in river topography. In order to design, test and evaluate a new approach for detection of river morphology, we combine different research techniques from remote sensing products to drone-based photogrammetry and LiDAR products (aerial LiDAR Scanner and TLS). Topographic information (e.g. changes in river channel morphology, surface roughness, evaluation of floodplain inundation, mapping gravel bars and slope characteristics) will be extracted either from one single layer or from combined layers in accordance to detect fluvial topographic changes before and after flood events. Besides statistical approaches for predictive geomorphological mapping and the determination of errors and uncertainties of the data, we will also provide 3D modelling of small fluvial features.

Scintillation measurements at Bahir Dar during the high solar activity phase of solar cycle 24

NASA Astrophysics Data System (ADS)

Kriegel, Martin; Jakowski, Norbert; Berdermann, Jens; Sato, Hiroatsu; Wassaie Mersha, Mogese

2017-01-01

Small-scale ionospheric disturbances may cause severe radio scintillations of signals transmitted from global navigation satellite systems (GNSSs). Consequently, small-scale plasma irregularities may heavily degrade the performance of current GNSSs such as GPS, GLONASS or Galileo. This paper presents analysis results obtained primarily from two high-rate GNSS receiver stations designed and operated by the German Aerospace Center (DLR) in cooperation with Bahir Dar University (BDU) at 11.6° N, 37.4° E. Both receivers collect raw data sampled at up to 50 Hz, from which characteristic scintillation parameters such as the S4 index are deduced. This paper gives a first overview of the measurement set-up and the observed scintillation events over Bahir Dar in 2015. Both stations are located close to one another and aligned in an east-west, direction which allows us to estimate the zonal drift velocity and spatial dimension of equatorial ionospheric plasma irregularities. Therefore, the lag times of moving electron density irregularities and scintillation patterns are derived by applying cross-correlation analysis to high-rate measurements of the slant total electron content (sTEC) along radio links between a GPS satellite and both receivers and to the associated signal power, respectively. Finally, the drift velocity is derived from the estimated lag time, taking into account the geometric constellation of both receiving antennas and the observed GPS satellites.

A resolved mantle anomaly as the cause of the Australian-Antarctic Discordance

NASA Astrophysics Data System (ADS)

Ritzwoller, M. H.; Shapiro, N. M.; Leahy, G. M.

2003-12-01

We present evidence for the existence of an Australian-Antarctic Mantle Anomaly (AAMA), which trends northwest-southeast (NW-SE) through the Australian-Antarctic Discordance (AAD) on the Southeast Indian Ridge (SEIR), is confined to the upper 120 km of the mantle beneath the AAD, and dips shallowly to the west so that it extends to a depth of about 150 km west of the AAD. Average temperatures within the AAMA are depressed about 100°C relative to surrounding lithosphere and suggest very rapid cooling of newly formed lithosphere at the AAD to an effective thermal age between 20 and 30 Ma. A convective down welling beneath the AAD is not consistent with the confinement of the AAMA in the uppermost mantle. In substantial agreement with the model of [1998], we argue that the AAMA is the suspended remnant of a slab that subducted at the Gondwanaland-Pacific convergent margin more than 100 Myr ago, foundered in the deeper mantle, and then ascended into the shallow mantle within the past 30 Myr, cutting any ties to deeper roots. The stability of the AAMA and its poor correlation with residual topography and gravity imply that it is approximately neutrally buoyant. The thermally induced density anomaly can be balanced by bulk iron depletion of less than 0.8%, consistent with the warmer conditions of formation for the Pacific than Indian lithosphere. We hypothesize that the low temperatures in the AAMA inhibit crustal formation and the AAD depth anomaly is formed at the intersection of the SEIR and the AAMA. The northward migration of the SEIR overriding the cold NW-SE trending AAMA therefore presents a simple kinematic explanation for both the V-shaped residual depth anomaly in the southeast Indian Ocean and the western migration of the AAD along the SEIR. Neither explanation requires the Pacific asthenospheric mantle to push westward and displace Indian asthenosphere. The AAMA may also act as a barrier to large-scale flows in the shallow asthenosphere and may therefore define a boundary for mantle convection and between the Indian and Pacific isotopic provinces. The westward dip of the AAMA would also favor along-axis flow from the Indian Ocean asthenosphere to the AAD that may contribute to the penetration of Indian Ocean mid-ocean ridge basalts into the AAD.

Perceptional gaps among women, husbands and family members about intentions for birthplace: a cross-sectional study.

PubMed

Shimpuku, Yoko; Madeni, Frida Elikana; Horiuchi, Shigeko; Leshabari, Sebalda Charles

2017-01-30

women are more likely to give birth at a health facility when their families agree with the birthplace. However, in rural areas of Tanzania, women are often marginalized from decision-making. This study predicted birthplace intention and identified factors to reduce perceptional gaps among pregnant women, husbands and family members. explanatory cross-sectional survey was conducted in three villages in North Eastern Tanzania. Participants were 138 pregnant women and their families who answered the Birth Intention Questionnaire (BIQ), measuring knowledge, attitude, perceived behavioral control, subjective norms and intention for birthplace. Descriptive analysis, ANOVA, Chi-square, and multiple linear regression was used to analyze the data. the regression model showed that knowledge, perceived behavioral control, and subjective norms predicted intention for birthplace (R2 = .28). While 81% of pregnant women thought their husbands were decision-makers for their birth, only 38% of husbands and 37% of family members agreed. Pregnant women had significantly lower scores on the item "I will prepare for childbirth with my family" compared with husbands (p < .01) and other family members (p < .001). providing evidence-based birth preparation and reducing the identified perceptual gaps may enhance women's intention to deliver at health facilities. as mulheres são mais propensas a dar à luz em um centro de saúde quando suas famílias estão de acordo com o local de nascimento. No entanto, nas áreas rurais da Tanzânia, as mulheres são muitas vezes marginalizadas do processo de decisão. Este estudo fez previsoes de intenção para o local do parto e fatores para reduzir as lacunas de percepção entre as mulheres grávidas, seus maridos e familiares identificados. estudo transversal explicativo realizado em três aldeias no nordeste da Tanzânia. Os participantes foram 138 mulheres grávidas e suas famílias que responderam ao Questionário de Intenção sobre Parto (BIQ), medindo o conhecimento, atitude, percepcão de controle comportamental, normas subjetivas e intenção para lugar de parto. Análise descritivas, ANOVA, Qui-quadrado e regressão linear múltipla foram utilizados para analisar os dados. o modelo de regressão mostrou que o conhecimento, percepcão de controle comportamental e normas subjetivas previram intenção de lugar de parto (R2 = 0,28). Enquanto 81% das mulheres grávidas pensavam que seus maridos eram os decisores para seu parto, apenas 38% dos maridos e 37% dos membros da família concordaram. As mulheres grávidas tiveram escores significativamente mais baixos sobre o item "Vou me preparar para o parto com a minha família", em comparação com os maridos (p < 0,01) e outros membros da família (p < 0,001). Proporcionar preparação para o parto baseada em evidencias e a redução das lacunas de percepção identificadas podem melhorar a intenção das mulheres para dar à luz em unidades de saúde. las mujeres son más propensas a dar a luz en un centro de salud cuando sus familias están de acuerdo con el lugar de parto. Sin embargo, en las zonas rurales de Tanzania, las mujeres son a menudo marginadas de la toma de decisiones. Este estudio predijo la intención del lugar de parto y los factores identificados para reducir la brecha de percepción entre las mujeres embarazadas, esposos y miembros de la familia. encuesta transversal explicativa llevada a cabo en tres aldeas en el noreste de Tanzania. Los participantes fueron 138 mujeres embarazadas y sus familias, que respondieron al Cuestionario sobre Intención del Parto (BIQ), que mide el conocimiento, la actitud, percepción de control del comportamiento, las normas subjetivas y la intención de lugar de parto. Se utilizaron análisis descriptivo, ANOVA, Chi-cuadrado y regresión lineal múltiple para analizar los datos. el modelo de regresión mostró que el conocimiento, la percepción de control del comportamiento, y las normas subjetivas predijeron la intencion del lugar de parto (R2 = 0,28). Mientras que el 81% de las mujeres embarazadas pensaba que sus maridos estaban encargados de tomar decisiones para el nacimiento, sólo el 38% de los esposos y el 37% de los miembros de la familia estuvieron de acuerdo. Las mujeres embarazadas tenían puntuaciones significativamente más bajas en el tema "Me prepararé para el parto con mi familia", en comparación con los maridos (p < 0,01) y otros miembros de la familia (p < 0,001). proporcionar la preparación al parto basada en la evidencia y reducir las brechas de percepción identificadas pueden mejorar intención de las mujeres a dar a luz en centros de salud.

Quantifying Wave Breaking Shape and Type in the Surf-Zone Using LiDAR

NASA Astrophysics Data System (ADS)

Albright, A.; Brodie, K. L.; Hartzell, P. J.; Glennie, C. L.

2017-12-01

Waves change shape as they shoal and break across the surf-zone, ultimately dissipating and transferring their energy into turbulence by either spilling or plunging. This injection of turbulence and changes in wave shape can affect the direction of sediment transport at the seafloor, and ultimately lead to morphological evolution. Typical methods for collecting wave data in the surf-zone include in-situ pressure gauges, velocimeters, ultrasonic sensors, and video imagery. Drawbacks to these data collection methods are low spatial resolution of point measurements, reliance on linear theory to calculate sea-surface elevations, and intensive computations required to extract wave properties from stereo 2D imagery. As a result, few field measurements of the shapes of plunging and/or spilling breakers exist, and existing knowledge is confined to results of laboratory studies. We therefore examine the use of a multi-beam scanning Light Detection and Ranging (LiDAR) remote sensing instrument with the goal of classifying the breaking type of propagating waves in the surf-zone and quantitatively determining wave morphometric properties. Data were collected with a Velodyne HDL-32E LiDAR scanner (360° vertical field of view) mounted on an arm of the Coastal Research Amphibious Buggy (CRAB) at the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina. Processed laser scan data are used to visualize the lifecycle of a wave (shoaling, breaking, broken) and identify wave types (spilling, plunging, non-breaking) as they pass beneath the scanner. For each rotation of the LiDAR scanner, the point cloud data are filtered, smoothed, and detrended in order to identify individual waves and measure their properties, such as speed, height, period, upward/downward slope, asymmetry, and skewness. The 3D nature of point cloud data is advantageous for research, because it enables viewing from any angle. In our analysis, plan views are used to separate individual waves, and cross-shore profiles are used to extract wave properties. Combined with accurate georeferencing information, LiDAR has the potential to be a powerful remote sensing tool for coastal monitoring systems and the study of nearshore processes.

Mapping and quantifying geodiversity in land-water transition zones using MBES and topobathymetric LiDAR

NASA Astrophysics Data System (ADS)

Brandbyge Ernstsen, Verner; Skovgaard Andersen, Mikkel; Gergely, Aron; Schulze Tenberge, Yvonne; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Winter, Christian; Bartholomä, Alexander

2016-04-01

Land-water transition zones, like e.g. coastal and fluvial environments, are valuable ecosystems which are often characterised by high biodiversity and geodiversity. However, often these land-water transition zones are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. Combining vessel borne shallow water multibeam echosounder (MBES) surveys ,to cover the subtidal coastal areas and the river channel areas, with airborne topobathymetric light detection and ranging (LiDAR) surveys, to cover the intertidal and supratidal coastal areas and the river floodplain areas, potentially enables full-coverage and high-resolution mapping in these challenging environments. We have carried out MBES and topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage, and in the Ribe Vesterå, a fluvial environment in the Ribe Å river catchment discharging into the Knudedyb tidal basin. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the MBES and the LiDAR point clouds, which both have point densities in the order of 20 points/m2. Morphometric analyses of the DEMs enabled the identification and mapping of the different landforms within the coastal and fluvial environments. Hereby, we demonstrate that vessel borne MBES and airborne topobathymetric LiDAR, here in combination, are promising tools for seamless mapping across land-water transition zones as well as for the quantification of a range of landforms at landscape scale in different land-water transition zone environments. Hence, we demonstrate the potential for mapping and quantifying geomorphological diversity, which is one of the main components of geodiversity and a prerequisite for assessing geoheritage. Acknowledgements This work was funded by the Danish Council for Independent Research | Natural Sciences through the project "Process-based understanding and prediction of morphodynamics in a natural coastal system in response to climate change" (Steno Grant no. 10-081102) and by the Geocenter Denmark through the project "Closing the gap! - Coherent land-water environmental mapping (LAWA)" (Grant no. 4-2015).

Joint Services Electronics Program Research in Electronics (University of Southern California, Electronic Sciences Laboratory)

DTIC Science & Technology

1990-01-05

submitted). 3. 0. J. Kim, A. Madhukar, W. Chen, K. Z. Hu, "Realization of High Mobilities at Ultra Low Electron Density in GaAs-Al O.3GaO.7As Inverted...to-Coherent Optical Conversion", in Photorefractive Materials and Aplications , J. P. Huignard and P. Gunter, Eds., Springer-Verlag, New York (1989). 2...Schottky Barrier Epitaxial Structures," USC Ph.D. Thesis (May 1989). 2. E. Garmire, N. M. Jokerst, A. Kost, A. Dar,---, and P. D. Dapkus, "Optical

UAS-Borne Photogrammetry for Surface Topographic Characterization: A Ground-Truth Baseline for Future Change Detection and Refinement of Scaled Remotely-Sensed Datasets

NASA Astrophysics Data System (ADS)

Coppersmith, R.; Schultz-Fellenz, E. S.; Sussman, A. J.; Vigil, S.; Dzur, R.; Norskog, K.; Kelley, R.; Miller, L.

2015-12-01

While long-term objectives of monitoring and verification regimes include remote characterization and discrimination of surficial geologic and topographic features at sites of interest, ground truth data is required to advance development of remote sensing techniques. Increasingly, it is desirable for these ground-based or ground-proximal characterization methodologies to be as nimble, efficient, non-invasive, and non-destructive as their higher-altitude airborne counterparts while ideally providing superior resolution. For this study, the area of interest is an alluvial site at the Nevada National Security Site intended for use in the Source Physics Experiment's (Snelson et al., 2013) second phase. Ground-truth surface topographic characterization was performed using a DJI Inspire 1 unmanned aerial system (UAS), at very low altitude (< 5-30m AGL). 2D photographs captured by the standard UAS camera payload were imported into Agisoft Photoscan to create three-dimensional point clouds. Within the area of interest, careful installation of surveyed ground control fiducial markers supplied necessary targets for field collection, and information for model georectification. The resulting model includes a Digital Elevation Model derived from 2D imagery. It is anticipated that this flexible and versatile characterization process will provide point cloud data resolution equivalent to a purely ground-based LiDAR scanning deployment (e.g., 1-2cm horizontal and vertical resolution; e.g., Sussman et al., 2012; Schultz-Fellenz et al., 2013). In addition to drastically increasing time efficiency in the field, the UAS method also allows for more complete coverage of the study area when compared to ground-based LiDAR. Comparison and integration of these data with conventionally-acquired airborne LiDAR data from a higher-altitude (~ 450m) platform will aid significantly in the refinement of technologies and detection capabilities of remote optical systems to identify and detect surface geologic and topographic signatures of interest. This work includes a preliminary comparison of surface signatures detected from varying standoff distances to assess current sensor performance and benefits.

The role of vegetation on gully erosion stabilization at a severely degraded landscape: A case study from Calhoun Experimental Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Bras, R. L.; Noto, L. V.; Istanbulluoglu, E.

2018-05-01

Gully erosion was evidence of land degradation in the southern Piedmont, site of the Calhoun Critical Zone Observatory (CCZO), during the cotton farming era. Understanding of the underlying gully erosion processes is essential to develop gully erosion models that could be useful in assessing the effectiveness of remedial and soil erosion control measures such as gully backfilling, revegetation, and terracing. Development and validation of process-based gully erosion models is difficult because observations of the formation and progression of gullies are limited. In this study, analytic formulations of the two dominant gullying processes, namely, plunge pool erosion and slab failure, are utilized to simulate the gullying processes in the 4-km2 Holcombe's Branch watershed. In order to calibrate parameters of the gully erosion model, gully features (e.g., depth and area) extracted from a high-resolution LiDAR map are used. After the calibration, the gully model is able to delineate the spatial extent of gullies whose statistics are in close agreement with the gullies extracted from the LiDAR DEM. Several simulations with the calibrated model are explored to evaluate the effectiveness of various gully remedial measures, such as backfilling and revegetation. The results show that in the short-term, the reshaping of the topographical surface by backfilling and compacting gullies is effective in slowing down the growth of gullies (e.g., backfilling decreased the spatial extent of gullies by 21-46% and decreased the average depth of gullies by up to 9%). Revegetation, however, is a more effective approach to stabilizing gullies that would otherwise expand if no gully remedial measures are implemented. Analyses of our simulations show that the gully stabilization effect of revegetation varies over a wide range, i.e., leading to 23-69% reduction of the spatial extent of gullies and up to 45% reduction in the depth of gullies, depending on the selection of plant species and management practices.

Back to the Future: Have Remotely Sensed Digital Elevation Models Improved Hydrological Parameter Extraction?

NASA Astrophysics Data System (ADS)

Jarihani, B.

2015-12-01

Digital Elevation Models (DEMs) that accurately replicate both landscape form and processes are critical to support modeling of environmental processes. Pre-processing analysis of DEMs and extracting characteristics of the watershed (e.g., stream networks, catchment delineation, surface and subsurface flow paths) is essential for hydrological and geomorphic analysis and sediment transport. This study investigates the status of the current remotely-sensed DEMs in providing advanced morphometric information of drainage basins particularly in data sparse regions. Here we assess the accuracy of three available DEMs: (i) hydrologically corrected "H-DEM" of Geoscience Australia derived from the Shuttle Radar Topography Mission (SRTM) data; (ii) the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) version2 1-arc-second (~30 m) data; and (iii) the 9-arc-second national GEODATA DEM-9S ver3 from Geoscience Australia and the Australian National University. We used ESRI's geospatial data model, Arc Hydro and HEC-GeoHMS, designed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. A coastal catchment in northeast Australia was selected as the study site where very high resolution LiDAR data are available for parts of the area as reference data to assess the accuracy of other lower resolution datasets. This study provides morphometric information for drainage basins as part of the broad research on sediment flux from coastal basins to Great Barrier Reef, Australia. After applying geo-referencing and elevation corrections, stream and sub basins were delineated for each DEM. Then physical characteristics for streams (i.e., length, upstream and downstream elevation, and slope) and sub-basins (i.e., longest flow lengths, area, relief and slopes) were extracted and compared with reference datasets from LiDAR. Results showed that, in the absence of high-precision and high resolution DEM data, ASTER GDEM or SRTM DEM can be used to extract common morphometric relationship which are widely used for hydrological and geomorphological modelling.

The Kilauea 1974 Flow: Quantitative Morphometry of Lava Flows using Low Altitude Aerial Image Data using a Kite-based Platform in the Field

NASA Astrophysics Data System (ADS)

Scheidt, S. P.; Whelley, P.; Hamilton, C.; Bleacher, J. E.; Garry, W. B.

2015-12-01

The December 31, 1974 lava flow from Kilauea Caldera, Hawaii within the Hawaii Volcanoes National Park was selected for field campaigns as a terrestrial analog for Mars in support of NASA Planetary Geology and Geophysics (PGG) research and the Remote, In Situ and Synchrotron Studies for Science and Exploration (RIS4E) node of the Solar System Exploration Research Virtual Institute (SSERVI) program). The lava flow was a rapidly emplaced unit that was strongly influenced by existing topography, which favored the formation of a tributary lava flow system. The unit includes a diverse range of surface textures (e.g., pāhoehoe, ´áā, and transitional lavas), and structural features (e.g., streamlined islands, pits, and interactions with older tumuli). However, these features are generally below the threshold of visibility within previously acquired airborne and spacecraft data. In this study, we have generated unique, high-resolution digital images using low-altitude Kite Aerial Photography (KAP) system during field campaigns in 2014 and 2015 (National Park Service permit #HAVO-2012-SCI-0025). The kite-based mapping platform (nadir-viewing) and a radio-controlled gimbal (allowing pointing) provided similar data as from an unmanned aerial vehicle (UAV), but with longer flight time, larger total data volumes per sortie, and fewer regulatory challenges and cost. Images acquired from KAP and UAVs are used to create orthomosaics and DEMs using Multi-View Stereo-Photogrammetry (MVSP) software. The 3-Dimensional point clouds are extremely dense, resulting in a grid resolution of < 2 cm. Airborne Light Detection and Ranging (LiDAR) / Terrestrial Laser Scanning (TLS) data have been collected for these areas and provide a basis of comparison or "ground truth" for the photogrammetric data. Our results show a good comparison with LiDAR/TLS data, each offering their own unique advantages and potential for data fusion.

Forecasting Epidemics Through Nonparametric Estimation of Time-Dependent Transmission Rates Using the SEIR Model.

PubMed

Smirnova, Alexandra; deCamp, Linda; Chowell, Gerardo

2017-05-02

Deterministic and stochastic methods relying on early case incidence data for forecasting epidemic outbreaks have received increasing attention during the last few years. In mathematical terms, epidemic forecasting is an ill-posed problem due to instability of parameter identification and limited available data. While previous studies have largely estimated the time-dependent transmission rate by assuming specific functional forms (e.g., exponential decay) that depend on a few parameters, here we introduce a novel approach for the reconstruction of nonparametric time-dependent transmission rates by projecting onto a finite subspace spanned by Legendre polynomials. This approach enables us to effectively forecast future incidence cases, the clear advantage over recovering the transmission rate at finitely many grid points within the interval where the data are currently available. In our approach, we compare three regularization algorithms: variational (Tikhonov's) regularization, truncated singular value decomposition (TSVD), and modified TSVD in order to determine the stabilizing strategy that is most effective in terms of reliability of forecasting from limited data. We illustrate our methodology using simulated data as well as case incidence data for various epidemics including the 1918 influenza pandemic in San Francisco and the 2014-2015 Ebola epidemic in West Africa.

Numerical solution of a spatio-temporal gender-structured model for hantavirus infection in rodents.

PubMed

Bürger, Raimund; Chowell, Gerardo; Gavilán, Elvis; Mulet, Pep; Villada, Luis M

2018-02-01

In this article we describe the transmission dynamics of hantavirus in rodents using a spatio-temporal susceptible-exposed-infective-recovered (SEIR) compartmental model that distinguishes between male and female subpopulations [L.J.S. Allen, R.K. McCormack and C.B. Jonsson, Bull. Math. Biol. 68 (2006), 511--524]. Both subpopulations are assumed to differ in their movement with respect to local variations in the densities of their own and the opposite gender group. Three alternative models for the movement of the male individuals are examined. In some cases the movement is not only directed by the gradient of a density (as in the standard diffusive case), but also by a non-local convolution of density values as proposed, in another context, in [R.M. Colombo and E. Rossi, Commun. Math. Sci., 13 (2015), 369--400]. An efficient numerical method for the resulting convection-diffusion-reaction system of partial differential equations is proposed. This method involves techniques of weighted essentially non-oscillatory (WENO) reconstructions in combination with implicit-explicit Runge-Kutta (IMEX-RK) methods for time stepping. The numerical results demonstrate significant differences in the spatio-temporal behavior predicted by the different models, which suggest future research directions.

NewsWire, 2000-2001.

ERIC Educational Resources Information Center

Richey, Nancy, Ed.; Byrom, Elizabeth, Ed.; Bingham, Margaret, Ed.; Guerrero, Jeanne, Ed.; Thrift, Beth, Ed.; Holton, Brook, Ed.

2001-01-01

This document contains five issues of "NewsWire," a newsletter created for the SouthEast and Islands Regional Technology in Education Consortium (SEIR-TEC). Topics addressed in these issues include: leadership and educational technology; technology program development; resources for teaching and learning with technology; U.S. Department of…

Investigating the performance of LiDAR-derived biomass information in hydromechanic slope stability modelling

NASA Astrophysics Data System (ADS)

Schmaltz, Elmar; Steger, Stefan; Bogaard, Thom; Van Beek, Rens; Glade, Thomas

2017-04-01

Hydromechanic slope stability models are often used to assess the landslide susceptibility of hillslopes. Some of these models are able to account for vegetation related effects when assessing slope stability. However, spatial information of required vegetation parameters (especially of woodland) that are defined by land cover type, tree species and stand density are mostly underrepresented compared to hydropedological and geomechanical parameters. The aim of this study is to assess how LiDAR-derived biomass information can help to distinguish distinct tree stand-immanent properties (e.g. stand density and diversity) and further improve the performance of hydromechanic slope stability models. We used spatial vegetation data produced from sophisticated algorithms that are able to separate single trees within a stand based on LiDAR point clouds and thus allow an extraordinary detailed determination of the aboveground biomass. Further, this information is used to estimate the species- and stand-related distribution of the subsurface biomass using an innovative approach to approximate root system architecture and development. The hydrological tree-soil interactions and their impact on the geotechnical stability of the soil mantle are then reproduced in the dynamic and spatially distributed slope stability model STARWARS/PROBSTAB. This study highlights first advances in the approximation of biomechanical reinforcement potential of tree root systems in tree stands. Based on our findings, we address the advantages and limitations of highly detailed biomass information in hydromechanic modelling and physically based slope failure prediction.

A comparison of waveform processing algorithms for single-wavelength LiDAR bathymetry

NASA Astrophysics Data System (ADS)

Wang, Chisheng; Li, Qingquan; Liu, Yanxiong; Wu, Guofeng; Liu, Peng; Ding, Xiaoli

2015-03-01

Due to the low-cost and lightweight units, single-wavelength LiDAR bathymetric systems are an ideal option for shallow-water (<12 m) bathymetry. However, one disadvantage of such systems is the lack of near-infrared and Raman channels, which results in difficulties in extracting the water surface. Therefore, the choice of a suitable waveform processing method is extremely important to guarantee the accuracy of the bathymetric retrieval. In this paper, we test six algorithms for single-wavelength bathymetric waveform processing, i.e. peak detection (PD), the average square difference function (ASDF), Gaussian decomposition (GD), quadrilateral fitting (QF), Richardson-Lucy deconvolution (RLD), and Wiener filter deconvolution (WD). To date, most of these algorithms have previously only been applied in topographic LiDAR waveforms captured over land. A simulated dataset and an Optech Aquarius dataset were used to assess the algorithms, with the focus being on their capability of extracting the depth and the bottom response. The influences of a number of water and equipment parameters were also investigated by the use of a Monte Carlo method. The results showed that the RLD method had a superior performance in terms of a high detection rate and low errors in the retrieved depth and magnitude. The attenuation coefficient, noise level, water depth, and bottom reflectance had significant influences on the measurement error of the retrieved depth, while the effects of scan angle and water surface roughness were not so obvious.

SEIIrR: Drug abuse model with rehabilitation

NASA Astrophysics Data System (ADS)

Sutanto, Azizah, Afina; Widyaningsih, Purnami; Saputro, Dewi Retno Sari

2017-05-01

Drug abuse in the world quite astonish and tend to increase. The increase and decrease on the number of drug abusers showed a pattern of spread that had the same characteristics with patterns of spread of infectious disease. The susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR) epidemic models for infectious disease was developed to study social epidemic. In this paper, SEIR model for disease epidemic was developed to study drug abuse epidemic with rehabilitation treatment. The aims of this paper were to analogize susceptible exposed infected isolated recovered (SEIIrR) model on the drug abusers, to determine solutions of the model, to determine equilibrium point, and to do simulation on β. The solutions of SEIIrR model was determined by using fourth order of Runge-Kutta algorithm, equilibrium point obtained was free-drug equilibrium point. Solutions of SEIIrR showed that the model was able to suppress the spread of drug abuse. The increasing value of contact rate was not affect the number of infected individuals due to rehabilitation treatment.

Procedural and short-term safety of bronchial thermoplasty in clinical practice: evidence from a national registry and Hospital Episode Statistics.

PubMed

Burn, Julie; Sims, Andrew J; Keltie, Kim; Patrick, Hannah; Welham, Sally A; Heaney, Liam G; Niven, Robert M

2017-10-01

Bronchial thermoplasty (BT) is a novel treatment for severe asthma. Its mode of action and ideal target patient group remain poorly defined, though clinical trials provided some evidence on efficacy and safety. This study presents procedural and short-term safety evidence from routine UK clinical practice. Patient characteristics and safety outcomes (procedural complications, 30-day readmission and accident and emergency (A&E) attendance, length of stay) were assessed using two independent data sources, the British Thoracic Society UK Difficult Asthma Registry (DAR) and Hospital Episodes Statistics (HES) database. A matched cohort (with records in both) was used to estimate safety outcome event rates and compare them with clinical trials. Between June 2011 and January 2015, 215 procedure records (83 patients; 68 treated in England) were available from DAR and 203 (85 patients) from HES. 152 procedures matched (59 patients; 6 centres), and of these, 11.2% reported a procedural complication, 11.8% resulted in emergency respiratory readmission, 0.7% in respiratory A&E attendance within 30 days (20.4% had at least one event) and 46.1% involved a post-procedure stay. Compared with published clinical trials which found lower hospitalisation rates, BT patients in routine clinical practice were, on average, older, had worse baseline lung function and asthma quality of life. A higher proportion of patients experienced adverse events compared with clinical trials. The greater severity of disease amongst patients treated in clinical practice may explain the observed rate of post-procedural stay and readmission. Study of long-term safety and efficacy requires continuing data collection.

Microbial Efficacy of Waterless Hand Hygiene in Dar es Salaam, Tanzania

NASA Astrophysics Data System (ADS)

Pickering, A.; Boehm, A.; Davis, J.

2008-12-01

Millions of people die from diarrheal and respiratory diseases every year due to lack of proper sanitation, hygiene, and access to clean water. The act of handwashing with soap has been found to effectively reduce both diarrheal and respiratory illness, however, handwashing at critical times (i.e. after using the toilet, before preparing food) remains infrequent around the world. This research investigates the potential for alcohol- based hand sanitizer (ABHS) to be an effective and appropriate hand hygiene option in developing countries. A study was conducted to assess the microbiological effectiveness of ABHS, as compared to handwashing with soap and water, in field conditions in Dar es Salaam, Tanzania. A total of 205 participants, including mothers, nurses, students, and teachers, were introduced to ABHS, given a standardized amount (2ml) of product, and instructed on how to use the product correctly. Hand samples were obtained using the hand rinse method before and after the use of ABHS from 152 participants. The other 53 participants were hand sampled before and after handwashing with a non-antimicrobial liquid soap and clean water (prior to using ABHS). Visual inspections of the hands were performed before hand sampling to record the level of dirt on the hands. All hand samples were processed and analyzed by membrane filtration for concentrations of two microbial indicators, enterococci and E. coli. User perceptions of the product and willingness to pay are also documented. The results of this study provide valuable insight on the prospective of promoting ABHS in developing countries and water scarce areas.

Coastal monitoring solutions of the geomorphological response of beach-dune systems using multi-temporal LiDAR datasets (Vendée coast, France)

NASA Astrophysics Data System (ADS)

Le Mauff, Baptiste; Juigner, Martin; Ba, Antoine; Robin, Marc; Launeau, Patrick; Fattal, Paul

2018-03-01

Three beach and dune systems located in the northeastern part of the Bay of Biscay in France were monitored over 5 years with a time series of three airborne LiDAR datasets. The three study sites illustrate a variety of morphological beach types found in this region. Reproducible monitoring solutions adapted to basic and complex beach and dune morphologies using LiDAR time series were investigated over two periods bounded by the three surveys. The first period (between May 2008 and August 2010) is characterized by a higher prevalence of storm events, and thus has a greater potential for eroding the coast, than the second period (between August 2010 and September 2013). During the first period, the central and northeastern part of the Bay of Biscay was notably impacted by Storm Xynthia, with water levels and wave heights exceeding the 10-year return period and 1-year return period, respectively. Despite differences in dune morphology between the sites, the dune crest (Dhigh) and the dune base (Dlow) are efficiently extracted from each DEM. Based on the extracted dune base, an original shoreline mobility indicator is built displaying a combination of the horizontal and vertical migrations of this geomorphic indicator between two LiDAR datasets. A 'Geomorphic Change Detection' is also completed by computing DEMs of Difference (DoD) resulting in segregated maps of erosion and deposition and sediment budgets. Accounting for the accuracy of LiDAR datasets, a probabilistic approach at a 95% confidence interval is used as a threshold for the Geomorphic Change Detection showing more reliable results. However, caution should be taken when interpreting thresholded maps of changes and sediment budgets because some beach processes may be masked, especially on wide tidal beaches, by only keeping the most significant changes. The results of the shoreline mobility and Geomorphic Change Detection show a high variability in the beach responses between and within the three study sites, explained mainly by beach orientation and local factors. Despite variable site-specific mechanisms, the recovery processes redistribute the available sand more on the upper parts of the beach, producing significant deposition generally in the form of embryo dunes. The monitoring of the beach and dune systems with airborne LiDAR datasets reveals that the three study sites show diverse behaviours during the first period likely associated with storms, while the analysis show more homogenous beach responses during the second period likely associated with a recovery phase.

Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

USGS Publications Warehouse

Cook, B.D.; Bolstad, P.V.; Naesset, E.; Anderson, R. Scott; Garrigues, S.; Morisette, J.T.; Nickeson, J.; Davis, K.J.

2009-01-01

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30??m to 1??km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600??ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400??m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Automatic landslide detection from LiDAR DTM derivatives by geographic-object-based image analysis based on open-source software

NASA Astrophysics Data System (ADS)

Knevels, Raphael; Leopold, Philip; Petschko, Helene

2017-04-01

With high-resolution airborne Light Detection and Ranging (LiDAR) data more commonly available, many studies have been performed to facilitate the detailed information on the earth surface and to analyse its limitation. Specifically in the field of natural hazards, digital terrain models (DTM) have been used to map hazardous processes such as landslides mainly by visual interpretation of LiDAR DTM derivatives. However, new approaches are striving towards automatic detection of landslides to speed up the process of generating landslide inventories. These studies usually use a combination of optical imagery and terrain data, and are designed in commercial software packages such as ESRI ArcGIS, Definiens eCognition, or MathWorks MATLAB. The objective of this study was to investigate the potential of open-source software for automatic landslide detection based only on high-resolution LiDAR DTM derivatives in a study area within the federal state of Burgenland, Austria. The study area is very prone to landslides which have been mapped with different methodologies in recent years. The free development environment R was used to integrate open-source geographic information system (GIS) software, such as SAGA (System for Automated Geoscientific Analyses), GRASS (Geographic Resources Analysis Support System), or TauDEM (Terrain Analysis Using Digital Elevation Models). The implemented geographic-object-based image analysis (GEOBIA) consisted of (1) derivation of land surface parameters, such as slope, surface roughness, curvature, or flow direction, (2) finding optimal scale parameter by the use of an objective function, (3) multi-scale segmentation, (4) classification of landslide parts (main scarp, body, flanks) by k-mean thresholding, (5) assessment of the classification performance using a pre-existing landslide inventory, and (6) post-processing analysis for the further use in landslide inventories. The results of the developed open-source approach demonstrated good success rates to objectively detect landslides in high-resolution topography data by GEOBIA.

Multi-temporal LiDAR and Landsat quantification of fire-induced changes to forest structure

USGS Publications Warehouse

McCarley, T. Ryan; Kolden, Crystal A.; Vaillant, Nicole M.; Hudak, Andrew T.; Smith, Alistair M.S.; Wing, Brian M.; Kellogg, Bryce; Kreitler, Jason R.

2017-01-01

Measuring post-fire effects at landscape scales is critical to an ecological understanding of wildfire effects. Predominantly this is accomplished with either multi-spectral remote sensing data or through ground-based field sampling plots. While these methods are important, field data is usually limited to opportunistic post-fire observations, and spectral data often lacks validation with specific variables of change. Additional uncertainty remains regarding how best to account for environmental variables influencing fire effects (e.g., weather) for which observational data cannot easily be acquired, and whether pre-fire agents of change such as bark beetle and timber harvest impact model accuracy. This study quantifies wildfire effects by correlating changes in forest structure derived from multi-temporal Light Detection and Ranging (LiDAR) acquisitions to multi-temporal spectral changes captured by the Landsat Thematic Mapper and Operational Land Imager for the 2012 Pole Creek Fire in central Oregon. Spatial regression modeling was assessed as a methodology to account for spatial autocorrelation, and model consistency was quantified across areas impacted by pre-fire mountain pine beetle and timber harvest. The strongest relationship (pseudo-r2 = 0.86, p < 0.0001) was observed between the ratio of shortwave infrared and near infrared reflectance (d74) and LiDAR-derived estimate of canopy cover change. Relationships between percentage of LiDAR returns in forest strata and spectral indices generally increased in strength with strata height. Structural measurements made closer to the ground were not well correlated. The spatial regression approach improved all relationships, demonstrating its utility, but model performance declined across pre-fire agents of change, suggesting that such studies should stratify by pre-fire forest condition. This study establishes that spectral indices such as d74 and dNBR are most sensitive to wildfire-caused structural changes such as reduction in canopy cover and perform best when that structure has not been reduced pre-fire.

Monitoring Cirrus Clouds Using Lamp Observations in Association with Balloon-Borne Radiosonde Over Nainital: Few Case Studies

NASA Astrophysics Data System (ADS)

Solanki, R.; Singh, N.

2012-12-01

Upper tropospheric clouds such as cirrus have been identified as one of the important regulator of the radiation balance of the earth atmospheric-system. Though the satellite observation provide valuable information on cirrus clouds, they have limitations on spectral, temporal and spatial coverage, hence the need for local remote sensing, such as LiDAR a leading technique for studying the characteristics and properties of cirrus clouds. The upgraded version of a micro pulse LiDAR popularly known as LiDAR for Atmospheric Measurements and Probing (LAMP) developed by National Atmospheric Research Laboratory (NARL) is operational since October 2011, at ARIES Nainital (29.4oN, 79.5oE, ~2 km above the mean sea level) a high altitude location in the central Himalayas. Regular observations are being carried out in order to study the vertical distribution of aerosols, clouds and boundary layer structure etc. Altitude profiles of range corrected photon count and derived aerosol back scatter coefficients have depicted the occurrence of high altitude cirrus clouds/ ice clouds in an altitude range of 7 to 11 Km. Among the total observations in 27% of the cases the occurrence of cirrus clouds were detected. The corresponding cloud parameters such as temperature (-59 0C), horizontal wind speed (26 m/s), vertical wind speed (24 m/s), Relative Humidity (61%), at a height (~9 Km) were measured with Radiosonde observations. The prevailing region for cirrus cloud is found to be highly turbulent, indicating the region of divergence followed by a convergence, showing the favorable conditions for cirrus cloud formation. Optical and geometrical characteristics of Cirrus clouds have been analyzed using LiDAR and radiosonde measurements. The temperature and thickness dependence of optical properties have also been studied. The results will be further substantiated with CALIPSO satellite and details will be discussed during the presentation.

High-Resolution Characterization of Intertidal Geomorphology by TLS

NASA Astrophysics Data System (ADS)

Guarnieri, A.; Vettore, A.; Marani, M.

2007-12-01

Observational fluvial geomorphology has greatly benefited in the last decades from the wide availability of digital terrain data obtained by orthophotos and by means of accurate airborne laser scanner data (LiDAR). On the contrary, the spatially-distributed study of the geomorphology of intertidal areas, such as tidal flats and marshes, remains problematic owing to the small relief characterizing such environments, often of the order of a few tens of centimetres, i.e. comparable to the accuracy of state-of-the-art LiDAR data. Here we present the results of Terrestrial Laser Scanner (TLS) acquisitions performed within a tidal marsh in the Venice lagoon. The survey was performed using a Leica HDS 3000 TLS, characterized by a large Field of View (360 deg H x 270 deg V), a low beam divergence (< 6 mm at 50 m) and a nominal accuracy of 6 mm at 50 m. The acquisition was performed at low tide to avoid interferences due to water on the marsh surface and, to minimize shadowing effects due to the tilting of the laser beam (especially in the channel network), the scanner was mounted on a custom-built tripod 3 m above the marsh surface. The area of the marsh, about 100m x 150m, was fully surveyed by just 2 scans. A total amount of about 3 million points was acquired, with an average measurement density of 200 points/m2. In order to reconstruct the geometry of the marsh, the two scans were co-registered using 8 reflective targets as matching points. Such targets were placed within the area of interest and surveyed with high accuracy (2 mm), while their position in the Italian national grid was determined with a double-frequency GPS receiver, in order to georeference the point clouds within an absolute framework. Post-processing of the very high resolution data obtained shows that the laser returns coming from the low vegetation present (about 0.5-1.0 m high) can be satisfactorily separated from those coming from the marsh surface, allowing the construction of a DSM and a DTM. This is important e.g. in eco-geomorphic studies of intertidal environments, where conventional LiDAR technologies cannot easily separate first and last laser returns (because of the low vegetation height) and thus provide models of the surface as well as of the terrain. Furthermore, the DTM is shown to provide unprecedented characterizations of marsh morphology, e.g. regarding the cross-sectional properties of small-scale tidal creeks (widths of the order of 10 cm), previously observable only through conventional topographic surveys, thus not allowing a fully spatially-distributed description of their morphology.

NGAM webinar materials for talk by C. Serest on May 2012 Market Technology Symposium, fenceline monitoring session

EPA Science Inventory

This talk supports the NGAM workshop and webinar seires and prepares for NGAM 2 The Next Generation Air Monitoring (NGAM) webinar and workshop series captures the revolution in air pollution measurement science enabled by rapid advances in sensors, communication...

New Exploration of North Kerguelen Plateau Margins : Constraints for the Australia-Antarctica Separation

NASA Astrophysics Data System (ADS)

Courrèges, E.; Vially, R.; Roest, W. R.; Patriat, M.; Patriat, P.; Loubrieu, B.; Lecomte, J.-C.; Schaming, M.; Schmitz, J.; Maia, M.

2009-04-01

France ratified the United Nations Convention on the Law of the Sea in 1996, and has since undertaken an ambitious program of bathymetric and seismic data acquisition (EXTRAPLAC Program) to support claims for the extension of the legal continental shelf, in accordance with Article 76 of this convention. For this purpose, three oceanographic surveys took place on board of the R/V Marion Dufresne II, operated by the French Polar Institute, on the Kerguelen Plateau, in the Southern Indian Ocean: MD137-Kergueplac1 (February 2004), MD150-Kergueplac2 (October 2005) and MD165-Kergueplac3 (January 2008). Thus, more than 20 000 km of multibeam bathymetric, magnetic and gravimetric profiles, and almost 6 000 km of seismic profiles where acquired during a total of 62 days of survey in the study area. Ifremer's "rapid seismic" system was used, comprised of 4 guns and a 24 trace digital streamer, operated at speeds up to 10 knots. In addition to its use for the Extraplac Program, the data set issued from these surveys provides the opportunity to improve our knowledge of the structure of the Kerguelen Plateau and more particularly of its complex margins. In this poster, we show different kinds of data. The high resolution bathymetry (200 m grid) data set allows us to specify the irregular morphology of the sea floor in the north Kerguelen Plateau region, characterised by ridges and volcano chains that intersect the oceanic basin on its NE edge. The seismic profiles show that the acoustic basement of the plateau is not much tectonised, and displays a very smooth texture, clearly contrasting it from typical oceanic basement. Both along the edge of the plateau and in the abyssal plain, sediments have variable thicknesses. The sediments on the margin of the plateau are up to 1200 meters thick and display irregular crisscross patterns, suggesting the presence of important bottom currents. An important concentration of new magnetic data, in a key area (Northern Kerguelen Platerau) and at a key period (Oligocene), helps us understand the setting up of the oceanic plateau and the kinematics reconstructions between Antarctica and Australia plates. We focused on the northeastern margin of the Kerguelen Plateau, from 77E30 up to the Amsterdam Saint-Paul fracture zone, where the South East Indian Ridge (SEIR) shows a large offset toward the Kerguelen Plateau. On a larger scale, the opening between Kerguelen Plateau and Broken Ridge has kept very morphologically homologous margins on each side of the SEIR: in the Southern Kerguelen Plateau, the magnetic anomalies are regular, parallel to the SEIR and also to the morphological boundary of the plateau. In contrast, the northeastern margin of the Northern Kerguelen Plateau is not much explored and its interpretation less obvious, because volcanic masses overlie discordantly the oceanic crust. We compiled the magnetic anomalies pickings, integrating data from recent Kergueplac surveys and previous studies, to identify with more confidence the oldest anomalies at the plateau margin. We used it for reconstructions at different stages (from a8o to initial opening), realised with rotation poles of Cande & Stocks (2004). These reconstructions confirm that kinematic in the whole SE Indian Ocean, and in particular in the Northern part of the Kerguelen Plateau, remains unresolved. In particular, we discuss both the fit between Kerguelen and Broken Ridge and the implication for the opening between Australia and Antarctica as well as the possible junctions along the Amsterdam fracture zone with the Crozet basin where the spreading rate was much faster before A18.

Effect of vitamin supplementation to HIV-infected pregnant women on the micronutrient status of their infants.

PubMed

Baylin, A; Villamor, E; Rifai, N; Msamanga, G; Fawzi, W W

2005-08-01

We examined whether supplementation with vitamin A and/or vitamins B, C, and E to HIV-infected women during pregnancy and lactation is related to increased concentrations of vitamins A, B12, and E in their infants during the first 6 months of life. We carried out a randomized clinical trial among 716 mother-infant pairs in Dar-es-Salaam, Tanzania. Women were randomly allocated to receive a daily oral dose of one of four regimens: vitamin A, multivitamins (B, C, and E), multivitamins including A, or placebo. Supplementation started at first prenatal visit and continued after delivery throughout the breastfeeding period. The serum concentration of vitamins A, E and B12 was measured in infants at 6 weeks and 6 months postpartum. Maternal vitamin A supplementation increased serum retinol in the infants at 6 weeks (mean difference=0.09 micromol/l, P<0.0001) and 6 months (mean difference=0.06 micromol/l, P=0.0002), and decreased the prevalence of vitamin A deficiency, but had no impact on serum vitamins E or B12. Multivitamins increased serum vitamin B12 at 6 weeks and 6 months (mean differences=176 pmol/l, P<0.0001 and 127 pmol/l, P<0.0001, respectively) and vitamin E (mean differences=1.8 micromol/l, P=0.0008 and 1.1 micromol/l, P=0.004, respectively) and decreased the prevalence of vitamin B12 deficiency. Vitamin supplementation to HIV-1-infected women is effective in improving the vitamin status of infants during the first 6 months of age.

Guild-specific responses of avian species richness to LiDAR-derived habitat heterogeneity

USGS Publications Warehouse

Weisberg, Peter J.; Dilts, Thomas E.; Becker, Miles E.; Young, Jock S.; Wong-Kone, Diane C.; Newton, Wesley E.; Ammon, Elisabeth M.

2014-01-01

Ecological niche theory implies that more heterogeneous habitats have the potential to support greater biodiversity. Positive heterogeneity-diversity relationships have been found for most studies investigating animal taxa, although negative relationships also occur and the scale dependence of heterogeneity-diversity relationships is little known. We investigated multi-scale, heterogeneity-diversity relationships for bird communities in a semi-arid riparian landscape, using airborne LiDAR data to derive key measures of structural habitat complexity. Habitat heterogeneity-diversity relationships were generally positive, although the overall strength of relationships varied across avian life history guilds (R2 range: 0.03–0.41). Best predicted were the species richness indices of cavity nesters, habitat generalists, woodland specialists, and foliage foragers. Heterogeneity-diversity relationships were also strongly scale-dependent, with strongest associations at the 200-m scale (4 ha) and weakest associations at the 50-m scale (0.25 ha). Our results underscore the value of LiDAR data for fine-grained quantification of habitat structure, as well as the need for biodiversity studies to incorporate variation among life-history guilds and to simultaneously consider multiple guild functional types (e.g. nesting, foraging, habitat). Results suggest that certain life-history guilds (foliage foragers, cavity nesters, woodland specialists) are more susceptible than others (ground foragers, ground nesters, low nesters) to experiencing declines in local species richness if functional elements of habitat heterogeneity are lost. Positive heterogeneity-diversity relationships imply that riparian conservation efforts need to not only provide high-quality riparian habitat locally, but also to provide habitat heterogeneity across multiple scales.

Landscape-scale quantification of fire-induced change in canopy cover following mountain pine beetle outbreak and timber harvest

USGS Publications Warehouse

McCarley, T. Ryan; Kolden, Crystal A.; Vaillant, Nicole M.; Hudak, Andrew T.; Smith, Alistair M.S.; Kreitler, Jason R.

2017-01-01

Across the western United States, the three primary drivers of tree mortality and carbon balance are bark beetles, timber harvest, and wildfire. While these agents of forest change frequently overlap, uncertainty remains regarding their interactions and influence on specific subsequent fire effects such as change in canopy cover. Acquisition of pre- and post-fire Light Detection and Ranging (LiDAR) data on the 2012 Pole Creek Fire in central Oregon provided an opportunity to isolate and quantify fire effects coincident with specific agents of change. This study characterizes the influence of pre-fire mountain pine beetle (MPB; Dendroctonus ponderosae) and timber harvest disturbances on LiDAR-estimated change in canopy cover. Observed canopy loss from fire was greater (higher severity) in areas experiencing pre-fire MPB (Δ 18.8%CC) than fire-only (Δ 11.1%CC). Additionally, increasing MPB intensity was directly related to greater canopy loss. Canopy loss was lower for all areas of pre-fire timber harvest (Δ 3.9%CC) than for fire-only, but among harvested areas, the greatest change was observed in the oldest treatments and the most intensive treatments [i.e., stand clearcut (Δ 5.0%CC) and combination of shelterwood establishment cuts and shelterwood removal cuts (Δ 7.7%CC)]. These results highlight the importance of accounting for and understanding the impact of pre-fire agents of change such as MPB and timber harvest on subsequent fire effects in land management planning. This work also demonstrates the utility of multi-temporal LiDAR as a tool for quantifying these landscape-scale interactions.

Exploring the association between women's access to economic resources and intimate partner violence in Dar es Salaam and Mbeya, Tanzania.

PubMed

Vyas, Seema; Jansen, Henrica Afm; Heise, Lori; Mbwambo, Jessie

2015-12-01

The relationship between women's access to economic resources, e.g. employment or access to micro-credit, and experience of intimate partner violence is complex. Empirical evidence documents that in some settings women's employment is associated with higher risk of partner violence but in other settings with lower risk. Evidence also shows that these conflicting associations exist not only between countries but also within different country settings. Using two population-based data sets gathered in 2002 in contrasting Tanzania settings-Dar es Salaam and Mbeya-, we used multivariate logistic regression to examine the relationship between women's access to economic resources and partner violence. Two indicators of economic resources were examined: whether women earned money and whether women owned a business either with someone or exclusively. In Dar es Salaam we found evidence of a higher risk association among women who earned money and who owned a business exclusively by themselves and a lower risk association among women who owned a business with someone. We found no relationship between either indicator of economic resources and partner violence in Mbeya. Other factors were similarly associated with partner violence in both settings and the strongest associations found were related to the respondents' partners: refusal to give money; alcohol use and relationships with other women. The findings support the assertion that women's access to economic resources operate differently in different country settings, thus highlighting the need for targeted prevention efforts that are relevant for the context. Copyright © 2015 Elsevier Ltd. All rights reserved.

Guild-specific responses of avian species richness to LiDAR-derived habitat heterogeneity

NASA Astrophysics Data System (ADS)

Weisberg, Peter J.; Dilts, Thomas E.; Becker, Miles E.; Young, Jock S.; Wong-Kone, Diane C.; Newton, Wesley E.; Ammon, Elisabeth M.

2014-08-01

Ecological niche theory implies that more heterogeneous habitats have the potential to support greater biodiversity. Positive heterogeneity-diversity relationships have been found for most studies investigating animal taxa, although negative relationships also occur and the scale dependence of heterogeneity-diversity relationships is little known. We investigated multi-scale, heterogeneity-diversity relationships for bird communities in a semi-arid riparian landscape, using airborne LiDAR data to derive key measures of structural habitat complexity. Habitat heterogeneity-diversity relationships were generally positive, although the overall strength of relationships varied across avian life history guilds (R2 range: 0.03-0.41). Best predicted were the species richness indices of cavity nesters, habitat generalists, woodland specialists, and foliage foragers. Heterogeneity-diversity relationships were also strongly scale-dependent, with strongest associations at the 200-m scale (4 ha) and weakest associations at the 50-m scale (0.25 ha). Our results underscore the value of LiDAR data for fine-grained quantification of habitat structure, as well as the need for biodiversity studies to incorporate variation among life-history guilds and to simultaneously consider multiple guild functional types (e.g. nesting, foraging, habitat). Results suggest that certain life-history guilds (foliage foragers, cavity nesters, woodland specialists) are more susceptible than others (ground foragers, ground nesters, low nesters) to experiencing declines in local species richness if functional elements of habitat heterogeneity are lost. Positive heterogeneity-diversity relationships imply that riparian conservation efforts need to not only provide high-quality riparian habitat locally, but also to provide habitat heterogeneity across multiple scales.

Hydrodynamic and sedimentological controls governing formation of fluvial levees

NASA Astrophysics Data System (ADS)

Johnston, G. H.; Edmonds, D. A.; David, S. R.; Czuba, J. A.

2017-12-01

Fluvial levees are familiar features found on the margins of river channels, yet we know little about what controls their presence, height, and shape. These attributes of levees are important because they control sediment transfer from channel to floodplain and flooding patterns along a river system. Despite the familiarity and importance of levees, there is a surprising lack of basic geomorphic data on fluvial levees. Because of this we seek to understand: 1) where along rivers do levees tend to occur?; 2) what geomorphic and hydrodynamic variables control cross-sectional shape of levees? We address these questions by extracting levee shape from LiDAR data and by collecting hydrodynamic and sedimentological data from reaches of the Tippecanoe River, the White River, and the Muscatatuck River, Indiana, USA. Fluvial levees are extracted from a 1.5-m resolution LiDAR bare surface model and compared to hydrological, sedimentological, and geomorphological data from USGS stream gages. We digitized banklines and extracted levee cross-sections to calculate levee slope, taper, height, e-folding length, and e-folding width. To answer the research questions, we performed a multivariable regression between the independent variables—channel geometry, sediment grain size and concentration, flooding conditions, and slope—and the dependent levee variables. We find considerable variation in levee presence and shape in our field data. On the Muscatatuck River levees occur on 30% of the banks compared to 10% on the White River. Moreover, levees on the Muscatatuck are on average 3 times wider than the White River. This is consistent with the observation that the Muscatatuck is finer-grained compared to the White River and points to sedimentology being an important control on levee geomorphology. Future work includes building a morphodynamic model to understand how different hydrodynamic and geomorphic conditions control levee geometry.

Some Preliminary Results on an SEIARD Epidemic Model with Vaccination and Antiviral Treatment Controls and Dead-Infective Culling Action

NASA Astrophysics Data System (ADS)

De la Sen, M.; Nistal, R.; Alonso-Quesada, S.; Garrido, A. J.

2016-08-01

This paper studies the non-negativity and stability properties of the solutions of a newly proposed SEIADR model which incorporates asymptomatic and dead-infective subpopulations to those defining the standard SEIR model and, in parallel, it incorporates feedback vaccination and antiviral treatment controls.

Geomorphology of intraplate postglacial faults in Sweden

NASA Astrophysics Data System (ADS)

Ask, M. V. S.; Abdujabbar, M.; Lund, B.; Smith, C.; Mikko, H.; Munier, R.

2015-12-01

Melting of the Weichselian ice sheet at ≈10 000 BP is inferred to have induced large to great intraplate earthquakes in northern Fennoscandia. Over a dozen large so-called postglacial faults (PGF) have been found, mainly using aerial photogrammetry, trenching, and recognition of numerous paleolandslides in the vicinity of the faults (e.g. Lagerbäck & Sundh 2008). Recent LiDAR-based mapping led to the extension of known PGFs, the discovery of new segments of existing PGFs, and a number of new suspected PGFs (Smith et al. 2014; Mikko et al. 2015). The PGFs in Fennoscandia occur within 14-25°E and 61-69°N; the majority are within Swedish territory. PGFs generally are prominent features, up to 155 km in length and 30 m maximum surface offset. The most intense microseismic activity in Sweden occurs near PGFs. The seismogenic zone of the longest known PGF (Pärvie fault zone, PFZ) extends to ≈40 km depth. From fault geometry and earthquake scaling relations, the paleomagnitude of PFZ is estimated to 8.0±0.3 (Lindblom et al. 2015). The new high-resolution LiDAR-derived elevation model of Sweden offers an unprecedented opportunity to constrain the surface geometry of the PGFs. The objective is to reach more detailed knowledge of the surface offset across their scarps. This distribution provides a one-dimensional view of the slip distribution during the inferred paleorupture. The second objective is to analyze the pattern of vertical displacement of the hanging wall, to obtain a two-dimensional view of the displaced area that is linked to the fault geometry at depth. The anticipated results will further constrain the paleomagnitude of PGFs and will be incorporated into future modeling efforts to investigate the nature of PGFs. ReferencesLagerbäck & Sundh 2008. Early Holocene faulting and paleoseismicity in northern Sweden. http://resource.sgu.se/produkter/c/c836-rapport.pdf Smith et al. 2014. Surficial geology indicates early Holocene faulting and seismicity, central Sweden. doi: 10.1007/s00531-014-1025-6 Mikko et al. 2015. LiDAR-derived inventory of post-glacial fault scarps in Sweden. doi:10.1080/11035897.2015.1036360 Lindblom et al. 2015. Microearthquakes illuminate the deep structure of the endglacial Pärvie fault, northern Sweden. doi: 10.1093/gji/ggv112

Evaluation of fire recurrence effect on genetic diversity in maritime pine (Pinus pinaster Ait.) stands using Inter-Simple Sequence Repeat profiles.

PubMed

Lucas-Borja, M E; Ahrazem, O; Candel-Pérez, D; Moya, D; Fonseca, T; Hernández Tecles, E; De Las Heras, J; Gómez-Gómez, L

2016-12-01

The management of maritime pine in fire-prone habitats is a challenging task and fine-scale population genetic analyses are necessary to check if different fire recurrences affect genetic variability. The objective of this study was to assess the effect of fire recurrence on maritime pine genetic diversity using inter-simple sequence repeat markers (ISSR). Three maritime pine (Pinus pinaster Ait.) populations from Northern Portugal were chosen to characterize the genetic variability among populations. In relation to fire recurrence, Seirós population was affected by fire both in 1990 and 2005 whereas Vila Seca-2 population was affected by fire just in 2005. The Vila Seca-1 population has been never affected by fire. Our results showed the highest Nei's genetic diversity (He=0.320), Shannon information index (I=0.474) and polymorphic loci (PPL=87.79%) among samples from twice burned populations (Seirós site). Thus, fire regime plays an important role affecting genetic diversity in the short-term, although not generating maritime pine genetic erosion. Copyright © 2016 Elsevier B.V. All rights reserved.

Seeing the Forest through the Trees: Citizen Scientists Provide Critical Data to Refine Aboveground Carbon Estimates in Restored Riparian Forests

NASA Astrophysics Data System (ADS)

Viers, J. H.

2013-12-01

Integrating citizen scientists into ecological informatics research can be difficult due to limited opportunities for meaningful engagement given vast data streams. This is particularly true for analysis of remotely sensed data, which are increasingly being used to quantify ecosystem services over space and time, and to understand how land uses deliver differing values to humans and thus inform choices about future human actions. Carbon storage and sequestration are such ecosystem services, and recent environmental policy advances in California (i.e., AB 32) have resulted in a nascent carbon market that is helping fuel the restoration of riparian forests in agricultural landscapes. Methods to inventory and monitor aboveground carbon for market accounting are increasingly relying on hyperspatial remotely sensed data, particularly the use of light detection and ranging (LiDAR) technologies, to estimate biomass. Because airborne discrete return LiDAR can inexpensively capture vegetation structural differences at high spatial resolution (< 1 m) over large areas (> 1000 ha), its use is rapidly increasing, resulting in vast stores of point cloud and derived surface raster data. While established algorithms can quantify forest canopy structure efficiently, the highly complex nature of native riparian forests can result in highly uncertain estimates of biomass due to differences in composition (e.g., species richness, age class) and structure (e.g., stem density). This study presents the comparative results of standing carbon estimates refined with field data collected by citizen scientists at three different sites, each capturing a range of agricultural, remnant forest, and restored forest cover types. These citizen science data resolve uncertainty in composition and structure, and improve allometric scaling models of biomass and thus estimates of aboveground carbon. Results indicate that agricultural land and horticulturally restored riparian forests store similar amounts of aboveground carbon (< 50 Mg/ha), but significantly less than naturally recruiting riparian forests (50 - 200 Mg/ha). Monitoring and assessment of dynamic ecosystem processes and functions will increasingly use data intensive methodologies; however, this research shows the utility of engaging citizen scientists in developing more robust data streams that not only reduces uncertainty, but also provide invaluable opportunities for improved education and outreach.

An Agent-Based Model of School Closing in Under-Vacccinated Communities During Measles Outbreaks.

PubMed

Getz, Wayne M; Carlson, Colin; Dougherty, Eric; Porco Francis, Travis C; Salter, Richard

2016-04-01

The winter 2014-15 measles outbreak in the US represents a significant crisis in the emergence of a functionally extirpated pathogen. Conclusively linking this outbreak to decreases in the measles/mumps/rubella (MMR) vaccination rate (driven by anti-vaccine sentiment) is critical to motivating MMR vaccination. We used the NOVA modeling platform to build a stochastic, spatially-structured, individual-based SEIR model of outbreaks, under the assumption that R 0 ≈ 7 for measles. We show this implies that herd immunity requires vaccination coverage of greater than approximately 85%. We used a network structured version of our NOVA model that involved two communities, one at the relatively low coverage of 85% coverage and one at the higher coverage of 95%, both of which had 400-student schools embedded, as well as students occasionally visiting superspreading sites (e.g. high-density theme parks, cinemas, etc.). These two vaccination coverage levels are within the range of values occurring across California counties. Transmission rates at schools and superspreading sites were arbitrarily set to respectively 5 and 15 times background community rates. Simulations of our model demonstrate that a 'send unvaccinated students home' policy in low coverage counties is extremely effective at shutting down outbreaks of measles.

An Agent-Based Model of School Closing in Under-Vacccinated Communities During Measles Outbreaks

PubMed Central

Getz, Wayne M.; Carlson, Colin; Dougherty, Eric; Porco, Travis C.; Salter, Richard

2016-01-01

The winter 2014–15 measles outbreak in the US represents a significant crisis in the emergence of a functionally extirpated pathogen. Conclusively linking this outbreak to decreases in the measles/mumps/rubella (MMR) vaccination rate (driven by anti-vaccine sentiment) is critical to motivating MMR vaccination. We used the NOVA modeling platform to build a stochastic, spatially-structured, individual-based SEIR model of outbreaks, under the assumption that R0 ≈ 7 for measles. We show this implies that herd immunity requires vaccination coverage of greater than approximately 85%. We used a network structured version of our NOVA model that involved two communities, one at the relatively low coverage of 85% coverage and one at the higher coverage of 95%, both of which had 400-student schools embedded, as well as students occasionally visiting superspreading sites (e.g. high-density theme parks, cinemas, etc.). These two vaccination coverage levels are within the range of values occurring across California counties. Transmission rates at schools and superspreading sites were arbitrarily set to respectively 5 and 15 times background community rates. Simulations of our model demonstrate that a ‘send unvaccinated students home’ policy in low coverage counties is extremely effective at shutting down outbreaks of measles. PMID:27668297

Multi-static Serial LiDAR for Surveillance and Identification of Marine Life at MHK Installations

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

Alsenas, Gabriel; Dalgleish, Fraser; Ouyang, Bing

Final Report for project DE-EE0006787: Multi-static Serial LiDAR for Surveillance and Identification of Marine Life at MHK Installations. This project developed and tested an optical monitoring system prototype that will be suitable for marine and hydrokinetic (MHK) full project lifecycle observation (baseline, commissioning, and decommissioning), with automated real-time classification of marine animals. This system can be deployed to collect pre-installation baseline species observations at a proposed deployment site with minimal post-processing overhead. To satisfy deployed MHK project species of concern (e.g. Endangered Species Act-listed) monitoring requirements, the system provides automated tracking and notification of the presence of managed animals withinmore » established perimeters of MHK equipment and provides high resolution imagery of their behavior through a wide range of conditions. During a project’s decommissioning stage, the system can remain installed to provide resource managers with post-installation data. Our technology, known as an Unobtrusive Multi-static Serial LiDAR Imager (UMSLI), is a technology transfer of underwater distributed LiDAR imaging technology that preserves the advantages of traditional optical and acoustic solutions while overcoming associated disadvantages for MHK environmental monitoring applications. This new approach is a purposefully-designed, reconfigurable adaptation of an existing technology that can be easily mounted on or around different classes of MHK equipment. The system uses low average power red (638nm) laser illumination to be invisible and eye-safe to marine animals and is compact and cost effective. The equipment is designed for long term, maintenance-free operations, to inherently generate a sparse primary dataset that only includes detected anomalies (animal presence information), and to allow robust real-time automated animal classification/identification with a low data bandwidth requirement. Advantages of the technology over others currently being used or being considered for MHK monitoring include: Unlike a conventional camera, the depth of field is near-infinite and limited by attenuation (approximately 5-8 m) rather than focal properties of a lens; Operation in an adaptive mode which can project a sparse grid of pulses with higher peak power for longer range detection (>10 meters) and track animals within a zone of interest with high resolution imagery for identification of marine life at closer range (<5m); System detection limit and Signal-to-Noise-Ratio is superior to a camera, due to rejection of both backscattering component and ambient solar background; Multiple wide-angle pulsed laser illuminators and bucket detectors can be flexibly configured to cover a 4pi steradian (i.e. omnidirectional) scene volume, while also retrieving 3D features of animal targets from timing information; Process and classification framework centered around a novel active learning and incremental classification classifier that enables accurate identification of a variety of marine animals automatically; A two-tiered monitoring architecture and invisible watermarking-based data archiving and retrieving approach ensures significant data reduction while preserving high fidelity monitoring. A methodology to train and optimize the classifier for target species of concern to optimize site monitoring effectiveness. This technological innovation addresses a high priority regulatory requirement to observe marine life interaction near MHK projects. Our solution improves resource manager confidence that any interactions between marine animals and equipment are observed in a cost-effective and automated manner. Without EERE funding, this novel application of multi-static LiDAR would not have been available to the MHK community for environmental monitoring.« less

A Novel Method of Autonomous Inspection for Transmission Line based on Cable Inspection Robot LiDAR Data

PubMed Central

Qin, Xinyan; Wu, Gongping; Fan, Fei; Ye, Xuhui; Mei, Quanjie

2018-01-01

With the growth of the national economy, there is increasing demand for electricity, which forces transmission line corridors to become structurally complicated and extend to complex environments (e.g., mountains, forests). It is a great challenge to inspect transmission line in these regions. To address these difficulties, a novel method of autonomous inspection for transmission line is proposed based on cable inspection robot (CIR) LiDAR data, which mainly includes two steps: preliminary inspection and autonomous inspection. In preliminary inspection, the position and orientation system (POS) data is used for original point cloud dividing, ground point filtering, and structured partition. A hierarchical classification strategy is established to identify the classes and positions of the abnormal points. In autonomous inspection, CIR can autonomously reach the specified points through inspection planning. These inspection targets are imaged with PTZ (pan, tilt, zoom) cameras by coordinate transformation. The feasibility and effectiveness of the proposed method are verified by test site experiments and actual line experiments, respectively. The proposed method greatly reduces manpower and improves inspection accuracy, providing a theoretical basis for intelligent inspection of transmission lines in the future. PMID:29462865

Neutrino Physics with Accelerator Driven Subcritical Reactors

NASA Astrophysics Data System (ADS)

Ciuffoli, Emilio

2017-09-01

Accelerator Driven Subcritical System (ADS) reactors are being developed around the world, to produce energy and, at the same time, to provide an efficient way to dispose of and to recycle nuclear waste. Used nuclear fuel, by itself, cannot sustain a chain reaction; however in ADS reactors the additional neutrons which are required will be supplied by a high-intensity accelerator. This accelerator will produce, as a by-product, a large quantity of {\\bar{ν }}μ via muon Decay At Rest (µDAR). Using liquid scintillators, it will be possible to to measure the CP-violating phase δCP and to look for experimental signs of the presence of sterile neutrinos in the appearance channel, testing the LSND and MiniBooNE anomalies. Even in the first stage of the project, when the beam energy will be lower, it will be possible to produce {\\bar{ν }}e via Isotope Decay At Rest (IsoDAR), which can be used to provide competitive bounds on sterile neutrinos in the disappearance channel. I will consider several experimental setups in which the antineutrinos are created using accelerators that will be constructed as part of the China-ADS program.

Oceanic magmatic evolution during ocean opening under influence of mantle plume

NASA Astrophysics Data System (ADS)

Sushchevskaya, Nadezhda; Melanholina, Elena; Belyatsky, Boris; Krymsky, Robert; Migdisova, Natalya

2015-04-01

Petrology, geochemistry and geophysics as well as numerical simulation of spreading processes in plume impact environments on examples of Atlantic Ocean Iceland and the Central Atlantic plumes and Kerguelen plume in the Indian Ocean reveal: - under interaction of large plume and continental landmass the plume can contribute to splitting off individual lithosphere blocks, and their subsequent movement into the emergent ocean. At the same time enriched plume components often have geochemical characteristics of the intact continental lithosphere by early plume exposure. This is typical for trap magmatism in Antarctica, and for magmatism of North and Central Atlantic margins; - in the course of the geodynamic reconstruction under the whole region of the South Atlantic was formed (not in one step) metasomatized enriched sub-oceanic mantle with pyroxenite mantle geochemical characteristics and isotopic composition of enriched HIMU and EM-2 sources. That is typical for most of the islands in the West Antarctic. This mantle through spreading axes jumping involved in different proportions in the melting under the influence of higher-temperature rising asthenospheric lherzolite mantle; - CAP activity was brief enough (200 ± 2 Ma), but Karoo-Maud plume worked for a longer time and continued from 180 to 170 Ma ago in the main phase. Plume impact within Antarctica distributed to the South and to the East, leading to the formation of extended igneous provinces along the Transantarctic Mountains and along the east coast (Queen Maud Land province and Schirmacher Oasis). Moreover, this plume activity may be continued later on, after about 40 million years cessation, as Kerguelen plume within the newly-formed Indian Ocean, significantly affects the nature of the rift magmatism; - a large extended uplift in the eastern part of the Indian Ocean - Southeastern Indian Ridge (SEIR) was formed on the ancient spreading Wharton ridge near active Kerguelen plume. The strongest plume influence on the SEIR formation occurred 70-50 mln years ago, when the process of primary magma generation happened at high degrees of melting (up to 30%), which is not typical for spreading ridges of the Atlantic and Pacific Oceans. According to geochemical characteristics of the Kerguelen Plateau and SEIR magma sources close to each other, and have an enriched source of more typical for Kerguelen plume magmas and diluted by depleted substance for SEIR melts. Appearance of magmatism on the Antarctic margin about 56 thousand years ago, in the form of a stratovolcano Gaussberg indicates sublithospheric Kerguelen plume distribution in the south-west direction. The source of primary magmas (lamproite composition) is an ancient Gondwana lithosphere, has undergone repeated changes in the early stages of evolution during which it was significantly enriched in volatile and lithophile elements, and radiogenic Sr and Pb.

Maximum entropy estimation of a Benzene contaminated plume using ecotoxicological assays.

PubMed

Wahyudi, Agung; Bartzke, Mariana; Küster, Eberhard; Bogaert, Patrick

2013-01-01

Ecotoxicological bioassays, e.g. based on Danio rerio teratogenicity (DarT) or the acute luminescence inhibition with Vibrio fischeri, could potentially lead to significant benefits for detecting on site contaminations on qualitative or semi-quantitative bases. The aim was to use the observed effects of two ecotoxicological assays for estimating the extent of a Benzene groundwater contamination plume. We used a Maximum Entropy (MaxEnt) method to rebuild a bivariate probability table that links the observed toxicity from the bioassays with Benzene concentrations. Compared with direct mapping of the contamination plume as obtained from groundwater samples, the MaxEnt concentration map exhibits on average slightly higher concentrations though the global pattern is close to it. This suggest MaxEnt is a valuable method to build a relationship between quantitative data, e.g. contaminant concentrations, and more qualitative or indirect measurements, in a spatial mapping framework, which is especially useful when clear quantitative relation is not at hand. Copyright © 2012 Elsevier Ltd. All rights reserved.

Rb-Sr and Sm-Nd Isotopic Studies of Martian Depleted Shergottes SaU 094/005

NASA Technical Reports Server (NTRS)

Shih, C.-Y.; Nyquist, L. E.; Reese, Y.

2007-01-01

Sayh al Uhaymir (SaU) 094 and SaU 005 are olivine-phyric shergottites from the Oman desert and are considered as pairs. [e.g., 1]. They are very similar to the Libyan desert shergottite Dar al Gani (DaG) 476 in petrology, chemistry and ejection age [2-6]. This group of shergottites, also recognized as depleted shergottites [e.g. 7] has been strongly shocked and contains very low abundances of light rare earth elements (REE). In addition, terrestrial contaminants are commonly present in meteorites found in desert environments. Age-dating these samples is very challenging, but lower calcite contents in the SaU meteorites suggest that they have been subjected to less severe desert weathering than their DaG counterparts [3-4]. In this report, we present Rb-Sr and Sm-Nd isotopic results for SaU 094 and SaU 005, discuss the correlation of their ages with those of other similar shergottites, and discuss their petrogenesis.

Attribution and Characterisation of Sclerophyll Forested Landscapes Over Large Areas

NASA Astrophysics Data System (ADS)

Jones, Simon; Soto-Berelov, Mariela; Suarez, Lola; Wilkes, Phil; Woodgate, Will; Haywood, Andrew

2016-06-01

This paper presents a methodology for the attribution and characterisation of Sclerophyll forested landscapes over large areas. First we define a set of woody vegetation data primitives (e.g. canopy cover, leaf area index (LAI), bole density, canopy height), which are then scaled-up using multiple remote sensing data sources to characterise and extract landscape woody vegetation features. The advantage of this approach is that vegetation landscape features can be described from composites of these data primitives. The proposed data primitives act as building blocks for the re-creation of past woody characterisation schemes as well as allowing for re-compilation to support present and future policy and management and decision making needs. Three main research sites were attributed; representative of different sclerophyll woody vegetated systems (Box Iron-bark forest; Mountain Ash forest; Mixed Species foothills forest). High resolution hyperspectral and full waveform LiDAR data was acquired over the three research sites. At the same time, land management agencies (Victorian Department of Environment, Land Water and Planning) and researchers (RMIT, CRC for Spatial Information and CSIRO) conducted fieldwork to collect structural and functional measurements of vegetation, using traditional forest mensuration transects and plots, terrestrial lidar scanning and high temporal resolution in-situ autonomous laser (VegNet) scanners. Results are presented of: 1) inter-comparisons of LAI estimations made using ground based hemispherical photography, LAI 2200 PCA, CI-110 and terrestrial and airborne laser scanners; 2) canopy height and vertical canopy complexity derived from airborne LiDAR validated using ground observations; and, 3) time-series characterisation of land cover features. 1. Accuracy targets for remotely sensed LAI products to match within ground based estimates are ± 0.5 LAI or a 20% maximum (CEOS/GCOS) with new aspirational targets of 5%). In this research we conducted a total of 67 ground-based method-to-method pairwise comparisons across 11 plots in five sites, incorporating the previously mentioned LAI methods. Out of the 67 comparisons, 29 had an RMSE ≥ 0.5 LAIe. This has important implications for the validation of remotely sensed products since ground based techniques themselves exhibit LAI variations greater than internationally recommended guidelines for satellite product accuracies. 2. Two methods of canopy height derivation are proposed and tested over a large area (4 Million Ha). 99th percentile maximum height achieved a RMSE of 6.6%, whilst 95th percentile dominant height a RMSE = 10.3%. Vertical canopy complexity (i.e. the number of forest layers of strata) was calculated as the local maxima of vegetation density within the LiDAR canopy profile and determined using a cubic spline smoothing of Pgap. This was then validated against in-situ and LiDAR observations of canopy strata with an RMSE 0.39 canopy layers. 3. Preliminary results are presented of landcover characterisation using LandTrendr analysis of Landsat LEDAPS data. kNN is then used to link these features to a dense network of 800 field plots sites.

Mapping Vegetation Community Types in a Highly-Disturbed Landscape: Integrating Hiearchical Object-Based Image Analysis with Digital Surface Models

NASA Astrophysics Data System (ADS)

Snavely, Rachel A.

Focusing on the semi-arid and highly disturbed landscape of San Clemente Island, California, this research tests the effectiveness of incorporating a hierarchal object-based image analysis (OBIA) approach with high-spatial resolution imagery and light detection and range (LiDAR) derived canopy height surfaces for mapping vegetation communities. The study is part of a large-scale research effort conducted by researchers at San Diego State University's (SDSU) Center for Earth Systems Analysis Research (CESAR) and Soil Ecology and Restoration Group (SERG), to develop an updated vegetation community map which will support both conservation and management decisions on Naval Auxiliary Landing Field (NALF) San Clemente Island. Trimble's eCognition Developer software was used to develop and generate vegetation community maps for two study sites, with and without vegetation height data as input. Overall and class-specific accuracies were calculated and compared across the two classifications. The highest overall accuracy (approximately 80%) was observed with the classification integrating airborne visible and near infrared imagery having very high spatial resolution with a LiDAR derived canopy height model. Accuracies for individual vegetation classes differed between both classification methods, but were highest when incorporating the LiDAR digital surface data. The addition of a canopy height model, however, yielded little difference in classification accuracies for areas of very dense shrub cover. Overall, the results show the utility of the OBIA approach for mapping vegetation with high spatial resolution imagery, and emphasizes the advantage of both multi-scale analysis and digital surface data for accuracy characterizing highly disturbed landscapes. The integrated imagery and digital canopy height model approach presented both advantages and limitations, which have to be considered prior to its operational use in mapping vegetation communities.

Resolution of lava tubes with ground penetrating radar: preliminary results from the TubeX project

NASA Astrophysics Data System (ADS)

Esmaeili, S.; Kruse, S.; Garry, W. B.; Whelley, P.; Young, K.; Jazayeri, S.; Bell, E.; Paylor, R.

2017-12-01

As early as the mid 1970's it was postulated that planetary tubes or caves on other planetary bodies (i.e., the Moon or Mars) could provide safe havens for human crews, protect life and shield equipment from harmful radiation, rapidly fluctuating surface temperatures, and even meteorite impacts. What is not clear, however, are the exploration methods necessary to evaluate a potential tube-rich environment to locate suitable tubes suitable for human habitation. We seek to address this knowledge gap using a suite of instruments to detect and document tubes in a terrestrial analog study at Lava Beds National Monument, California, USA. Here we describe the results of ground penetrating radar (GPR) profiles and light detection and ranging (LiDAR) scans. Surveys were conducted from the surface and within four lava tubes (Hercules Leg, Skull, Valentine and, Indian Well Caves) with varying flow composition, shape, and complexity. Results are shown across segments of these tubes where the tubes are <1 m to ranging > 10 m in height and the ceilings are 1 - 10 m below the surface. The GPR profiles over the tubes are, as expected, complex, due to scattering from fractures in roof material and three-dimensional heterogeneities. Point clouds derived from the LiDAR scans of both the interior and exterior of the lava tubes provide precise positioning of the tube geometry and depth of the ceiling and floor with respect to the surface topography. GPR profiles over LiDAR-mapped tube cross-sections are presented and compared against synthetic models of radar response to the measured geometry. This comparison will help to better understand the origins of characteristic features in the radar profiles. We seek to identify the optimal data processing and migration approaches to aid lava tube exploration of planetary surfaces.

Coastal erosion and mass wasting along the Canadian Beaufort Sea based on annual airborne LiDAR elevation data

NASA Astrophysics Data System (ADS)

Obu, Jaroslav; Lantuit, Hugues; Grosse, Guido; Günther, Frank; Sachs, Torsten; Helm, Veit; Fritz, Michael

2017-09-01

Erosion of permafrost coasts has received increasing scientific attention since 1990s because of rapid land loss and the mobilisation potential of old organic carbon. The majority of permafrost coastal erosion studies are limited to time periods from a few years to decades. Most of these studies emphasize the spatial variability of coastal erosion, but the intensity of inter-annual variations, including intermediate coastal aggradation, remains poorly documented. We used repeat airborne Light Detection And Ranging (LiDAR) elevation data from 2012 and 2013 with 1 m horizontal resolution to study coastal erosion and accompanying mass-wasting processes in the hinterland. Study sites were selected to include different morphologies along the coast of the Yukon Coastal Plain and on Herschel Island. We studied elevation and volume changes and coastline movement and compared the results between geomorphic units. Results showed simple uniform coastal erosion from low coasts (up to 10 m height) and a highly diverse erosion pattern along coasts with higher backshore elevation. This variability was particularly pronounced in the case of active retrogressive thaw slumps, which can decrease coastal erosion or even cause temporary progradation by sediment release. Most of the extremes were recorded in study sites with active slumping (e.g. 22 m of coastline retreat and 42 m of coastline progradation). Coastline progradation also resulted from the accumulation of slope collapse material. These occasional events can significantly affect the coastline position on a specific date and can affect coastal retreat rates as estimated in long term by coastline digitalisation from air photos and satellite imagery. These deficiencies can be overcome by short-term airborne LiDAR measurements, which provide detailed and high-resolution information about quickly changing elevations in coastal areas.

Numerical simulation and analysis for low-frequency rock physics measurements

NASA Astrophysics Data System (ADS)

Dong, Chunhui; Tang, Genyang; Wang, Shangxu; He, Yanxiao

2017-10-01

In recent years, several experimental methods have been introduced to measure the elastic parameters of rocks in the relatively low-frequency range, such as differential acoustic resonance spectroscopy (DARS) and stress-strain measurement. It is necessary to verify the validity and feasibility of the applied measurement method and to quantify the sources and levels of measurement error. Relying solely on the laboratory measurements, however, we cannot evaluate the complete wavefield variation in the apparatus. Numerical simulations of elastic wave propagation, on the other hand, are used to model the wavefield distribution and physical processes in the measurement systems, and to verify the measurement theory and analyze the measurement results. In this paper we provide a numerical simulation method to investigate the acoustic waveform response of the DARS system and the quasi-static responses of the stress-strain system, both of which use axisymmetric apparatus. We applied this method to parameterize the properties of the rock samples, the sample locations and the sensor (hydrophone and strain gauges) locations and simulate the measurement results, i.e. resonance frequencies and axial and radial strains on the sample surface, from the modeled wavefield following the physical experiments. Rock physical parameters were estimated by inversion or direct processing of these data, and showed a perfect match with the true values, thus verifying the validity of the experimental measurements. Error analysis was also conducted for the DARS system with 18 numerical samples, and the sources and levels of error are discussed. In particular, we propose an inversion method for estimating both density and compressibility of these samples. The modeled results also showed fairly good agreement with the real experiment results, justifying the effectiveness and feasibility of our modeling method.

Effect of target color and scanning geometry on terrestrial LiDAR point-cloud noise and plane fitting

NASA Astrophysics Data System (ADS)

Bolkas, Dimitrios; Martinez, Aaron

2018-01-01

Point-cloud coordinate information derived from terrestrial Light Detection And Ranging (LiDAR) is important for several applications in surveying and civil engineering. Plane fitting and segmentation of target-surfaces is an important step in several applications such as in the monitoring of structures. Reliable parametric modeling and segmentation relies on the underlying quality of the point-cloud. Therefore, understanding how point-cloud errors affect fitting of planes and segmentation is important. Point-cloud intensity, which accompanies the point-cloud data, often goes hand-in-hand with point-cloud noise. This study uses industrial particle boards painted with eight different colors (black, white, grey, red, green, blue, brown, and yellow) and two different sheens (flat and semi-gloss) to explore how noise and plane residuals vary with scanning geometry (i.e., distance and incidence angle) and target-color. Results show that darker colors, such as black and brown, can produce point clouds that are several times noisier than bright targets, such as white. In addition, semi-gloss targets manage to reduce noise in dark targets by about 2-3 times. The study of plane residuals with scanning geometry reveals that, in many of the cases tested, residuals decrease with increasing incidence angles, which can assist in understanding the distribution of plane residuals in a dataset. Finally, a scheme is developed to derive survey guidelines based on the data collected in this experiment. Three examples demonstrate that users should consider instrument specification, required precision of plane residuals, required point-spacing, target-color, and target-sheen, when selecting scanning locations. Outcomes of this study can aid users to select appropriate instrumentation and improve planning of terrestrial LiDAR data-acquisition.

LiDAR and IFSAR-Based Flood Inundation Model Estimates for Flood-Prone Areas of Afghanistan

NASA Astrophysics Data System (ADS)

Johnson, W. C.; Goldade, M. M.; Kastens, J.; Dobbs, K. E.; Macpherson, G. L.

2014-12-01

Extreme flood events are not unusual in semi-arid to hyper-arid regions of the world, and Afghanistan is no exception. Recent flashfloods and flashflood-induced landslides took nearly 100 lives and destroyed or damaged nearly 2000 homes in 12 villages within Guzargah-e-Nur district of Baghlan province in northeastern Afghanistan. With available satellite imagery, flood-water inundation estimation can be accomplished remotely, thereby providing a means to reduce the impact of such flood events by improving shared situational awareness during major flood events. Satellite orbital considerations, weather, cost, data licensing restrictions, and other issues can often complicate the acquisition of appropriately timed imagery. Given the need for tools to supplement imagery where not available, complement imagery when it is available, and bridge the gap between imagery based flood mapping and traditional hydrodynamic modeling approaches, we have developed a topographic floodplain model (FLDPLN), which has been used to identify and map river valley floodplains with elevation data ranging from 90-m SRTM to 1-m LiDAR. Floodplain "depth to flood" (DTF) databases generated by FLDPLN are completely seamless and modular. FLDPLN has been applied in Afghanistan to flood-prone areas along the northern and southern flanks of the Hindu Kush mountain range to generate a continuum of 1-m increment flood-event models up to 10 m in depth. Elevation data used in this application of FLDPLN included high-resolution, drone-acquired LiDAR (~1 m) and IFSAR (5 m; INTERMAP). Validation of the model has been accomplished using the best available satellite-derived flood inundation maps, such as those issued by Unitar's Operational Satellite Applications Programme (UNOSAT). Results provide a quantitative approach to evaluating the potential risk to urban/village infrastructure as well as to irrigation systems, agricultural fields and archaeological sites.

Spatio Temporal Detection and Virtual Mapping of Landslide Using High-Resolution Airborne Laser Altimetry (lidar) in Densely Vegetated Areas of Tropics

NASA Astrophysics Data System (ADS)

Bibi, T.; Azahari Razak, K.; Rahman, A. Abdul; Latif, A.

2017-10-01

Landslides are an inescapable natural disaster, resulting in massive social, environmental and economic impacts all over the world. The tropical, mountainous landscape in generally all over Malaysia especially in eastern peninsula (Borneo) is highly susceptible to landslides because of heavy rainfall and tectonic disturbances. The purpose of the Landslide hazard mapping is to identify the hazardous regions for the execution of mitigation plans which can reduce the loss of life and property from future landslide incidences. Currently, the Malaysian research bodies e.g. academic institutions and government agencies are trying to develop a landslide hazard and risk database for susceptible areas to backing the prevention, mitigation, and evacuation plan. However, there is a lack of devotion towards landslide inventory mapping as an elementary input of landslide susceptibility, hazard and risk mapping. The developing techniques based on remote sensing technologies (satellite, terrestrial and airborne) are promising techniques to accelerate the production of landslide maps, shrinking the time and resources essential for their compilation and orderly updates. The aim of the study is to provide a better perception regarding the use of virtual mapping of landslides with the help of LiDAR technology. The focus of the study is spatio temporal detection and virtual mapping of landslide inventory via visualization and interpretation of very high-resolution data (VHR) in forested terrain of Mesilau river, Kundasang. However, to cope with the challenges of virtual inventory mapping on in forested terrain high resolution LiDAR derivatives are used. This study specifies that the airborne LiDAR technology can be an effective tool for mapping landslide inventories in a complex climatic and geological conditions, and a quick way of mapping regional hazards in the tropics.

Asymptomatic bacteriuria and concomitant presence of other micro-organisms in urine of pregnant women in Dar es Salaam -- Tanzania.

PubMed

Mtimavalye, L A; Runyoro, D E; Massawe, F N; Mhalu, F S; Kanyawana, J Z

1983-09-01

This study was designed to determine the prevalence of significant bacteriuria in pregnancy in Dar es Salaam as well as attempt to find out whether bacteriuria has any effects on the mother and baby. Of 1007 pregnant women studied for asymptomatic bacteriuria, a significant bacteriuria rate of 6.3% was revealed. Escherichia coli was the predominant organism, making up 47.6% of the total organisms isolated. Schistosoma hematobium was present in 8.7%, T. vaginalis in 14%, yeast cells were found in the urine of 9.1% and the microfilariae of Wuchereria bancrofti were found in 1 specimen. 66.2% had no abnormality in their urine. It is recommended on the basis of this study that all women found to have significant bacteriuria in 1 cultured urine sample should be treated. There was a significant relationship noted between significant bacteriuria and the passing of S. hematobium in the urine. There was also a significant correlation between the presence of T. vaginalis and yeast cells in the urine. On the basis of laboratory sensitivity studies it was also found that the antimicrobial agents of choice for treating urinary tract infections in Dar es Salaam where E. coli and Klebsiella erogenes are the predominant organisms are nitrofurantoin, nalidixic acid and co-trimoxazole. The socioeconomic status of the bacteriuric and control group was divided into 4 groups according to take home pay; results show no significant increase of bacteriuria in any of the groups. It was not possible to follow up the effects of the presence of micro-organisms in urine during pregnancy because once a woman was found to have a positive culture she was treated.

Genome-wide association mapping of quantitative traits in a breeding population of sugarcane.

PubMed

Racedo, Josefina; Gutiérrez, Lucía; Perera, María Francisca; Ostengo, Santiago; Pardo, Esteban Mariano; Cuenya, María Inés; Welin, Bjorn; Castagnaro, Atilio Pedro

2016-06-24

Molecular markers associated with relevant agronomic traits could significantly reduce the time and cost involved in developing new sugarcane varieties. Previous sugarcane genome-wide association analyses (GWAS) have found few molecular markers associated with relevant traits at plant-cane stage. The aim of this study was to establish an appropriate GWAS to find molecular markers associated with yield related traits consistent across harvesting seasons in a breeding population. Sugarcane clones were genotyped with DArT (Diversity Array Technology) and TRAP (Target Region Amplified Polymorphism) markers, and evaluated for cane yield (CY) and sugar content (SC) at two locations during three successive crop cycles. GWAS mapping was applied within a novel mixed-model framework accounting for population structure with Principal Component Analysis scores as random component. A total of 43 markers significantly associated with CY in plant-cane, 42 in first ratoon, and 41 in second ratoon were detected. Out of these markers, 20 were associated with CY in 2 years. Additionally, 38 significant associations for SC were detected in plant-cane, 34 in first ratoon, and 47 in second ratoon. For SC, one marker-trait association was found significant for the 3 years of the study, while twelve markers presented association for 2 years. In the multi-QTL model several markers with large allelic substitution effect were found. Sequences of four DArT markers showed high similitude and e-value with coding sequences of Sorghum bicolor, confirming the high gene microlinearity between sorghum and sugarcane. In contrast with other sugarcane GWAS studies reported earlier, the novel methodology to analyze multi-QTLs through successive crop cycles used in the present study allowed us to find several markers associated with relevant traits. Combining existing phenotypic trial data and genotypic DArT and TRAP marker characterizations within a GWAS approach including population structure as random covariates may prove to be highly successful. Moreover, sequences of DArT marker associated with the traits of interest were aligned in chromosomal regions where sorghum QTLs has previously been reported. This approach could be a valuable tool to assist the improvement of sugarcane and better supply sugarcane demand that has been projected for the upcoming decades.

Tree species classification using within crown localization of waveform LiDAR attributes

NASA Astrophysics Data System (ADS)

Blomley, Rosmarie; Hovi, Aarne; Weinmann, Martin; Hinz, Stefan; Korpela, Ilkka; Jutzi, Boris

2017-11-01

Since forest planning is increasingly taking an ecological, diversity-oriented perspective into account, remote sensing technologies are becoming ever more important in assessing existing resources with reduced manual effort. While the light detection and ranging (LiDAR) technology provides a good basis for predictions of tree height and biomass, tree species identification based on this type of data is particularly challenging in structurally heterogeneous forests. In this paper, we analyse existing approaches with respect to the geometrical scale of feature extraction (whole tree, within crown partitions or within laser footprint) and conclude that currently features are always extracted separately from the different scales. Since multi-scale approaches however have proven successful in other applications, we aim to utilize the within-tree-crown distribution of within-footprint signal characteristics as additional features. To do so, a spin image algorithm, originally devised for the extraction of 3D surface features in object recognition, is adapted. This algorithm relies on spinning an image plane around a defined axis, e.g. the tree stem, collecting the number of LiDAR returns or mean values of returns attributes per pixel as respective values. Based on this representation, spin image features are extracted that comprise only those components of highest variability among a given set of library trees. The relative performance and the combined improvement of these spin image features with respect to non-spatial statistical metrics of the waveform (WF) attributes are evaluated for the tree species classification of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and Silver/Downy birch (Betula pendula Roth/Betula pubescens Ehrh.) in a boreal forest environment. This evaluation is performed for two WF LiDAR datasets that differ in footprint size, pulse density at ground, laser wavelength and pulse width. Furthermore, we evaluate the robustness of the proposed method with respect to internal parameters and tree size. The results reveal, that the consideration of the crown-internal distribution of within-footprint signal characteristics captured in spin image features improves the classification results in nearly all test cases.

Canopy wake measurements using multiple scanning wind LiDARs

NASA Astrophysics Data System (ADS)

Markfort, C. D.; Carbajo Fuertes, F.; Iungo, V.; Stefan, H. G.; Porte-Agel, F.

2014-12-01

Canopy wakes have been shown, in controlled wind tunnel experiments, to significantly affect the fluxes of momentum, heat and other scalars at the land and water surface over distances of ˜O(1 km), see Markfort et al. (EFM, 2013). However, there are currently no measurements of the velocity field downwind of a full-scale forest canopy. Point-based anemometer measurements of wake turbulence provide limited insight into the extent and details of the wake structure, whereas scanning Doppler wind LiDARs can provide information on how the wake evolves in space and varies over time. For the first time, we present measurements of the velocity field in the wake of a tall patch of forest canopy. The patch consists of two uniform rows of 40-meter tall deciduous, plane trees, which border either side of the Allée de Dorigny, near the EPFL campus. The canopy is approximately 250 m long, and it is approximately 40 m wide, along the direction of the wind. A challenge faced while making field measurements is that the wind rarely intersects a canopy normal to the edge. The resulting wake flow may be deflected relative to the mean inflow. Using multiple LiDARs, we measure the evolution of the wake due to an oblique wind blowing over the canopy. One LiDAR is positioned directly downwind of the canopy to measure the flow along the mean wind direction and the other is positioned near the canopy to evaluate the transversal component of the wind and how it varies with downwind distance from the canopy. Preliminary results show that the open trunk space near the base of the canopy results in a surface jet that can be detected just downwind of the canopy and farther downwind dissipates as it mixes with the wake flow above. A time-varying recirculation zone can be detected by the periodic reversal of the velocity near the surface, downwind of the canopy. The implications of canopy wakes for measurement and modeling of surface fluxes will be discussed.

Canopy wake measurements using multiple scanning wind LiDARs

NASA Astrophysics Data System (ADS)

Markfort, Corey D.; Carbajo Fuertes, Fernando; Valerio Iungo, Giacomo; Stefan, Heinz; Porté-Agel, Fernando

2014-05-01

Canopy wakes have been shown, in controlled wind tunnel experiments, to significantly affect the fluxes of momentum, heat and other scalars at the land and water surface over distances of ~O(1 km), see Markfort et al. (EFM, 2013). However, there are currently no measurements of the velocity field downwind of a full-scale forest canopy. Point-based anemometer measurements of wake turbulence provide limited insight into the extent and details of the wake structure, whereas scanning Doppler wind LiDARs can provide information on how the wake evolves in space and varies over time. For the first time, we present measurements of the velocity field in the wake of a tall patch of forest canopy. The patch consists of two uniform rows of 35-meter tall deciduous, plane trees, which border either side of the Allée de Dorigny, near the EPFL campus. The canopy is approximately 250 m long, and it is 35 m wide, along the direction of the wind. A challenge faced while making field measurements is that the wind rarely intersects a canopy normal to the edge. The resulting wake flow may be deflected relative to the mean inflow. Using multiple LiDARs, we measure the evolution of the wake due to an oblique wind blowing over the canopy. One LiDAR is positioned directly downwind of the canopy to measure the flow along the mean wind direction and the other is positioned near the canopy to evaluate the transversal component of the wind and how it varies with downwind distance from the canopy. Preliminary results show that the open trunk space near the base of the canopy results in a surface jet that can be detected just downwind of the canopy and farther downwind dissipates as it mixes with the wake flow above. A time-varying recirculation zone can be detected by the periodic reversal of the velocity vector near the surface, downwind of the canopy. The implications of canopy wakes for measurement and modeling of surface fluxes will be discussed.

Estimation of hydromorphological attributes of a small forested catchment by applying the Structure from Motion (SfM) approach

NASA Astrophysics Data System (ADS)

Méndez-Barroso, Luis A.; Zárate-Valdez, Jose L.; Robles-Morúa, Agustín

2018-07-01

Structure from Motion (SfM) represents a good low-cost alternative to generate high resolution topography where LiDAR (Light Detection and Ranging) data is scarce or unaffordable. In this work, we demonstrate the advantages of high resolution elevation models (DEM) obtained using the SfM technique to delineate catchment boundaries and the stream network. The SfM-based DEM was compared with LiDAR data, distributed by the Mexican Government, and a previous high resolution topographic map generated by a RTK-GPS system. Aerial images were collected on a forested ecohydrological monitoring site in northwest Mexico using a commercial grade digital camera attached to a tethered helium balloon. Here we applied the SfM method with the removal of the vegetation, similarly to the more advance LiDAR methods. This was achieved by adjusting the point cloud classification parameters (maximum angle, maximum distance and cell size), which to our knowledge, has not has not been reported in the available SfM literature. The SfM terrain model showed minimal differences in ground elevation in the center of the image domain (0-0.5 m) while errors increased on the edges of the domain. The SfM model generated the largest catchment area, main and total channel length (1.07 ha, 106.1 and 223 m, respectively) while LiDAR model obtained the smallest area and main channel length (0.77 ha and 92.9 m, respectively). On the other hand, the SfM model had a better and accurate representation of the river network among all models evaluated due to its closest proximity to the observed GPS-tracked main channel. We concluded that the integration of low cost unmanned aerial vehicles and the SfM method is a good alternative to estimate hydro-morphological attributes in small catchments. Furthermore, we found that high resolution SfM-based terrain models had a fairly good representation of small catchments which is useful in regions with limited data availability. The main findings of this research provide scientific value within the field of hydrological remote sensing in particular in the acquisition of high resolution topography in remote areas without access to more expensive LiDAR or survey techniques. High resolution DEMs allow for a better characterization of catchment area size and stream network delineation which influence hydrological processes (i.e. soil moisture redistribution, runoff, ET).

Detectability and geomorphometry of tufa barrages in a small forested karstic river using airborne LiDAR topo-bathymetry

NASA Astrophysics Data System (ADS)

Profe, Jörn; Höfle, Bernhard

2017-04-01

Tufas are secondary carbonate precipitations which occur ubiquitously in karstic environments. Thus, freshwater tufas are increasingly noticed as a high-resolution terrestrial paleoclimate archive. However, complex interactions between climate, hydrology and geomorphology drive tufa landscapes as a self-organizing system that creates a patchy transition zone between land and water at the decimeter scale. These feedbacks challenge the modern analogue technique to understand paleo-tufa evolution and require a detailed 3D characterization of tufa geomorphometry to better understand their shaping processes in relation to channel bed morphology. Due to the complex geometric nature of tufa landscapes and predominant land-water transition zones, new remote sensing techniques such as airborne sub-meter footprint LiDAR topo-bathymetry (ALTB) are necessary to enable a detailed 3D description. Using the Riegl VQ-820-G at the Kaisinger Brunnenbach, Germany, we successfully detected submerged and subaerial tufas with maximum total dam heights from 0.3 m up to 1.6 m (cf. Profe et al. 2016). In addition, slope and openness derived from a high-resolution digital terrain model (DTM) with 0.2 m spatial resolution provide insights into barrage morphology and orientation. We found that longitudinal slope analysis along the river course relates tufa morphology to channel bed morphology. Raster-based data quality control of the LiDAR topo-bathymetric DTM reveals an overall vertical data precision of 3 cm and an overall vertical data accuracy of 15.4 cm (1σ) (Profe et al. 2016). The 3D characterization of tufa landscapes facilitates the identification of monitoring and drilling sites for subsequent hydrological and geochemical studies that deepen our knowledge about the complex barrage formation processes. In the advent of UAV-borne LiDAR platforms, we are convinced that it becomes possible to reduce data uncertainty and to better represent e.g. tufa overhangs, vegetation cover and incorporated plant material. Furthermore, our findings may foster research in other disciplines that work on small-scale land-water transition zones and are interested in a detailed 3D geomorphometric description derived from 3D point clouds directly. Reference: Profe, J., Höfle, B., Hämmerle, M., Steinbacher, F., Yang, M.-S., Schröder-Ritzrau, A., Frank, N., 2016. Characterizing tufa barrages in relation to channel bed morphology in a small karstic river by airborne LiDAR topo-bathymetry. Proceedings of the Geologists' Association 127: 664-675. doi:10.1016/j.pgeola.2016.10.004

IDA Publications on Irregular Warfare: A Bibliography 2000 - Fall 2008

DTIC Science & Technology

2008-12-01

Affairs Insurgency Quds Force Civil Military Insurrection Radical Islam Civil Services Interagency Reconciliation Coalition Intifada Reconstruction...decision-making. While the reports have not been formally released, the database has been shared on a regular basis with other agencies and Services ...ACT ID A PUBLICATION NO. & L IMITATIONS PUBLICATION YEAR individuals. The objective SEIR curves characterize health care and mortuary service

Do we need a voxel-based approach for LiDAR data in geomorphology?

NASA Astrophysics Data System (ADS)

Székely, Balázs; Dorninger, Peter; Faber, Robert; Nothegger, Clemens

2010-05-01

Generations of geomorphologists have developed a multi-faceted approach to model the Earth's (and planetary) surface and the corresponding processes. This set of models is based on data, more specifically on conspicuously increasing amount of data. Obviously, all geomorphologists wish themselves more accurate and increasingly high resolution data on, or related to the Earth surface. This evolution also means that the studied boundary is not anymore a single surface; instead it is considered mostly a 2.5D object, sometimes a real 3D object. LiDAR technology can cope with this challenge: the data accuracy and resolution requirements can be fulfilled by applying this method. Although it is yet somewhat still expensive, more and more areas will be scanned, and in some regions the topographic point clouds are already multitemporal (causing of course other types of processing and evaluation problems). It is rather obvious that for certain, geomorphologically very interesting areas very dense and severalfold multitemporal LiDAR data will be available in the near future. These data sets will have various differences concerning the data density, accuracy, data acquisition technique (conventional or full-waveform), and perhaps most importantly, concerning the actual state of the surface. Similar to the satellite imagery integration problems, soon we all have to face with the LiDAR data integration problem. What type of surface or surfaces can be derived from this multitude of data sources with acceptable ambiguity? What conclusions can be drawn from these data that were originally acquired for various other purposes using various acquisition concepts? Will it be advantageous for geomorphic use to have a coverage of the surface with 100-200 points/m² density? Clearly, these data are, if they are once collected, still too expensive not to be integrated for further analyses. Consequently, we need a data reduction concept that effectively decreases the computer capacity needed to store, process and visualize the results. To reduce the amount of originally collected data for further applications, in general, continuous model surfaces are derived from the point clouds using interpolation approaches. Commonly, grid-based or triangulation models are used for that purpose. Typical models are Digital Surface Models (DSM) representing the whole topography including all natural (e.g. vegetation) and artificial (e.g. buildings) objects and Digital Terrain Models (DTM) representing the topography only. In the visual computing industry the voxel-based approach is quite common for various purposes. Although this technology is quite straightforward concerning the data reduction, it is hardly applied in the geomorphic context. An argument can be against its application that mostly we are interested in a surface, not a volume. Of course in the strict sense it is true, however, if we consider the technology itself how the data, especially the ground data are derived, it turns out that actually it is a volume with a certain accuracy that we are sampling of. The position of this "relatively thin" volume also varies, especially in mountainous areas. Here, depending on the slope angles, the accuracy also varies, especially for the integrated data set consisting of a multitude of sources, e.g. mixing conventional (first echo/last echo) and full-waveform data. These point clouds also contain attributes that otherwise could be very valuable, but during the integration, their meaning may be lost, or it cannot be integrated to the data set. A large scale application of such approaches is mainly prevented by the problems introduced by the high amount of data, making on-the-fly processing a challenging task. To overcome these restrictions and to enable taking advantage of the new possibilities provided by the waveform analysis, we propose a voxel-based data representation approach. The multichannel/multilayer design with an a priori unlimited number of layers enables storing an unlimited number of additional parameter per point. We expect that such a voxel structure enables to represent and analyze huge datasets of large areas (e.g., connected regions which are geologically relevant to be analyzed at once) in applicable processing times in order to bridge the gap between the original point cloud and the user and interpretation level. The challenging task to be solved will be to reduce the amount of data significantly by means of the proposed structure while preserving the content of the original data.

Impact of survey workflow on precision and accuracy of terrestrial LiDAR datasets

NASA Astrophysics Data System (ADS)

Gold, P. O.; Cowgill, E.; Kreylos, O.

2009-12-01

Ground-based LiDAR (Light Detection and Ranging) survey techniques are enabling remote visualization and quantitative analysis of geologic features at unprecedented levels of detail. For example, digital terrain models computed from LiDAR data have been used to measure displaced landforms along active faults and to quantify fault-surface roughness. But how accurately do terrestrial LiDAR data represent the true ground surface, and in particular, how internally consistent and precise are the mosaiced LiDAR datasets from which surface models are constructed? Addressing this question is essential for designing survey workflows that capture the necessary level of accuracy for a given project while minimizing survey time and equipment, which is essential for effective surveying of remote sites. To address this problem, we seek to define a metric that quantifies how scan registration error changes as a function of survey workflow. Specifically, we are using a Trimble GX3D laser scanner to conduct a series of experimental surveys to quantify how common variables in field workflows impact the precision of scan registration. Primary variables we are testing include 1) use of an independently measured network of control points to locate scanner and target positions, 2) the number of known-point locations used to place the scanner and point clouds in 3-D space, 3) the type of target used to measure distances between the scanner and the known points, and 4) setting up the scanner over a known point as opposed to resectioning of known points. Precision of the registered point cloud is quantified using Trimble Realworks software by automatic calculation of registration errors (errors between locations of the same known points in different scans). Accuracy of the registered cloud (i.e., its ground-truth) will be measured in subsequent experiments. To obtain an independent measure of scan-registration errors and to better visualize the effects of these errors on a registered point cloud, we scan from multiple locations an object of known geometry (a cylinder mounted above a square box). Preliminary results show that even in a controlled experimental scan of an object of known dimensions, there is significant variability in the precision of the registered point cloud. For example, when 3 scans of the central object are registered using 4 known points (maximum time, maximum equipment), the point clouds align to within ~1 cm (normal to the object surface). However, when the same point clouds are registered with only 1 known point (minimum time, minimum equipment), misalignment of the point clouds can range from 2.5 to 5 cm, depending on target type. The greater misalignment of the 3 point clouds when registered with fewer known points stems from the field method employed in acquiring the dataset and demonstrates the impact of field workflow on LiDAR dataset precision. By quantifying the degree of scan mismatch in results such as this, we can provide users with the information needed to maximize efficiency in remote field surveys.

Comparative analysis of genetic architectures for nine developmental traits of rye.

PubMed

Masojć, Piotr; Milczarski, P; Kruszona, P

2017-08-01

Genetic architectures of plant height, stem thickness, spike length, awn length, heading date, thousand-kernel weight, kernel length, leaf area and chlorophyll content were aligned on the DArT-based high-density map of the 541 × Ot1-3 RILs population of rye using the genes interaction assorting by divergent selection (GIABDS) method. Complex sets of QTL for particular traits contained 1-5 loci of the epistatic D class and 10-28 loci of the hypostatic, mostly R and E classes controlling traits variation through D-E or D-R types of two-loci interactions. QTL were distributed on each of the seven rye chromosomes in unique positions or as a coinciding loci for 2-8 traits. Detection of considerable numbers of the reversed (D', E' and R') classes of QTL might be attributed to the transgression effects observed for most of the studied traits. First examples of E* and F QTL classes, defined in the model, are reported for awn length, leaf area, thousand-kernel weight and kernel length. The results of this study extend experimental data to 11 quantitative traits (together with pre-harvest sprouting and alpha-amylase activity) for which genetic architectures fit the model of mechanism underlying alleles distribution within tails of bi-parental populations. They are also a valuable starting point for map-based search of genes underlying detected QTL and for planning advanced marker-assisted multi-trait breeding strategies.

Inferring sediment connectivity from high-resolution DEMs of Difference

NASA Astrophysics Data System (ADS)

Heckmann, Tobias; Vericat, Damià

2017-04-01

Topographic changes due to the erosion and deposition of bedrock, sediments and soil can be measured by differencing Digital Elevation Models (DEM) acquired at different points in time. So-called morphological sediment budgets can be computed from such DEMs of Difference (DoD) on an areal rather than a point basis. The advent of high-resolution and highly accurate surveying techniques (e.g. LiDAR, SfM), together with recent advances of survey platforms (e.g. UaVs) provides opportunities to improve the spatial and temporal scale (in terms of extent and resolution), the availability and quality of such measurements. Many studies have used DoD to investigate and interpret the spatial pattern of positive and negative vertical differences in terms of erosion and deposition, or of horizontal movement. Vertical differences can be converted to volumes, and negative (erosion) and positive (deposition) volumetric changes aggregated for spatial units (e.g., landforms, hillslopes, river channels) have been used to compute net balances. We argue that flow routing algorithms common in digital terrain analysis provide a means to enrich DoD-based investigations with some information about (potential) sediment pathways - something that has been widely neglected in previous studies. Where the DoD indicates a positive surface change, flow routing delineates the upslope area where the deposited sediment has potentially been derived from. In the downslope direction, flow routing indicates probable downslope pathways of material eroded/detached/entrained where the DoD shows negative surface change. This material has either been deposited along these pathways or been flushed out of the area of investigation. This is a question of sediment connectivity, a property of a system (i.e. a hillslope, a sub-/catchment) that describes its potential to move sediment through itself. The sediment pathways derived from the DEM are related to structural connectivity, while the spatial pattern of (net) erosion and deposition has emerged from sediment transfer between the two epochs of the DoD (i.e. functional connectivity). In this study, we use multitemporal raster DEMs generated (i) from terrestrial LiDAR surveys and (ii) by a landscape evolution model to compute DoDs. Flow accumulation is used to compute, for the contributing area of each raster cell, (i) the net balance and (ii) the total sum of material eroded. The net balance represents the sediment yield of the contributing area. In the case of a study area delimited by a catchment boundary, it is either negative (more sediment eroded than deposited within the contributing area, i.e. net export) or zero (eroded material has been re-deposited within the contributing area). Finally, the ratio of sediment yield and gross erosion is called the sediment delivery ratio (SDR). This number has been used as a "performance factor" indicating the degree of sediment connectivity, as it describes the proportion of material eroded on the local scale that is being delivered to the outlet of the contributing area. The evaluation of a DoD to compute the SDR overcomes one major criticism of the SDR, namely that gross erosion is generally estimated (e.g. by empirical USLE-type equations) rather than measured. Both our proposed approach and the concept of SDR are subject to a number of caveats, which we will discuss in our contribution. In any case, we advocate more detailed analyses of DoD using flow routing algorithms in order to include information on potential sediment pathways in morphological sediment budgets for hillslopes and catchments.

Modeling the transmission dynamics and control of rabies in China.

PubMed

Ruan, Shigui

2017-04-01

Human rabies was first recorded in ancient China in about 556 BC and is still one of the major public-health problems in China. From 1950 to 2015, 130,494 human rabies cases were reported in Mainland China with an average of 1977 cases per year. It is estimated that 95% of these human rabies cases are due to dog bites. The purpose of this article is to provide a review about the models, results, and simulations that we have obtained recently on studying the transmission of rabies in China. We first construct a basic susceptible, exposed, infectious, and recovered (SEIR) type model for the spread of rabies virus among dogs and from dogs to humans and use the model to simulate the human rabies data in China from 1996 to 2010. Then we modify the basic model by including both domestic and stray dogs and apply the model to simulate the human rabies data from Guangdong Province, China. To study the seasonality of rabies, in Section 4 we further propose a SEIR model with periodic transmission rates and employ the model to simulate the monthly data of human rabies cases reported by the Chinese Ministry of Health from January 2004 to December 2010. To understand the spatial spread of rabies, in Section 5 we add diffusion to the dog population in the basic SEIR model to obtain a reaction-diffusion equation model and determine the minimum wave speed connecting the disease-free equilibrium to the endemic equilibrium. Finally, in order to investigate how the movement of dogs affects the geographically inter-provincial spread of rabies in Mainland China, in Section 6 we propose a multi-patch model to describe the transmission dynamics of rabies between dogs and humans and use the two-patch submodel to investigate the rabies virus clades lineages and to simulate the human rabies data from Guizhou and Guangxi, Hebei and Fujian, and Sichuan and Shaanxi, respectively. Some discussions are provided in Section 7. Copyright © 2017 Elsevier Inc. All rights reserved.

Was mandatory quarantine necessary in China for controlling the 2009 H1N1 pandemic?

PubMed

Li, Xinhai; Geng, Wenjun; Tian, Huidong; Lai, Dejian

2013-09-30

The Chinese government enforced mandatory quarantine for 60 days (from 10 May to 8 July 2009) as a preventative strategy to control the spread of the 2009 H1N1 pandemic. Such a prevention strategy was stricter than other non-pharmaceutical interventions that were carried out in many other countries. We evaluated the effectiveness of the mandatory quarantine and provide suggestions for interventions against possible future influenza pandemics. We selected one city, Beijing, as the analysis target. We reviewed the epidemiologic dynamics of the 2009 H1N1 pandemic and the implementation of quarantine measures in Beijing. The infectious population was simulated under two scenarios (quarantined and not quarantined) using a deterministic Susceptible-Exposed-Infectious-Recovered (SEIR) model. The basic reproduction number R0 was adjusted to match the epidemic wave in Beijing. We found that mandatory quarantine served to postpone the spread of the 2009 H1N1 pandemic in Beijing by one and a half months. If mandatory quarantine was not enforced in Beijing, the infectious population could have reached 1,553 by 21 October, i.e., 5.6 times higher than the observed number. When the cost of quarantine is taken into account, mandatory quarantine was not an economically effective intervention approach against the 2009 H1N1 pandemic. We suggest adopting mitigation methods for an influenza pandemic with low mortality and morbidity.

Was Mandatory Quarantine Necessary in China for Controlling the 2009 H1N1 Pandemic?

PubMed Central

Li, Xinhai; Geng, Wenjun; Tian, Huidong; Lai, Dejian

2013-01-01

The Chinese government enforced mandatory quarantine for 60 days (from 10 May to 8 July 2009) as a preventative strategy to control the spread of the 2009 H1N1 pandemic. Such a prevention strategy was stricter than other non-pharmaceutical interventions that were carried out in many other countries. We evaluated the effectiveness of the mandatory quarantine and provide suggestions for interventions against possible future influenza pandemics. We selected one city, Beijing, as the analysis target. We reviewed the epidemiologic dynamics of the 2009 H1N1 pandemic and the implementation of quarantine measures in Beijing. The infectious population was simulated under two scenarios (quarantined and not quarantined) using a deterministic Susceptible-Exposed-Infectious-Recovered (SEIR) model. The basic reproduction number R0 was adjusted to match the epidemic wave in Beijing. We found that mandatory quarantine served to postpone the spread of the 2009 H1N1 pandemic in Beijing by one and a half months. If mandatory quarantine was not enforced in Beijing, the infectious population could have reached 1,553 by 21 October, i.e., 5.6 times higher than the observed number. When the cost of quarantine is taken into account, mandatory quarantine was not an economically effective intervention approach against the 2009 H1N1 pandemic. We suggest adopting mitigation methods for an influenza pandemic with low mortality and morbidity. PMID:24084677

Nonlinear model of epidemic spreading in a complex social network.

PubMed

Kosiński, Robert A; Grabowski, A

2007-10-01

The epidemic spreading in a human society is a complex process, which can be described on the basis of a nonlinear mathematical model. In such an approach the complex and hierarchical structure of social network (which has implications for the spreading of pathogens and can be treated as a complex network), can be taken into account. In our model each individual has one of the four permitted states: susceptible, infected, infective, unsusceptible or dead. This refers to the SEIR model used in epidemiology. The state of an individual changes in time, depending on the previous state and the interactions with other individuals. The description of the interpersonal contacts is based on the experimental observations of the social relations in the community. It includes spatial localization of the individuals and hierarchical structure of interpersonal interactions. Numerical simulations were performed for different types of epidemics, giving the progress of a spreading process and typical relationships (e.g. range of epidemic in time, the epidemic curve). The spreading process has a complex and spatially chaotic character. The time dependence of the number of infective individuals shows the nonlinear character of the spreading process. We investigate the influence of the preventive vaccinations on the spreading process. In particular, for a critical value of preventively vaccinated individuals the percolation threshold is observed and the epidemic is suppressed.

New Late Gene, dar, Involved in DNA Replication of Bacteriophage T4 I. Isolation, Characterization, and Genetic Location.

PubMed

Wu, J R; Yeh, Y C

1975-05-01

Suppressors of gene 59-defective mutants were isolated by screening spontaneous, temperature-sensitive (ts) revertants of the amber mutant, amC5, in gene 59. Six ts revertants were isolated. No gene 59-defective ts recombinant was obtained by crossing each ts revertant with the wild type, T4D. However, suppressors of gene 59-defective mutants were obtained from two of these ts revertants. These suppressor mutants are referred to as dar (DNA arrested restoration). dar mutants specifically restored the abnormalities, both in DNA synthesis and burst size, caused by gene 59-defective mutants to normal levels. It is unlikely that dar mutants are nonsense suppressors since theý failed to suppress amber mutations in 11 other genes investigated. The genetic expression of dar is controlled by gene 55; therefore, dar is a late gene. The genetic location of dar has been mapped between genes 24 and 25, a region contiguous to late genes. dar appears to be another nonessential gene of T4 since burst sizes of dar were almost identical to those of the wild type. Mutations in dar did not affect genetic recombination and repair of UV-damaged DNA, but caused a sensitivity to hydroxyurea in progeny formation. The effect of the dar mutation on host DNA degradation cannot account for its hydroxyurea sensitivity. dar mutant alleles were recessive to the wild-type allele as judged by restoration of arrested DNA synthesis. The possible mechanisms for the suppression of defects in gene 59 are discussed.

Comparison of physical and semi-empirical hydraulic models for flood inundation mapping

NASA Astrophysics Data System (ADS)

Tavakoly, A. A.; Afshari, S.; Omranian, E.; Feng, D.; Rajib, A.; Snow, A.; Cohen, S.; Merwade, V.; Fekete, B. M.; Sharif, H. O.; Beighley, E.

2016-12-01

Various hydraulic/GIS-based tools can be used for illustrating spatial extent of flooding for first-responders, policy makers and the general public. The objective of this study is to compare four flood inundation modeling tools: HEC-RAS-2D, Gridded Surface Subsurface Hydrologic Analysis (GSSHA), AutoRoute and Height Above the Nearest Drainage (HAND). There is a trade-off among accuracy, workability and computational demand in detailed, physics-based flood inundation models (e.g. HEC-RAS-2D and GSSHA) in contrast with semi-empirical, topography-based, computationally less expensive approaches (e.g. AutoRoute and HAND). The motivation for this study is to evaluate this trade-off and offer guidance to potential large-scale application in an operational prediction system. The models were assessed and contrasted via comparability analysis (e.g. overlapping statistics) by using three case studies in the states of Alabama, Texas, and West Virginia. The sensitivity and accuracy of physical and semi-eimpirical models in producing inundation extent were evaluated for the following attributes: geophysical characteristics (e.g. high topographic variability vs. flat natural terrain, urbanized vs. rural zones, effect of surface roughness paratermer value), influence of hydraulic structures such as dams and levees compared to unobstructed flow condition, accuracy in large vs. small study domain, effect of spatial resolution in topographic data (e.g. 10m National Elevation Dataset vs. 0.3m LiDAR). Preliminary results suggest that semi-empericial models tend to underestimate in a flat, urbanized area with controlled/managed river channel around 40% of the inundation extent compared to the physical models, regardless of topographic resolution. However, in places where there are topographic undulations, semi-empericial models attain relatively higher level of accuracy than they do in flat non-urbanized terrain.

Cordilleran forest scaling dynamics and disturbance regimes quantified by aerial lidar

NASA Astrophysics Data System (ADS)

Swetnam, Tyson L.

Semi-arid forests are in a period of rapid transition as a result of unprecedented landscape scale fires, insect outbreaks, drought, and anthropogenic land use practices. Understanding how historically episodic disturbances led to coherent forest structural and spatial patterns that promoted resilience and resistance is a critical part of addressing change. Here my coauthors and I apply metabolic scaling theory (MST) to examine scaling behavior and structural patterns of semi-arid conifer forests in Arizona and New Mexico. We conceptualize a linkage to mechanistic drivers of forest assembly that incorporates the effects of low-intensity disturbance, and physiologic and resource limitations as an extension of MST. We use both aerial LiDAR data and field observations to quantify changes in forest structure from the sub-meter to landscape scales. We found: (1) semi-arid forest structure exhibits MST-predicted behaviors regardless of disturbance and that MST can help to quantitatively measure the level of disturbance intensity in a forest, (2) the application of a power law to a forest overstory frequency distribution can help predict understory presence/absence, (3) local indicators of spatial association can help to define first order effects (e.g. topographic changes) and map where recent disturbances (e.g. logging and fire) have altered forest structure. Lastly, we produced a comprehensive set of above-ground biomass and carbon models for five distinct forest types and ten common species of the southwestern US that are meant for use in aerial LiDAR forest inventory projects. This dissertation presents both a conceptual framework and applications for investigating local scales (stands of trees) up to entire ecosystems for diagnosis of current carbon balances, levels of departure from historical norms, and ecological stability. These tools and models will become more important as we prepare our ecosystems for a future characterized by increased climatic variability with an associated increase in frequency and severity of ecological disturbances.

Development of teaching modules for geology and engineering coursework using terrestrial LiDAR scanning systems

NASA Astrophysics Data System (ADS)

Yarbrough, L. D.; Katzenstein, K.

2012-12-01

Exposing students to active and local examples of physical geologic processes is beneficial to the learning process. Students typically respond with interest to examples that use state-of-the-art technologies to investigate local or regional phenomena. For lower cognitive level of learning (e.g. knowledge, comprehension, and application), the use of "close-to-home" examples ensures that students better understand concepts. By providing these examples, the students may already have a familiarity or can easily visit the location. Furthermore, these local and regional examples help students to offer quickly other examples of similar phenomena. Investigation of these examples using normal photographic techniques, as well as a more sophisticated 3-D Light Detection And Ranging (LiDAR) (AKA Terrestrial Laser Scanning or TLS) system, allows students to gain a better understanding of the scale and the mechanics of the geologic processes and hazards. The systems are used for research, teaching and outreach efforts and depending on departmental policies can be accessible to students are various learning levels. TLS systems can yield scans at sub-centimeter resolution and contain surface reflectance of targets. These systems can serve a number of learning goals that are essential for training geoscientists and engineers. While querying the data to answer geotechnical or geomorphologic related questions, students will develop skills using large, spatial databases. The upper cognitive level of learning (e.g. analysis, synthesis, and evaluation) is also promoted by using a subset of the data and correlating the physical geologic process of stream bank erosion and rock slope failures with mathematical and computer models using the scanned data. Students use the examples and laboratory exercises to help build their engineering judgment skills with Earth materials. The students learn not only applications of math and engineering science but also the economic and social implication of designed engineering solutions. These course learning modules were developed for traditional geological engineering courses delivered on campus, for more intensive field work courses and online-based asynchronous course delivery.

The role of vegetation on gully stabilization at a severely degraded landscape: a case study from Calhoun experimental critical zone observatory

NASA Astrophysics Data System (ADS)

Dialynas, Y. G.; Bastola, S.; Bras, R. L.; Noto, L. V.; Istanbulluoglu, E.

2016-12-01

Gully erosion was the primary driver of land degradation in Southern Piedmont, site of the Calhoun Critical Zone Observatory (CCZO), during the cotton farming era. Understanding of underlying erosion processes is essential to develop a model useful in assessing the effectiveness of gully stabilization and soil erosion control. Development of process-based gully erosion models is difficult because observations of the formation and progression of gullies are limited. In this study, analytic formulations of the two dominant gullying processes, namely, plunge pool erosion and slab failure, are utilized to simulate the gullying processes in the 4 km2 Holcombe's Branch watershed. Gully features (e.g., depth and area) automatically extracted from high-resolution LiDAR DEM are used to calibrate parameters of the gully model. The statistics of the spatial extent of simulated gullies are in close agreement with the gullies obtained from the LiDAR map. Simulations initialized with contemporary topography suggest that few gully complexes have the potential to progress further. Several simulations are used to evaluate the effectiveness of various gully treatment measures, such as backfilling of gullies and revegetation, by initializing the model with the historical topographical surface. Simulation results show that in the short-term, the reshaping of the topographical surface by backfilling and compacting gullies is effective in slowing down the growth of gullies (e.g., backfilling decreased the spatial extent of gullies by 20-38% and decreased the average depth by 0.005-8%). Revegetation, however, is a more effective approach to stabilizing gullies which would, otherwise, expand if left barren. Moreover simulations suggest that the gully stabilization effect of revegetation can lead to a 23-70% reduction of gully area and 1.3-45% reduction in the depth of gullies, depending on forest type and management practices.

ISED: Constructing a high-resolution elevation road dataset from massive, low-quality in-situ observations derived from geosocial fitness tracking data.

PubMed

McKenzie, Grant; Janowicz, Krzysztof

2017-01-01

Gaining access to inexpensive, high-resolution, up-to-date, three-dimensional road network data is a top priority beyond research, as such data would fuel applications in industry, governments, and the broader public alike. Road network data are openly available via user-generated content such as OpenStreetMap (OSM) but lack the resolution required for many tasks, e.g., emergency management. More importantly, however, few publicly available data offer information on elevation and slope. For most parts of the world, up-to-date digital elevation products with a resolution of less than 10 meters are a distant dream and, if available, those datasets have to be matched to the road network through an error-prone process. In this paper we present a radically different approach by deriving road network elevation data from massive amounts of in-situ observations extracted from user-contributed data from an online social fitness tracking application. While each individual observation may be of low-quality in terms of resolution and accuracy, taken together they form an accurate, high-resolution, up-to-date, three-dimensional road network that excels where other technologies such as LiDAR fail, e.g., in case of overpasses, overhangs, and so forth. In fact, the 1m spatial resolution dataset created in this research based on 350 million individual 3D location fixes has an RMSE of approximately 3.11m compared to a LiDAR-based ground-truth and can be used to enhance existing road network datasets where individual elevation fixes differ by up to 60m. In contrast, using interpolated data from the National Elevation Dataset (NED) results in 4.75m RMSE compared to the base line. We utilize Linked Data technologies to integrate the proposed high-resolution dataset with OpenStreetMap road geometries without requiring any changes to the OSM data model.

Immunogenicity and Protective Efficacy of the DAR-901 Booster Vaccine in a Murine Model of Tuberculosis

PubMed Central

Lahey, Timothy; Laddy, Dominick; Hill, Krystal; Schaeffer, Jacqueline; Hogg, Alison; Keeble, James; Dagg, Belinda; Ho, Mei Mei; Arbeit, Robert D.; von Reyn, C. Fordham

2016-01-01

Background The development of a novel tuberculosis vaccine is a leading global health priority. SRL172, an inactivated, whole-cell mycobacterial vaccine, was safe, immunogenic and reduced the incidence of culture-confirmed tuberculosis in a phase III trial in HIV-infected and BCG immunized adults in Tanzania. Here we describe the immunogenicity and protective efficacy of DAR-901, a booster vaccine against tuberculosis manufactured from the same seed strain using a new scalable method. Methods We evaluated IFN-γ responses by ELISpot and antibody responses by enzyme linked immunosorbent assay in C57BL/6 and BALB/c mice after three doses of DAR-901. In an aerosol challenge model, we evaluated the protective efficacy of the DAR-901 booster in C57BL/6 mice primed with BCG and boosted with two doses of DAR-901 at 4 dosage levels in comparison with homologous BCG boost. Results DAR-901 vaccination elicited IFN-γ responses to mycobacterial antigen preparations derived from both DAR-901 and Mycobacterium tuberculosis. DAR-901 immunization enhanced antibody responses to DAR-901 but not Mycobacterium tuberculosis lysate or purified protein derivative. Among animals primed with BCG, boosting with DAR-901 at 1 mg provided greater protection against aerosol challenge than a homologous BCG boost (lungs P = 0.036, spleen P = 0.028). Conclusions DAR-901 induces cellular and humoral immunity and boosts protection from M. tuberculosis compared to a homologous BCG boost. PMID:27997597

Characterization and Higher-Order Structure Assessment of an Interchain Cysteine-Based ADC: Impact of Drug Loading and Distribution on the Mechanism of Aggregation.

PubMed

Guo, Jianxin; Kumar, Sandeep; Chipley, Mark; Marcq, Olivier; Gupta, Devansh; Jin, Zhaowei; Tomar, Dheeraj S; Swabowski, Cecily; Smith, Jacquelynn; Starkey, Jason A; Singh, Satish K

2016-03-16

The impact of drug loading and distribution on higher order structure and physical stability of an interchain cysteine-based antibody drug conjugate (ADC) has been studied. An IgG1 mAb was conjugated with a cytotoxic auristatin payload following the reduction of interchain disulfides. The 2-D LC-MS analysis shows that there is a preference for certain isomers within the various drug to antibody ratios (DARs). The physical stability of the unconjugated monoclonal antibody, the ADC, and isolated conjugated species with specific DAR, were compared using calorimetric, thermal, chemical denaturation and molecular modeling techniques, as well as techniques to assess hydrophobicity. The DAR was determined to have a significant impact on the biophysical properties and stability of the ADC. The CH2 domain was significantly perturbed in the DAR6 species, which was attributable to quaternary structural changes as assessed by molecular modeling. At accelerated storage temperatures, the DAR6 rapidly forms higher molecular mass species, whereas the DAR2 and the unconjugated mAb were largely stable. Chemical denaturation study indicates that DAR6 may form multimers while DAR2 and DAR4 primarily exist in monomeric forms in solution at ambient conditions. The physical state differences were correlated with a dramatic increase in the hydrophobicity and a reduction in the surface tension of the DAR6 compared to lower DAR species. Molecular modeling of the various DAR species and their conformers demonstrates that the auristatin-based linker payload directly contributes to the hydrophobicity of the ADC molecule. Higher order structural characterization provides insight into the impact of conjugation on the conformational and colloidal factors that determine the physical stability of cysteine-based ADCs, with implications for process and formulation development.

RIS4E at Kilauea's December 1974 Flow: Lava Flow Texture LiDAR Signatures

NASA Astrophysics Data System (ADS)

Whelley, P.; Garry, W. B.; Scheidt, S. P.; Bleacher, J. E.; Hamilton, C.

2015-12-01

High-resolution point clouds and digital terrain models (DTMs) are used to investigate lava textures on the Big Island of Hawaii. Lava texture (e.g., ´áā and pāhoehoe) depends significantly on eruption conditions, and it is therefore instructive, if accurately determined. In places where field investigations are prohibitive (e.g., on other planets and remote regions of Earth) lava texture must be assessed from remote sensing data. A reliable method for doing so remains elusive. The December 1974 flow from Kilauea, in the Kau desert, presents an excellent field site to develop techniques for identifying lava texture. The eruption is young and the textures are well preserved. We present results comparing properties of lava textures observed in Terrestrial Laser Scanning (TLS) data. The authors collected the TLS data during May 2014 and June 2015 field seasons. Scans are a quantitative representation of what a geologist, or robotic system, sees "on the ground" and provides "ground truth" for airborne or orbital remote sensing analysis by enabling key parameters of lava morphology to be quantified. While individual scans have a heterogeneous point density, multiple scans are merged such that sub-cm lava textures can be quantified. Results indicate that TLS-derived surface roughness (i.e., de-trended RMS roughness) is useful for differentiating lava textures and assists volcanologic interpretations. As many lava types are quite rough, it is not simply roughness that is the most advantageous parameter for differentiating lava textures; rather co-occurrence patterns in surface roughness are used. Gradually forming textures (e.g., pāhoehoe) are elevated in statistics that measure smoothness (e.g., homogeneity) while lava with disrupted crusts (e.g., slabby and platy flow) have more random distributions of roughness (i.e., high entropy). A similar technique will be used to analyze high-resolution DTMs of martian lava flows using High Resolution Imaging Science Experiment DTMs. This work will lead to faster and more reliable volcanic mapping efforts for planetary exploration as well as terrestrial geohazards.

Meteorologically Driven Simulations of Dengue Epidemics in San Juan, PR

PubMed Central

Morin, Cory W.; Monaghan, Andrew J.; Hayden, Mary H.; Barrera, Roberto; Ernst, Kacey

2015-01-01

Meteorological factors influence dengue virus ecology by modulating vector mosquito population dynamics, viral replication, and transmission. Dynamic modeling techniques can be used to examine how interactions among meteorological variables, vectors and the dengue virus influence transmission. We developed a dengue fever simulation model by coupling a dynamic simulation model for Aedes aegypti, the primary mosquito vector for dengue, with a basic epidemiological Susceptible-Exposed-Infectious-Recovered (SEIR) model. Employing a Monte Carlo approach, we simulated dengue transmission during the period of 2010–2013 in San Juan, PR, where dengue fever is endemic. The results of 9600 simulations using varied model parameters were evaluated by statistical comparison (r2) with surveillance data of dengue cases reported to the Centers for Disease Control and Prevention. To identify the most influential parameters associated with dengue virus transmission for each period the top 1% of best-fit model simulations were retained and compared. Using the top simulations, dengue cases were simulated well for 2010 (r2 = 0.90, p = 0.03), 2011 (r2 = 0.83, p = 0.05), and 2012 (r2 = 0.94, p = 0.01); however, simulations were weaker for 2013 (r2 = 0.25, p = 0.25) and the entire four-year period (r2 = 0.44, p = 0.002). Analysis of parameter values from retained simulations revealed that rain dependent container habitats were more prevalent in best-fitting simulations during the wetter 2010 and 2011 years, while human managed (i.e. manually filled) container habitats were more prevalent in best-fitting simulations during the drier 2012 and 2013 years. The simulations further indicate that rainfall strongly modulates the timing of dengue (e.g., epidemics occurred earlier during rainy years) while temperature modulates the annual number of dengue fever cases. Our results suggest that meteorological factors have a time-variable influence on dengue transmission relative to other important environmental and human factors. PMID:26275146

Study on environmental test technology of LiDAR used for vehicle

NASA Astrophysics Data System (ADS)

Wang, Yi; Yang, Jianfeng; Ou, Yong

2018-03-01

With the development of intelligent driving, the LiDAR used for vehicle plays an important role in it, in some extent LiDAR is the key factor of intelligent driving. And environmental adaptability is one critical factor of quality, it relates success or failure of LiDAR. This article discusses about the environment and its effects on LiDAR used for vehicle, it includes analysis of any possible environment that vehicle experiences, and environmental test design.

Post-donation telephonic interview of blood donors providing an insight into delayed adverse reactions: First attempt in India.

PubMed

Tiwari, Aseem K; Aggarwal, Geet; Dara, Ravi C; Arora, Dinesh; Srivastava, Khushboo; Raina, Vimarsh

2017-04-01

Blood donor experiences both immediate adverse reactions (IAR) and delayed adverse reactions (DAR). With limited published data available on the incidence of DAR, a study was conducted to estimate incidence and profile of DAR through telephonic interview. Study was conducted over a 45-day period for consecutive volunteer whole blood donations at tertiary care hospital. Donors were divided into first-time, repeat and regular and were monitored for IAR. They were given written copy of post-donation advice. Donors were contacted telephonically three weeks post-donation and enquired about general wellbeing and specific DAR in accordance with a standard n international (International Society of Blood Transfusion) standard format. Donors participated in the study of which 1.6% donors experienced an IAR. Much larger number reported DAR (10.3% vs.1.6% p<0.0001). Further, DAR was presented as a variegated profile with bruise, painful arms and fatigue being the commonest. DARs were more common in females than males (25% vs. 10.3%, p<0.02). Localized DAR like bruise and painful arms were more common in younger donors (age <50 years) whereas systemic DAR like fatigue was common in older donors (>50 years). First time (12.3%) and repeat donors (13.5%) had similar frequency of DAR but were lower among regular donors (6.7%). DARs are more common than IAR and are of different profile. Post-donation interview has provided an insight into donor experiences and can be used as a valuable tool in donor hemovigilance. Copyright © 2016 Elsevier Ltd. All rights reserved.

In-depth genome characterization of a Brazilian common bean core collection using DArTseq high-density SNP genotyping.

PubMed

Valdisser, Paula A M R; Pereira, Wendell J; Almeida Filho, Jâneo E; Müller, Bárbara S F; Coelho, Gesimária R C; de Menezes, Ivandilson P P; Vianna, João P G; Zucchi, Maria I; Lanna, Anna C; Coelho, Alexandre S G; de Oliveira, Jaison P; Moraes, Alessandra da Cunha; Brondani, Claudio; Vianello, Rosana P

2017-05-30

Common bean is a legume of social and nutritional importance as a food crop, cultivated worldwide especially in developing countries, accounting for an important source of income for small farmers. The availability of the complete sequences of the two common bean genomes has dramatically accelerated and has enabled new experimental strategies to be applied for genetic research. DArTseq has been widely used as a method of SNP genotyping allowing comprehensive genome coverage with genetic applications in common bean breeding programs. Using this technology, 6286 SNPs (1 SNP/86.5 Kbp) were genotyped in genic (43.3%) and non-genic regions (56.7%). Genetic subdivision associated to the common bean gene pools (K = 2) and related to grain types (K = 3 and K = 5) were reported. A total of 83% and 91% of all SNPs were polymorphic within the Andean and Mesoamerican gene pools, respectively, and 26% were able to differentiate the gene pools. Genetic diversity analysis revealed an average H E of 0.442 for the whole collection, 0.102 for Andean and 0.168 for Mesoamerican gene pools (F ST  = 0.747 between gene pools), 0.440 for the group of cultivars and lines, and 0.448 for the group of landrace accessions (F ST  = 0.002 between cultivar/line and landrace groups). The SNP effects were predicted with predominance of impact on non-coding regions (77.8%). SNPs under selection were identified within gene pools comparing landrace and cultivar/line germplasm groups (Andean: 18; Mesoamerican: 69) and between the gene pools (59 SNPs), predominantly on chromosomes 1 and 9. The LD extension estimate corrected for population structure and relatedness (r 2 SV ) was ~ 88 kbp, while for the Andean gene pool was ~ 395 kbp, and for the Mesoamerican was ~ 130 kbp. For common bean, DArTseq provides an efficient and cost-effective strategy of generating SNPs for large-scale genome-wide studies. The DArTseq resulted in an operational panel of 560 polymorphic SNPs in linkage equilibrium, providing high genome coverage. This SNP set could be used in genotyping platforms with many applications, such as population genetics, phylogeny relation between common bean varieties and support to molecular breeding approaches.

Effect of urban design on microclimate and thermal comfort outdoors in warm-humid Dar es Salaam, Tanzania

NASA Astrophysics Data System (ADS)

Yahia, Moohammed Wasim; Johansson, Erik; Thorsson, Sofia; Lindberg, Fredrik; Rasmussen, Maria Isabel

2018-03-01

Due to the complexity of built environment, urban design patterns considerably affect the microclimate and outdoor thermal comfort in a given urban morphology. Variables such as building heights and orientations, spaces between buildings, plot coverage alter solar access, wind speed and direction at street level. To improve microclimate and comfort conditions urban design elements including vegetation and shading devices can be used. In warm-humid Dar es Salaam, the climate consideration in urban design has received little attention although the urban planning authorities try to develop the quality of planning and design. The main aim of this study is to investigate the relationship between urban design, urban microclimate, and outdoor comfort in four built-up areas with different morphologies including low-, medium-, and high-rise buildings. The study mainly concentrates on the warm season but a comparison with the thermal comfort conditions in the cool season is made for one of the areas. Air temperature, wind speed, mean radiant temperature (MRT), and the physiologically equivalent temperature (PET) are simulated using ENVI-met to highlight the strengths and weaknesses of the existing urban design. An analysis of the distribution of MRT in the areas showed that the area with low-rise buildings had the highest frequency of high MRTs and the lowest frequency of low MRTs. The study illustrates that areas with low-rise buildings lead to more stressful urban spaces than areas with high-rise buildings. It is also shown that the use of dense trees helps to enhance the thermal comfort conditions, i.e., reduce heat stress. However, vegetation might negatively affect the wind ventilation. Nevertheless, a sensitivity analysis shows that the provision of shade is a more efficient way to reduce PET than increases in wind speed, given the prevailing sun and wind conditions in Dar es Salaam. To mitigate heat stress in Dar es Salaam, a set of recommendations and guidelines on how to develop the existing situation from microclimate and thermal comfort perspectives is outlined. Such recommendations will help architects and urban designers to increase the quality of the outdoor environment and demonstrate the need to create better urban spaces in harmony with microclimate and thermal comfort.

Non-Trivial Feature Derivation for Intensifying Feature Detection Using LIDAR Datasets Through Allometric Aggregation Data Analysis Applying Diffused Hierarchical Clustering for Discriminating Agricultural Land Cover in Portions of Northern Mindanao, Philippines

NASA Astrophysics Data System (ADS)

Villar, Ricardo G.; Pelayo, Jigg L.; Mozo, Ray Mari N.; Salig, James B., Jr.; Bantugan, Jojemar

2016-06-01

Leaning on the derived results conducted by Central Mindanao University Phil-LiDAR 2.B.11 Image Processing Component, the paper attempts to provides the application of the Light Detection and Ranging (LiDAR) derived products in arriving quality Landcover classification considering the theoretical approach of data analysis principles to minimize the common problems in image classification. These are misclassification of objects and the non-distinguishable interpretation of pixelated features that results to confusion of class objects due to their closely-related spectral resemblance, unbalance saturation of RGB information is a challenged at the same time. Only low density LiDAR point cloud data is exploited in the research denotes as 2 pts/m2 of accuracy which bring forth essential derived information such as textures and matrices (number of returns, intensity textures, nDSM, etc.) in the intention of pursuing the conditions for selection characteristic. A novel approach that takes gain of the idea of object-based image analysis and the principle of allometric relation of two or more observables which are aggregated for each acquisition of datasets for establishing a proportionality function for data-partioning. In separating two or more data sets in distinct regions in a feature space of distributions, non-trivial computations for fitting distribution were employed to formulate the ideal hyperplane. Achieving the distribution computations, allometric relations were evaluated and match with the necessary rotation, scaling and transformation techniques to find applicable border conditions. Thus, a customized hybrid feature was developed and embedded in every object class feature to be used as classifier with employed hierarchical clustering strategy for cross-examining and filtering features. This features are boost using machine learning algorithms as trainable sets of information for a more competent feature detection. The product classification in this investigation was compared to a classification based on conventional object-oriented approach promoting straight-forward functionalities of the software eCognition. A compelling rise of efficiency in the overall accuracy (74.4% to 93.4%) and kappa index of agreement (70.5% to 91.7%) is noticeable based on the initial process. Nevertheless, having low-dense LiDAR dataset could be enough in generating exponential increase of performance in accuracy.

Effect of urban design on microclimate and thermal comfort outdoors in warm-humid Dar es Salaam, Tanzania.

PubMed

Yahia, Moohammed Wasim; Johansson, Erik; Thorsson, Sofia; Lindberg, Fredrik; Rasmussen, Maria Isabel

2018-03-01

Due to the complexity of built environment, urban design patterns considerably affect the microclimate and outdoor thermal comfort in a given urban morphology. Variables such as building heights and orientations, spaces between buildings, plot coverage alter solar access, wind speed and direction at street level. To improve microclimate and comfort conditions urban design elements including vegetation and shading devices can be used. In warm-humid Dar es Salaam, the climate consideration in urban design has received little attention although the urban planning authorities try to develop the quality of planning and design. The main aim of this study is to investigate the relationship between urban design, urban microclimate, and outdoor comfort in four built-up areas with different morphologies including low-, medium-, and high-rise buildings. The study mainly concentrates on the warm season but a comparison with the thermal comfort conditions in the cool season is made for one of the areas. Air temperature, wind speed, mean radiant temperature (MRT), and the physiologically equivalent temperature (PET) are simulated using ENVI-met to highlight the strengths and weaknesses of the existing urban design. An analysis of the distribution of MRT in the areas showed that the area with low-rise buildings had the highest frequency of high MRTs and the lowest frequency of low MRTs. The study illustrates that areas with low-rise buildings lead to more stressful urban spaces than areas with high-rise buildings. It is also shown that the use of dense trees helps to enhance the thermal comfort conditions, i.e., reduce heat stress. However, vegetation might negatively affect the wind ventilation. Nevertheless, a sensitivity analysis shows that the provision of shade is a more efficient way to reduce PET than increases in wind speed, given the prevailing sun and wind conditions in Dar es Salaam. To mitigate heat stress in Dar es Salaam, a set of recommendations and guidelines on how to develop the existing situation from microclimate and thermal comfort perspectives is outlined. Such recommendations will help architects and urban designers to increase the quality of the outdoor environment and demonstrate the need to create better urban spaces in harmony with microclimate and thermal comfort.

Retrieval of effective leaf area index (LAIe) and leaf area density (LAD) profile at individual tree level using high density multi-return airborne LiDAR

NASA Astrophysics Data System (ADS)

Lin, Yi; West, Geoff

2016-08-01

As an important canopy structure indicator, leaf area index (LAI) proved to be of considerable implications for forest ecosystem and ecological studies, and efficient techniques for accurate LAI acquisitions have long been highlighted. Airborne light detection and ranging (LiDAR), often termed as airborne laser scanning (ALS), once was extensively investigated for this task but showed limited performance due to its low sampling density. Now, ALS systems exhibit more competing capacities such as high density and multi-return sampling, and hence, people began to ask the questions like-;can ALS now work better on the task of LAI prediction?; As a re-examination, this study investigated the feasibility of LAI retrievals at the individual tree level based on high density and multi-return ALS, by directly considering the vertical distributions of laser points lying within each tree crown instead of by proposing feature variables such as quantiles involving laser point distribution modes at the plot level. The examination was operated in the case of four tree species (i.e. Picea abies, Pinus sylvestris, Populus tremula and Quercus robur) in a mixed forest, with their LAI-related reference data collected by using static terrestrial laser scanning (TLS). In light of the differences between ALS- and TLS-based LAI characterizations, the methods of voxelization of 3D scattered laser points, effective LAI (LAIe) that does not distinguish branches from canopies and unified cumulative LAI (ucLAI) that is often used to characterize the vertical profiles of crown leaf area densities (LADs) was used; then, the relationships between the ALS- and TLS-derived LAIes were determined, and so did ucLAIs. Tests indicated that the tree-level LAIes for the four tree species can be estimated based on the used airborne LiDAR (R2 = 0.07, 0.26, 0.43 and 0.21, respectively) and their ucLAIs can also be derived. Overall, this study has validated the usage of the contemporary high density multi-return airborne LiDARs for LAIe and LAD profile retrievals at the individual tree level, and the contribution are of high potential for advancing forest ecosystem modeling and ecological understanding.

An Algorithm to Identify and Localize Suitable Dock Locations from 3-D LiDAR Scans

DTIC Science & Technology

2013-05-10

Locations from 3-D LiDAR Scans 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Graves, Mitchell Robert 5d. PROJECT NUMBER...Ranging ( LiDAR ) scans. A LiDAR sensor is a sensor that collects range images from a rotating array of vertically aligned lasers. Our solution leverages...Algorithm, Dock, Locations, Point Clouds, LiDAR , Identify 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a

Health assessment of natural radioactivity and radon exhalation rate in granites used as building materials in Lebanon.

PubMed

Kobeissi, M A; El-Samad, O; Rachidi, I

2013-03-01

Measurements of specific activities (Bq kg(-1)) of gamma-emissions from radioactive nuclides, (238)U, (226)Ra, (214)Bi, (232)Th, (212)Pb and (40)K, contained in 28 granite types, used as building materials in indoors in Lebanon, were performed on the powdered granites. The concentration of the nuclides, (226)Ra, (232)Th and (40)K, in the granites varied from below detection level (BDL) to 494 Bq kg(-1), BDL to 157.2 Bq kg(-1) and BDL to 1776 Bq kg(-1), respectively. (226)Ra concentration equivalents, C(Raeq), were obtained and ranged between 37 and 591 Bq kg(-1), with certain values above the allowed limit of 370 Bq kg(-1). Calculated annual gamma-absorbed dose in air, D(aR), varied from 17.7 to 274.5 (nGy h(-1)). Annual effective dose, E (mSv y(-1)), of gamma radiations related to the studied granites and absorbed by the inhabitants was evaluated. E (mSv y(-1)) ranged from 0.09 to 1.35 mSv y(-1). Some granite types produced E above the allowed limit of 1 mSv y(-1) set by ICRP. Values of (222)Rn mass exhalation rate, E(M) (mBq kg(-1)h(-1))(,) in granite powder were obtained using the CR-39 detector technique. Diffusion factors, f, in 23 granite types were calculated with f ranging between (0.1 ± 0.02)×10(-2) and (6.6 ± 1.01)×10(-2).

LiDAR utility for natural resource managers

Treesearch

Andrew Thomas Hudak; Jeffrey Scott Evans; Alistair Mattthew Stuart Smith

2009-01-01

Applications of LiDAR remote sensing are exploding, while moving from the research to the operational realm. Increasingly, natural resource managers are recognizing the tremendous utility of LiDAR-derived information to make improved decisions. This review provides a cross-section of studies, many recent, that demonstrate the relevance of LiDAR across a suite of...

LiDAR-IMU Time Delay Calibration Based on Iterative Closest Point and Iterated Sigma Point Kalman Filter.

PubMed

Liu, Wanli

2017-03-08

The time delay calibration between Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs) is an essential prerequisite for its applications. However, the correspondences between LiDAR and IMU measurements are usually unknown, and thus cannot be computed directly for the time delay calibration. In order to solve the problem of LiDAR-IMU time delay calibration, this paper presents a fusion method based on iterative closest point (ICP) and iterated sigma point Kalman filter (ISPKF), which combines the advantages of ICP and ISPKF. The ICP algorithm can precisely determine the unknown transformation between LiDAR-IMU; and the ISPKF algorithm can optimally estimate the time delay calibration parameters. First of all, the coordinate transformation from the LiDAR frame to the IMU frame is realized. Second, the measurement model and time delay error model of LiDAR and IMU are established. Third, the methodology of the ICP and ISPKF procedure is presented for LiDAR-IMU time delay calibration. Experimental results are presented that validate the proposed method and demonstrate the time delay error can be accurately calibrated.

Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations.

PubMed

Huang, Rongyong; Zheng, Shunyi; Hu, Kun

2018-06-01

Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4⁻1/2 (0.17⁻0.27 m) and 1/8⁻1/4 (0.10⁻0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data.

Retrieving aboveground biomass of wetland Phragmites australis (common reed) using a combination of airborne discrete-return LiDAR and hyperspectral data

NASA Astrophysics Data System (ADS)

Luo, Shezhou; Wang, Cheng; Xi, Xiaohuan; Pan, Feifei; Qian, Mingjie; Peng, Dailiang; Nie, Sheng; Qin, Haiming; Lin, Yi

2017-06-01

Wetland biomass is essential for monitoring the stability and productivity of wetland ecosystems. Conventional field methods to measure or estimate wetland biomass are accurate and reliable, but expensive, time consuming and labor intensive. This research explored the potential for estimating wetland reed biomass using a combination of airborne discrete-return Light Detection and Ranging (LiDAR) and hyperspectral data. To derive the optimal predictor variables of reed biomass, a range of LiDAR and hyperspectral metrics at different spatial scales were regressed against the field-observed biomasses. The results showed that the LiDAR-derived H_p99 (99th percentile of the LiDAR height) and hyperspectral-calculated modified soil-adjusted vegetation index (MSAVI) were the best metrics for estimating reed biomass using the single regression model. Although the LiDAR data yielded a higher estimation accuracy compared to the hyperspectral data, the combination of LiDAR and hyperspectral data produced a more accurate prediction model for reed biomass (R2 = 0.648, RMSE = 167.546 g/m2, RMSEr = 20.71%) than LiDAR data alone. Thus, combining LiDAR data with hyperspectral data has a great potential for improving the accuracy of aboveground biomass estimation.

A General-purpose Framework for Parallel Processing of Large-scale LiDAR Data

NASA Astrophysics Data System (ADS)

Li, Z.; Hodgson, M.; Li, W.

2016-12-01

Light detection and ranging (LiDAR) technologies have proven efficiency to quickly obtain very detailed Earth surface data for a large spatial extent. Such data is important for scientific discoveries such as Earth and ecological sciences and natural disasters and environmental applications. However, handling LiDAR data poses grand geoprocessing challenges due to data intensity and computational intensity. Previous studies received notable success on parallel processing of LiDAR data to these challenges. However, these studies either relied on high performance computers and specialized hardware (GPUs) or focused mostly on finding customized solutions for some specific algorithms. We developed a general-purpose scalable framework coupled with sophisticated data decomposition and parallelization strategy to efficiently handle big LiDAR data. Specifically, 1) a tile-based spatial index is proposed to manage big LiDAR data in the scalable and fault-tolerable Hadoop distributed file system, 2) two spatial decomposition techniques are developed to enable efficient parallelization of different types of LiDAR processing tasks, and 3) by coupling existing LiDAR processing tools with Hadoop, this framework is able to conduct a variety of LiDAR data processing tasks in parallel in a highly scalable distributed computing environment. The performance and scalability of the framework is evaluated with a series of experiments conducted on a real LiDAR dataset using a proof-of-concept prototype system. The results show that the proposed framework 1) is able to handle massive LiDAR data more efficiently than standalone tools; and 2) provides almost linear scalability in terms of either increased workload (data volume) or increased computing nodes with both spatial decomposition strategies. We believe that the proposed framework provides valuable references on developing a collaborative cyberinfrastructure for processing big earth science data in a highly scalable environment.

Applicability of Aerial Green LiDAR to a Large River in the Western United States

NASA Astrophysics Data System (ADS)

Conner, J. T.; Welcker, C. W.; Cooper, C.; Faux, R.; Butler, M.; Nayegandhi, A.

2013-12-01

In October 2012, aerial green LiDAR data were collected in the Snake River (within Idaho and Oregon) to test this emerging technology in a large river with poor water clarity. Six study areas (total of 30 river miles spread out over 250 river miles) were chosen to represent a variety of depths, channel types, and surface conditions to test the accuracy, depth penetration, data density of aerial green LiDAR. These characteristics along with cost and speed of acquisition were compared to other bathymetric survey techniques including rod surveys (total station and RTK-GPS), single-beam sonar, and multibeam echosounder (MBES). The green LiDAR system typically measured returns from the riverbed through 1-2 meters of water, which was less than one Secchi depth. However, in areas with steep banks or aquatic macrophytes, LiDAR returns from the riverbed were less frequent or non-existent. In areas of good return density, depths measured from green LiDAR data corresponded well with previously collected data sets from traditional bathymetric survey techniques. In such areas, the green LiDAR point density was much higher than both rod and single beam sonar surveys, yet lower than MBES. The green LiDAR survey was also collected more efficiently than all other methods. In the Snake River, green LiDAR does not provide a method to map the entire riverbed as it only receives bottom returns in shallow water, typically at the channel margins. However, green LiDAR does provide survey data that is an excellent complement to MBES, which is more effective at surveying the deeper portions of the channel. In some cases, the green LiDAR was able to provide data in areas that the MBES could not, often due to issues with navigating the survey boat in shallow water. Even where both MBES and green LiDAR mapped the river bottom, green LiDAR often provides more accurate data through a better angle of incidence and less shadowing than the MBES survey. For one MBES survey in 2013, the green LiDAR data was used to create a map of shallow hazards to be avoided during the survey for the safety of the crew and the MBES equipment. While green LiDAR does not provide a single solution to all large river surveying problems, when combined with MBES it allows for more complete, more efficient, and safer surveys in a large river.

Using LIDAR and Quickbird Data to Model Plant Production and Quantify Uncertainties Associated with Wetland Detection and Land Cover Generalizations

NASA Technical Reports Server (NTRS)

Cook, Bruce D.; Bolstad, Paul V.; Naesset, Erik; Anderson, Ryan S.; Garrigues, Sebastian; Morisette, Jeffrey T.; Nickeson, Jaime; Davis, Kenneth J.

2009-01-01

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the MOderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

A multiscale curvature algorithm for classifying discrete return LiDAR in forested environments

Treesearch

Jeffrey S. Evans; Andrew T. Hudak

2007-01-01

One prerequisite to the use of light detection and ranging (LiDAR) across disciplines is differentiating ground from nonground returns. The objective was to automatically and objectively classify points within unclassified LiDAR point clouds, with few model parameters and minimal postprocessing. Presented is an automated method for classifying LiDAR returns as ground...

LiDAR - An emerging tool for geological applications

USGS Publications Warehouse

Stoker, Jason M.

2012-01-01

Over the past five to ten years the use and applicability of light detection and ranging (LiDAR) technology has increased dramatically. As a result, more and more LiDAR data now are being collected across the country for a wide range of applications, and LiDAR currently is the technology of choice for high resolution terrain model creation, 3-D city and infrastructure modeling, forestry, and a wide range of scientific applications. LiDAR is a key technology for geological applications both within and outside the U.S. Geological Survey, and efforts are underway to try to collect high resolution LiDAR data for the entire United States (https://pubs.usgs.gov/fs/2012/3089/pdf/fs2012-3089.pdf).

LiDAR-based TWI and terrain attributes in improving parametric predictor for tree growth in southeast Finland

NASA Astrophysics Data System (ADS)

Mohamedou, Cheikh; Tokola, Timo; Eerikäinen, Kalle

2017-10-01

The effect of soil moisture content on vegetation and therefore on growth is well known. Information about the growth of forest stands is key in forest planning and management, and is the concern of various stakeholders. One way to assess moisture content and its impacts on forest growth is to apply the Topographic Wetness Index (TWI) and the derived terrain attributes from the Digital Terrain Model (DTM). The TWI is an important terrain attribute, used in various ecological studies. In the current study, a total of 9987 tally trees within 197 sample plots in southeastern Finland and LiDAR (Light Detection and Ranging) -based TWI were selected to examine: 1) the effect of cell resolutions and focal statistics of neighborhood cells of DTM, on tree diameter increment, and 2) possibilities to improve the prediction accuracy of an existing single-tree growth model using the terrain attributes and TWI with the combined effects of three characteristics (i.e., cell resolutions, neighborhood cells and terrain attributes). The results suggest that the TWI with terrain attributes improved the growth estimation significantly, and within different site types the Root Mean Square Errors (RMSE) were lowered substantially. The best results were obtained for birch trees. The higher resolution of the DTM and the lower focal neighborhood cells were found to be the best alternative in computing the TWI.

[Drug-Coated Balloons and Stents for the Treatment of Femoro-Popliteal Lesions].

PubMed

Ito, Wulf D

2017-08-01

Medikamenten-beschichtete Ballons bei femoro-poplitealen Läsionen  Medikamenten-beschichtete Ballons (DCB) führen in der Behandlung von femoro-poplitealen Läsionen zu besseren Offenheitsraten als die einfache Ballondilatation und zu ähnlichen bis besseren Offenheitsraten als die Stentimplantation. Vorteil ist die Vermeidung von permanentem Fremdmaterial in Regionen, die einer ständigen mechanischen Beanspruchung unterworfen sind und die Möglichkeit, die Prozedur an derselben Stelle wiederholen zu können bzw. chirurgische Zugangswege offenzuhalten. Bei Auftreten von Dissektionen oder einem Recoil bietet sich die fokale Implantation möglichst kurzer Stents in den betroffenen Segmenten an. Die primäre Implantation Medikamenten-beschichteter Stents zeigt darüber hinaus keinen weiteren Vorteil und ist auf längere Sicht mit den Nachteilen der Implantation von Fremdmaterial in Bewegungssegmenten behaftet. Nicht medikamentöse und medikamentöse Begleittherapie  Die Kombination aus interventioneller Behandlung und supervidiertem Gehtraining zeigt die besten Erfolgsaussichten einer dauerhaften Verbesserung der Gehstrecke bei Patienten mit femoro-poplitealen Läsionen und ist einer alleinigen interventionellen Behandlung oder einem alleinigen Gehtraining überlegen. Darüber hinaus werden aktuell große randomisierte, kontrollierte Studien durchgeführt, die den Einfluss niedrig dosierter direkter Antikoagulanzien auf die kardiovaskuläre Komplikationsrate nach Intervention untersuchen. Die Ergebnisse dieser Studien werden Aufschluss geben über die optimale antithrombotische Therapie nach Intervention im femoro-poplitealen Stromgebiet.

A tool for assessing ecological status of forest ecosystem

NASA Astrophysics Data System (ADS)

Rahman Kassim, Abd; Afizzul Misman, Muhammad; Azahari Faidi, Mohd; Omar, Hamdan

2016-06-01

Managers and policy makers are beginning to appreciate the value of ecological monitoring of artificially regenerated forest especially in urban areas. With the advent of more advance technology in precision forestry, high resolution remotely sensed data e.g. hyperspectral and LiDAR are becoming available for rapid and precise assessment of the forest condition. An assessment of ecological status of forest ecosystem was developed and tested using FRIM campus forest stand. The forest consisted of three major blocks; the old growth artificially regenerated native species forests, naturally regenerated forest and recent planted forest for commercial timber and other forest products. Our aim is to assess the ecological status and its proximity to the mature old growth artificially regenerated stand. We used airborne LiDAR, orthophoto and thirty field sampling quadrats of 20x20m for ground verification. The parameter assessments were grouped into four broad categories: a. forest community level-composition, structures, function; landscape structures-road network and forest edges. A metric of parameters and rating criteria was introduced as indicators of the forest ecological status. We applied multi-criteria assessment to categorize the ecological status of the forest stand. The paper demonstrates the application of the assessment approach using FRIM campus forest as its first case study. Its potential application to both artificially and naturally regenerated forest in the variety of Malaysian landscape is discussed

Coupling fine-scale root and canopy structure using ground-based remote sensing

DOE PAGES

Hardiman, Brady S.; Gough, Christopher M.; Butnor, John R.; ...

2017-02-21

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatialmore » scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less

Coupling fine-scale root and canopy structure using ground-based remote sensing

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

Hardiman, Brady S.; Gough, Christopher M.; Butnor, John R.

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatialmore » scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less

An Epidemiological Approach to Terrorism

DTIC Science & Technology

2006-03-01

poliomyelitis. Joyner and Rogers (2001) and Aylward et al. (1999) discuss this effort and the particular characteristics of the poliovirus that render it a...R0, σ, and R Within an epidemic or endemic SIR (MSEIR, or SEIR) model, R0, the basic reproduction number, is the first threshold number to consider...R/N) R0 Basic reproduction number (or rate) σ Contact number R Replacement number t Time, an independent variable β Average number of adequate

Estimating the vegetation canopy height using micro-pulse photon-counting LiDAR data.

PubMed

Nie, Sheng; Wang, Cheng; Xi, Xiaohuan; Luo, Shezhou; Li, Guoyuan; Tian, Jinyan; Wang, Hongtao

2018-05-14

The upcoming space-borne LiDAR satellite Ice, Cloud and land Elevation Satellite-2 (ICESat-2) is scheduled to launch in 2018. Different from the waveform LiDAR system onboard the ICESat, ICESat-2 will use a micro-pulse photon-counting LiDAR system. Thus new data processing algorithms are required to retrieve vegetation canopy height from photon-counting LiDAR data. The objective of this paper is to develop and validate an automated approach for better estimating vegetation canopy height. The new proposed method consists of three key steps: 1) filtering out the noise photons by an effective noise removal algorithm based on localized statistical analysis; 2) separating ground returns from canopy returns using an iterative photon classification algorithm, and then determining ground surface; 3) generating canopy-top surface and calculating vegetation canopy height based on canopy-top and ground surfaces. This automatic vegetation height estimation approach was tested to the simulated ICESat-2 data produced from Sigma Space LiDAR data and Multiple Altimeter Beam Experimental LiDAR (MABEL) data, and the retrieved vegetation canopy heights were validated by canopy height models (CHMs) derived from airborne discrete-return LiDAR data. Results indicated that the estimated vegetation canopy heights have a relatively strong correlation with the reference vegetation heights derived from airborne discrete-return LiDAR data (R 2 and RMSE values ranging from 0.639 to 0.810 and 4.08 m to 4.56 m respectively). This means our new proposed approach is appropriate for retrieving vegetation canopy height from micro-pulse photon-counting LiDAR data.

Remote sensing of Sonoran Desert vegetation structure and phenology with ground-based LiDAR

USGS Publications Warehouse

Sankey, Joel B.; Munson, Seth M.; Webb, Robert H.; Wallace, Cynthia S.A.; Duran, Cesar M.

2015-01-01

Long-term vegetation monitoring efforts have become increasingly important for understanding ecosystem response to global change. Many traditional methods for monitoring can be infrequent and limited in scope. Ground-based LiDAR is one remote sensing method that offers a clear advancement to monitor vegetation dynamics at high spatial and temporal resolution. We determined the effectiveness of LiDAR to detect intra-annual variability in vegetation structure at a long-term Sonoran Desert monitoring plot dominated by cacti, deciduous and evergreen shrubs. Monthly repeat LiDAR scans of perennial plant canopies over the course of one year had high precision. LiDAR measurements of canopy height and area were accurate with respect to total station survey measurements of individual plants. We found an increase in the number of LiDAR vegetation returns following the wet North American Monsoon season. This intra-annual variability in vegetation structure detected by LiDAR was attributable to a drought deciduous shrub Ambrosia deltoidea, whereas the evergreen shrub Larrea tridentata and cactus Opuntia engelmannii had low variability. Benefits of using LiDAR over traditional methods to census desert plants are more rapid, consistent, and cost-effective data acquisition in a high-resolution, 3-dimensional context. We conclude that repeat LiDAR measurements can be an effective method for documenting ecosystem response to desert climatology and drought over short time intervals and at detailed-local spatial scale.

Temporal transferability of LiDAR-based imputation of forest structure attributes

Treesearch

Patrick A. Fekety; Michael J. Falkowski; Andrew T. Hudak

2015-01-01

Forest inventory and planning decisions are frequently informed by LiDAR data. Repeated LiDAR acquisitions offer an opportunity to update forest inventories and potentially improve forest inventory estimates through time. We leveraged repeated LiDAR and ground measures for a study area in northern Idaho, U.S.A., to predict (via imputation) - across both space and time-...

Relationship between LiDAR-derived forest canopy height and Landsat images

Treesearch

Cristina Pascual; Antonio Garcia-Abril; Warren B. Cohen; Susana Martin-Fernandez

2010-01-01

The mean and standard deviation (SD) of light detection and ranging (LiDAR)-derived canopy height are related to forest structure. However, LiDAR data typically cover a limited area and have a high economic cost compared with satellite optical imagery. Optical images may be required to extrapolate LiDAR height measurements across a broad landscape. Different spectral...

LiDAR-IMU Time Delay Calibration Based on Iterative Closest Point and Iterated Sigma Point Kalman Filter

PubMed Central

Liu, Wanli

2017-01-01

The time delay calibration between Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs) is an essential prerequisite for its applications. However, the correspondences between LiDAR and IMU measurements are usually unknown, and thus cannot be computed directly for the time delay calibration. In order to solve the problem of LiDAR-IMU time delay calibration, this paper presents a fusion method based on iterative closest point (ICP) and iterated sigma point Kalman filter (ISPKF), which combines the advantages of ICP and ISPKF. The ICP algorithm can precisely determine the unknown transformation between LiDAR-IMU; and the ISPKF algorithm can optimally estimate the time delay calibration parameters. First of all, the coordinate transformation from the LiDAR frame to the IMU frame is realized. Second, the measurement model and time delay error model of LiDAR and IMU are established. Third, the methodology of the ICP and ISPKF procedure is presented for LiDAR-IMU time delay calibration. Experimental results are presented that validate the proposed method and demonstrate the time delay error can be accurately calibrated. PMID:28282897

Automation of lidar-based hydrologic feature extraction workflows using GIS

NASA Astrophysics Data System (ADS)

Borlongan, Noel Jerome B.; de la Cruz, Roel M.; Olfindo, Nestor T.; Perez, Anjillyn Mae C.

2016-10-01

With the advent of LiDAR technology, higher resolution datasets become available for use in different remote sensing and GIS applications. One significant application of LiDAR datasets in the Philippines is in resource features extraction. Feature extraction using LiDAR datasets require complex and repetitive workflows which can take a lot of time for researchers through manual execution and supervision. The Development of the Philippine Hydrologic Dataset for Watersheds from LiDAR Surveys (PHD), a project under the Nationwide Detailed Resources Assessment Using LiDAR (Phil-LiDAR 2) program, created a set of scripts, the PHD Toolkit, to automate its processes and workflows necessary for hydrologic features extraction specifically Streams and Drainages, Irrigation Network, and Inland Wetlands, using LiDAR Datasets. These scripts are created in Python and can be added in the ArcGIS® environment as a toolbox. The toolkit is currently being used as an aid for the researchers in hydrologic feature extraction by simplifying the workflows, eliminating human errors when providing the inputs, and providing quick and easy-to-use tools for repetitive tasks. This paper discusses the actual implementation of different workflows developed by Phil-LiDAR 2 Project 4 in Streams, Irrigation Network and Inland Wetlands extraction.

Improving Measurement of Forest Structural Parameters by Co-Registering of High Resolution Aerial Imagery and Low Density LiDAR Data

PubMed Central

Huang, Huabing; Gong, Peng; Cheng, Xiao; Clinton, Nick; Li, Zengyuan

2009-01-01

Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to generate a DEM (Digital Elevation Model) and a CHM (Canopy Height Model) from LiDAR data. The LiDAR camera image is matched to the aerial image with an automated keypoints search algorithm. As a result, a high registration accuracy of 0.5 pixels was obtained. A local maximum filter, watershed segmentation, and object-oriented image segmentation are used to obtain tree height and crown width. Results indicate that the camera data collected by the integrated LiDAR system plays an important role in registration with aerial imagery. The synthesis with aerial imagery increases the accuracy of forest structural parameter extraction when compared to only using the low density LiDAR data. PMID:22573971

Validating LiDAR Derived Estimates of Canopy Height, Structure and Fractional Cover in Riparian Areas: A Comparison of Leaf-on and Leaf-off LiDAR Data

NASA Astrophysics Data System (ADS)

Wasser, L. A.; Chasmer, L. E.; Taylor, A.; Day, R.

2010-12-01

Characterization of riparian buffers is integral to understanding the landscape scale impacts of disturbance on wildlife and aquatic ecosystems. Riparian buffers may be characterized using in situ plot sampling or via high resolution remote sensing. Field measurements are time-consuming and may not cover a broad range of ecosystem types. Further, spectral remote sensing methods introduce a compromise between spatial resolution (grain) and area extent. Airborne LiDAR can be used to continuously map and characterize riparian vegetation structure and composition due to the three-dimensional reflectance of laser pulses within and below the canopy, understory and at the ground surface. The distance between reflections (or ‘returns’) allows for detection of narrow buffer corridors at the landscape scale. There is a need to compare leaf-off and leaf-on surveyed LiDAR data with in situ measurements to assess accuracy in landscape scale analysis. These comparisons are particularly important considering increased availability of leaf-off surveyed LiDAR datasets. And given this increased availability, differences between leaf-on and leaf-off derived LiDAR metrics are largely unknown for riparian vegetation of varying composition and structure. This study compares the effectiveness of leaf-on and leaf-off LiDAR in characterizing riparian buffers of varying structure and composition as compared to field measurements. Field measurements were used to validate LiDAR derived metrics. Vegetation height, canopy cover, density and overstory and understory species composition were recorded in 80 random plots of varying vegetation type, density and structure within a Pennsylvania watershed (-77.841, 40.818). Plot data were compared with LiDAR data collected during leaf on and leaf off conditions to determine 1) accuracy of LiDAR derived metrics compared to field measures and 2) differences between leaf-on and leaf-off LiDAR metrics. Results illustrate that differences exist between metrics derived from leaf on and leaf-off surveyed LiDAR. There is greater variability between the two datasets within taller deciduous and mixed (conifer and deciduous) vegetation compared to shorter deciduous and mixed vegetation. Differences decrease as stand density increases for both mixed and deciduous forests. LiDAR derived canopy height is more sensitive to understory vegetation as stand density decreases making measurement of understory vegetation in the field important in the validation process. Finally, while leaf-on LiDAR is often preferred for vegetation analysis, results suggest that leaf-off LiDAR may be sufficient to categorize vegetation into height classes to be used for landscape scale habitat models.

Three-dimensional canopy fuel loading predicted using upward and downward sensing LiDAR systems

Treesearch

Nicholas S. Skowronski; Kenneth L. Clark; Matthew Duveneck; John. Hom

2011-01-01

We calibrated upward sensing profiling and downward sensing scanning LiDAR systems to estimates of canopy fuel loading developed from field plots and allometric equations, and then used the LiDAR datasets to predict canopy bulk density (CBD) and crown fuel weight (CFW) in wildfire prone stands in the New Jersey Pinelands. LiDAR-derived height profiles were also...

Demystifying LiDAR technologies for temperate rainforest in the Pacific Northwest

Treesearch

Rhonda Mazza; Demetrios Gatziolis

2013-01-01

Light detection and ranging (LiDAR), also known as airborne laser scanning, is a rapidly emerging technology for remote sensing. Used to help map, monitor, and assess natural resources, LiDAR data were first embraced by forestry professionals in Scandinavia as a tool for conducting forest inventories in the mid to late 1990s. Thus early LiDAR theory and applications...

Remote sensing based detection of forested wetlands: An evaluation of LiDAR, aerial imagery, and their data fusion

NASA Astrophysics Data System (ADS)

Suiter, Ashley Elizabeth

Multi-spectral imagery provides a robust and low-cost dataset for assessing wetland extent and quality over broad regions and is frequently used for wetland inventories. However in forested wetlands, hydrology is obscured by tree canopy making it difficult to detect with multi-spectral imagery alone. Because of this, classification of forested wetlands often includes greater errors than that of other wetlands types. Elevation and terrain derivatives have been shown to be useful for modelling wetland hydrology. But, few studies have addressed the use of LiDAR intensity data detecting hydrology in forested wetlands. Due the tendency of LiDAR signal to be attenuated by water, this research proposed the fusion of LiDAR intensity data with LiDAR elevation, terrain data, and aerial imagery, for the detection of forested wetland hydrology. We examined the utility of LiDAR intensity data and determined whether the fusion of Lidar derived data with multispectral imagery increased the accuracy of forested wetland classification compared with a classification performed with only multi-spectral image. Four classifications were performed: Classification A -- All Imagery, Classification B -- All LiDAR, Classification C -- LiDAR without Intensity, and Classification D -- Fusion of All Data. These classifications were performed using random forest and each resulted in a 3-foot resolution thematic raster of forested upland and forested wetland locations in Vermilion County, Illinois. The accuracies of these classifications were compared using Kappa Coefficient of Agreement. Importance statistics produced within the random forest classifier were evaluated in order to understand the contribution of individual datasets. Classification D, which used the fusion of LiDAR and multi-spectral imagery as input variables, had moderate to strong agreement between reference data and classification results. It was found that Classification A performed using all the LiDAR data and its derivatives (intensity, elevation, slope, aspect, curvatures, and Topographic Wetness Index) was the most accurate classification with Kappa: 78.04%, indicating moderate to strong agreement. However, Classification C, performed with LiDAR derivative without intensity data had less agreement than would be expected by chance, indicating that LiDAR contributed significantly to the accuracy of Classification B.

A DArT marker genetic map of perennial ryegrass (Lolium perenne L.) integrated with detailed comparative mapping information; comparison with existing DArT marker genetic maps of Lolium perenne, L. multiflorum and Festuca pratensis.

PubMed

King, Julie; Thomas, Ann; James, Caron; King, Ian; Armstead, Ian

2013-07-03

Ryegrasses and fescues (genera, Lolium and Festuca) are species of forage and turf grasses which are used widely in agricultural and amenity situations. They are classified within the sub-family Pooideae and so are closely related to Brachypodium distachyon, wheat, barley, rye and oats. Recently, a DArT array has been developed which can be used in generating marker and mapping information for ryegrasses and fescues. This represents a potential common marker set for ryegrass and fescue researchers which can be linked through to comparative genomic information for the grasses. A F2 perennial ryegrass genetic map was developed consisting of 7 linkage groups defined by 1316 markers and deriving a total map length of 683 cM. The marker set included 866 DArT and 315 gene sequence-based markers. Comparison with previous DArT mapping studies in perennial and Italian ryegrass (L. multiflorum) identified 87 and 105 DArT markers in common, respectively, of which 94% and 87% mapped to homoeologous linkage groups. A similar comparison with meadow fescue (F. pratensis) identified only 28 DArT markers in common, of which c. 50% mapped to non-homoelogous linkage groups. In L. perenne, the genetic distance spanned by the DArT markers encompassed the majority of the regions that could be described in terms of comparative genomic relationships with rice, Brachypodium distachyon, and Sorghum bicolor. DArT markers are likely to be a useful common marker resource for ryegrasses and fescues, though the success in aligning different populations through the mapping of common markers will be influenced by degrees of population interrelatedness. The detailed mapping of DArT and gene-based markers in this study potentially allows comparative relationships to be derived in future mapping populations characterised using solely DArT markers.

[Evaluation of the effect of varicella outbreak control measures through a discrete time delay SEIR model].

PubMed

Pan, Jin-ren; Huang, Zheng-qiang; Chen, Kun

2012-04-01

forecast the epidemic trend and to evaluate the effect of outbreak control measures by investigation of a varicella outbreak event with a discrete time delay SEIR model. A discrete time delay model was formulated by discretization method based on a continuous SEIR model with the consideration of the time delay effect on latent period and communicable period. The epidemic trend forecast was carried out based on the number of expected cases. The theoretical effect evaluation was assessed by comparing the results from different emergency control measures. Without any control measures, the theoretical attack rate was 30.16% (504/1671). The course of the epidemic lasted for 4 months and the peak epidemic time was 78 days after the onset of the first case. 'Generation' phenomenon had been observed in the course of the epidemic with the interval of two weeks. The actual number of cases was decreased by 89.48% (451/504) compared with the number of expected cases under no control measure scenario. With the rigorous quarantine measure for all cases on their onset day, when the measure was conducted on 0, 14, 28, 42 days after the onset of the first case, the total numbers of expected cases were 22, 59, 127 and 220 respectively. With the quarantine measure conducted on 14 days after the onset of the first case, when the proportion of quarantine was 30%, 50%, 70%, 90%, the total number of expected cases were 485, 457, 386 and 169, respectively. With the emergent vaccination for all persons, when the measure was conducted on 0, 14, 28, 42 days after the onset of the first case, the total numbers of expected cases were 7, 26, 81 and 202 respectively. With the emergent vaccination conducted on 14 days after the onset of the first case, when the immunization coverage rate was 30%, 50%, 70%, 90%, the total numbers of expected cases were 354, 246, 127 and 40, respectively. The number of expected cases can be regarded as the reference to evaluate the effect of control measures. The simulation results suggest that it will get more benefits to conduct control measures earlier in varicella outbreak events, and the effect of emergent vaccination is better than that of quarantine measure under the same conditions.

DArT Markers Effectively Target Gene Space in the Rye Genome

PubMed Central

Gawroński, Piotr; Pawełkowicz, Magdalena; Tofil, Katarzyna; Uszyński, Grzegorz; Sharifova, Saida; Ahluwalia, Shivaksh; Tyrka, Mirosław; Wędzony, Maria; Kilian, Andrzej; Bolibok-Brągoszewska, Hanna

2016-01-01

Large genome size and complexity hamper considerably the genomics research in relevant species. Rye (Secale cereale L.) has one of the largest genomes among cereal crops and repetitive sequences account for over 90% of its length. Diversity Arrays Technology is a high-throughput genotyping method, in which a preferential sampling of gene-rich regions is achieved through the use of methylation sensitive restriction enzymes. We obtained sequences of 6,177 rye DArT markers and following a redundancy analysis assembled them into 3,737 non-redundant sequences, which were then used in homology searches against five Pooideae sequence sets. In total 515 DArT sequences could be incorporated into publicly available rye genome zippers providing a starting point for the integration of DArT- and transcript-based genomics resources in rye. Using Blast2Go pipeline we attributed putative gene functions to 1101 (29.4%) of the non-redundant DArT marker sequences, including 132 sequences with putative disease resistance-related functions, which were found to be preferentially located in the 4RL and 6RL chromosomes. Comparative analysis based on the DArT sequences revealed obvious inconsistencies between two recently published high density consensus maps of rye. Furthermore we demonstrated that DArT marker sequences can be a source of SSR polymorphisms. Obtained data demonstrate that DArT markers effectively target gene space in the large, complex, and repetitive rye genome. Through the annotation of putative gene functions and the alignment of DArT sequences relative to reference genomes we obtained information, that will complement the results of the studies, where DArT genotyping was deployed, by simplifying the gene ontology and microcolinearity based identification of candidate genes. PMID:27833625

DArT Markers Effectively Target Gene Space in the Rye Genome.

PubMed

Gawroński, Piotr; Pawełkowicz, Magdalena; Tofil, Katarzyna; Uszyński, Grzegorz; Sharifova, Saida; Ahluwalia, Shivaksh; Tyrka, Mirosław; Wędzony, Maria; Kilian, Andrzej; Bolibok-Brągoszewska, Hanna

2016-01-01

Large genome size and complexity hamper considerably the genomics research in relevant species. Rye ( Secale cereale L.) has one of the largest genomes among cereal crops and repetitive sequences account for over 90% of its length. Diversity Arrays Technology is a high-throughput genotyping method, in which a preferential sampling of gene-rich regions is achieved through the use of methylation sensitive restriction enzymes. We obtained sequences of 6,177 rye DArT markers and following a redundancy analysis assembled them into 3,737 non-redundant sequences, which were then used in homology searches against five Pooideae sequence sets. In total 515 DArT sequences could be incorporated into publicly available rye genome zippers providing a starting point for the integration of DArT- and transcript-based genomics resources in rye. Using Blast2Go pipeline we attributed putative gene functions to 1101 (29.4%) of the non-redundant DArT marker sequences, including 132 sequences with putative disease resistance-related functions, which were found to be preferentially located in the 4RL and 6RL chromosomes. Comparative analysis based on the DArT sequences revealed obvious inconsistencies between two recently published high density consensus maps of rye. Furthermore we demonstrated that DArT marker sequences can be a source of SSR polymorphisms. Obtained data demonstrate that DArT markers effectively target gene space in the large, complex, and repetitive rye genome. Through the annotation of putative gene functions and the alignment of DArT sequences relative to reference genomes we obtained information, that will complement the results of the studies, where DArT genotyping was deployed, by simplifying the gene ontology and microcolinearity based identification of candidate genes.

Heterodimerization with beta2-adrenergic receptors promotes surface expression and functional activity of alpha1D-adrenergic receptors.

PubMed

Uberti, Michelle A; Hague, Chris; Oller, Heide; Minneman, Kenneth P; Hall, Randy A

2005-04-01

The alpha1D-adrenergic receptor (alpha1D-AR) is a G protein-coupled receptor (GPCR) that is poorly trafficked to the cell surface and largely nonfunctional when heterologously expressed by itself in a variety of cell types. We screened a library of approximately 30 other group I GPCRs in a quantitative luminometer assay for the ability to promote alpha1D-AR cell surface expression. Strikingly, these screens revealed only two receptors capable of inducing robust increases in the amount of alpha1D-AR at the cell surface: alpha1B-AR and beta2-AR. Confocal imaging confirmed that coexpression with beta2-AR resulted in translocation of alpha1D-AR from intracellular sites to the plasma membrane. Additionally, coimmunoprecipitation studies demonstrated that alpha1D-AR and beta2-AR specifically interact to form heterodimers when coexpressed in HEK-293 cells. Ligand binding studies revealed an increase in total alpha1D-AR binding sites upon coexpression with beta2-AR, but no apparent effect on the pharmacological properties of the receptors. In functional studies, coexpression with beta2-AR significantly enhanced the coupling of alpha1D-AR to norepinephrine-stimulated Ca2+ mobilization. Heterodimerization of beta2-AR with alpha1D-AR also conferred the ability of alpha1D-AR to cointernalize upon beta2-AR agonist stimulation, revealing a novel mechanism by which these different adrenergic receptor subtypes may regulate each other's activity. These findings demonstrate that the selective association of alpha1D-AR with other receptors is crucial for receptor surface expression and function and also shed light on a novel mechanism of cross talk between alpha1- and beta2-ARs that is mediated through heterodimerization and cross-internalization.

Important LiDAR metrics for discriminating forest tree species in Central Europe

NASA Astrophysics Data System (ADS)

Shi, Yifang; Wang, Tiejun; Skidmore, Andrew K.; Heurich, Marco

2018-03-01

Numerous airborne LiDAR-derived metrics have been proposed for classifying tree species. Yet an in-depth ecological and biological understanding of the significance of these metrics for tree species mapping remains largely unexplored. In this paper, we evaluated the performance of 37 frequently used LiDAR metrics derived under leaf-on and leaf-off conditions, respectively, for discriminating six different tree species in a natural forest in Germany. We firstly assessed the correlation between these metrics. Then we applied a Random Forest algorithm to classify the tree species and evaluated the importance of the LiDAR metrics. Finally, we identified the most important LiDAR metrics and tested their robustness and transferability. Our results indicated that about 60% of LiDAR metrics were highly correlated to each other (|r| > 0.7). There was no statistically significant difference in tree species mapping accuracy between the use of leaf-on and leaf-off LiDAR metrics. However, combining leaf-on and leaf-off LiDAR metrics significantly increased the overall accuracy from 58.2% (leaf-on) and 62.0% (leaf-off) to 66.5% as well as the kappa coefficient from 0.47 (leaf-on) and 0.51 (leaf-off) to 0.58. Radiometric features, especially intensity related metrics, provided more consistent and significant contributions than geometric features for tree species discrimination. Specifically, the mean intensity of first-or-single returns as well as the mean value of echo width were identified as the most robust LiDAR metrics for tree species discrimination. These results indicate that metrics derived from airborne LiDAR data, especially radiometric metrics, can aid in discriminating tree species in a mixed temperate forest, and represent candidate metrics for tree species classification and monitoring in Central Europe.

Diversity Arrays Technology (DArT) for Pan-Genomic Evolutionary Studies of Non-Model Organisms

PubMed Central

James, Karen E.; Schneider, Harald; Ansell, Stephen W.; Evers, Margaret; Robba, Lavinia; Uszynski, Grzegorz; Pedersen, Niklas; Newton, Angela E.; Russell, Stephen J.; Vogel, Johannes C.; Kilian, Andrzej

2008-01-01

Background High-throughput tools for pan-genomic study, especially the DNA microarray platform, have sparked a remarkable increase in data production and enabled a shift in the scale at which biological investigation is possible. The use of microarrays to examine evolutionary relationships and processes, however, is predominantly restricted to model or near-model organisms. Methodology/Principal Findings This study explores the utility of Diversity Arrays Technology (DArT) in evolutionary studies of non-model organisms. DArT is a hybridization-based genotyping method that uses microarray technology to identify and type DNA polymorphism. Theoretically applicable to any organism (even one for which no prior genetic data are available), DArT has not yet been explored in exclusively wild sample sets, nor extensively examined in a phylogenetic framework. DArT recovered 1349 markers of largely low copy-number loci in two lineages of seed-free land plants: the diploid fern Asplenium viride and the haploid moss Garovaglia elegans. Direct sequencing of 148 of these DArT markers identified 30 putative loci including four routinely sequenced for evolutionary studies in plants. Phylogenetic analyses of DArT genotypes reveal phylogeographic and substrate specificity patterns in A. viride, a lack of phylogeographic pattern in Australian G. elegans, and additive variation in hybrid or mixed samples. Conclusions/Significance These results enable methodological recommendations including procedures for detecting and analysing DArT markers tailored specifically to evolutionary investigations and practical factors informing the decision to use DArT, and raise evolutionary hypotheses concerning substrate specificity and biogeographic patterns. Thus DArT is a demonstrably valuable addition to the set of existing molecular approaches used to infer biological phenomena such as adaptive radiations, population dynamics, hybridization, introgression, ecological differentiation and phylogeography. PMID:18301759

LiDAR for data efficiency.

DOT National Transportation Integrated Search

2011-09-30

This report documents the AHMCT research project: LiDAR for Data Efficiency for the Washington State Department of Transportation (WSDOT). The research objective was to evaluate mobile LiDAR technology to enhance safety, determine efficiency ga...

Diversity arrays technology: a generic genome profiling technology on open platforms.

PubMed

Kilian, Andrzej; Wenzl, Peter; Huttner, Eric; Carling, Jason; Xia, Ling; Blois, Hélène; Caig, Vanessa; Heller-Uszynska, Katarzyna; Jaccoud, Damian; Hopper, Colleen; Aschenbrenner-Kilian, Malgorzata; Evers, Margaret; Peng, Kaiman; Cayla, Cyril; Hok, Puthick; Uszynski, Grzegorz

2012-01-01

In the last 20 years, we have observed an exponential growth of the DNA sequence data and simular increase in the volume of DNA polymorphism data generated by numerous molecular marker technologies. Most of the investment, and therefore progress, concentrated on human genome and genomes of selected model species. Diversity Arrays Technology (DArT), developed over a decade ago, was among the first "democratizing" genotyping technologies, as its performance was primarily driven by the level of DNA sequence variation in the species rather than by the level of financial investment. DArT also proved more robust to genome size and ploidy-level differences among approximately 60 organisms for which DArT was developed to date compared to other high-throughput genotyping technologies. The success of DArT in a number of organisms, including a wide range of "orphan crops," can be attributed to the simplicity of underlying concepts: DArT combines genome complexity reduction methods enriching for genic regions with a highly parallel assay readout on a number of "open-access" microarray platforms. The quantitative nature of the assay enabled a number of applications in which allelic frequencies can be estimated from DArT arrays. A typical DArT assay tests for polymorphism tens of thousands of genomic loci with the final number of markers reported (hundreds to thousands) reflecting the level of DNA sequence variation in the tested loci. Detailed DArT methods, protocols, and a range of their application examples as well as DArT's evolution path are presented.

Shipborne LiDAR system for coastal change monitoring

NASA Astrophysics Data System (ADS)

Kim, chang hwan; Park, chang hong; Kim, hyun wook; hyuck Kim, won; Lee, myoung hoon; Park, hyeon yeong

2016-04-01

Coastal areas, used as human utilization areas like leisure space, medical care, ports and power plants, etc., are regions that are continuously changing and interconnected with oceans and land and the sea level has risen by about 8cm (1.9mm / yr) due to global warming from 1964 year to 2006 year in Korea. Coastal erosion due to sea-level rise has caused the problem of marine ecosystems and loss of tourism resources, etc. Regular monitoring of coastal erosion is essential at key locations with such volatility. But the survey method of land mobile LiDAR (light detection and ranging) system has much time consuming and many restrictions. For effective monitoring beach erosion, KIOST (Korea Institute of Ocean Science & Technology) has constructed a shipborne mobile LiDAR system. The shipborne mobile LiDAR system comprised a land mobile LiDAR (RIEGL LMS-420i), an INS (inertial navigation system, MAGUS Inertial+), a RTKGPS (LEICA GS15 GS25), and a fixed platform. The shipborne mobile LiDAR system is much more effective than a land mobile LiDAR system in the measuring of fore shore areas without shadow zone. Because the vessel with the shipborne mobile LiDAR system is continuously moved along the shoreline, it is possible to efficiently survey a large area in a relatively short time. Effective monitoring of the changes using the constructed shipborne mobile LiDAR system for seriously eroded coastal areas will be able to contribute to coastal erosion management and response.

Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

NASA Astrophysics Data System (ADS)

Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

2016-06-01

Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

Highly reproducible surface-enhanced Raman scattering-active Au nanostructures prepared by simple electrodeposition: origin of surface-enhanced Raman scattering activity and applications as electrochemical substrates.

PubMed

Choi, Suhee; Ahn, Miri; Kim, Jongwon

2013-05-24

The fabrication of effective surface-enhanced Raman scattering (SERS) substrates has been the subject of intensive research because of their useful applications. In this paper, dendritic gold (Au) rod (DAR) structures prepared by simple one-step electrodeposition in a short time were examined as an effective SERS-active substrate. The SERS activity of the DAR surfaces was compared to that of other nanostructured Au surfaces with different morphologies, and its dependence on the structural variation of DAR structures was examined. These comparisonal investigations revealed that highly faceted sharp edge sites present on the DAR surfaces play a critical role in inducing a high SERS activity. The SERS enhancement factor was estimated to be greater than 10(5), and the detection limit of rhodamine 6G at DAR surfaces was 10(-8)M. The DAR surfaces exhibit excellent spot-to-spot and substrate-to-substrate SERS enhancement reproducibility, and their long-term stability is very good. It was also demonstrated that the DAR surfaces can be effectively utilized in electrochemical SERS systems, wherein a reversible SERS behavior was obtained during the cycling to cathodic potential regions. Considering the straightforward preparation of DAR substrates and the clean nature of SERS-active Au surfaces prepared in the absence of additives, we expect that DAR surfaces can be used as cost-effective SERS substrates in analytical and electrochemical applications. Copyright © 2013 Elsevier B.V. All rights reserved.

An Approach to Extract Moving Objects from Mls Data Using a Volumetric Background Representation

NASA Astrophysics Data System (ADS)

Gehrung, J.; Hebel, M.; Arens, M.; Stilla, U.

2017-05-01

Data recorded by mobile LiDAR systems (MLS) can be used for the generation and refinement of city models or for the automatic detection of long-term changes in the public road space. Since for this task only static structures are of interest, all mobile objects need to be removed. This work presents a straightforward but powerful approach to remove the subclass of moving objects. A probabilistic volumetric representation is utilized to separate MLS measurements recorded by a Velodyne HDL-64E into mobile objects and static background. The method was subjected to a quantitative and a qualitative examination using multiple datasets recorded by a mobile mapping platform. The results show that depending on the chosen octree resolution 87-95% of the measurements are labeled correctly.

Optimizing variable radius plot size and LiDAR resolution to model standing volume in conifer forests

Treesearch

Ram Kumar Deo; Robert E. Froese; Michael J. Falkowski; Andrew T. Hudak

2016-01-01

The conventional approach to LiDAR-based forest inventory modeling depends on field sample data from fixed-radius plots (FRP). Because FRP sampling is cost intensive, combining variable-radius plot (VRP) sampling and LiDAR data has the potential to improve inventory efficiency. The overarching goal of this study was to evaluate the integration of LiDAR and VRP data....

The comparison between two airborne LiDAR datasets to analyse debris flow initiation in north-western Iceland

NASA Astrophysics Data System (ADS)

Morino, Costanza; Conway, Susan J.; Balme, Matthew R.; Jordan, Colm; Hillier, John; Sæmundsson, Þorsteinn; Argles, Tom

2015-04-01

A debris flow is a very rapid to extremely rapid flow (e.g., 0.8-28 ms-1) [1], that occurs when coarse and poorly-sorted debris, mixed with water and/or air, move down hill slopes in response to gravity [2]. Both the fluid and the solid have a strong influence on the movement of debris flows. They can be extremely destructive, due to their capability of transporting metre-size boulders [e.g., 3, 4]. There are two main ways in which a debris flow can be initiated: by slope failure or by the "fire hose" effect. The slope failure type is particularly common in alpine regions, where landslides can evolve into debris flows [5], triggered by the coalescence of different slope failures. Steep slope gradients, high pore-water pressures, heavy rainfall and/or snowmelt favour this process. The "fire hose" effect occurs when there is a high concentration of debris accumulated within a pre-existing channel; a surge of water through the channel can then develop into a debris flow by incorporating this debris [e.g. 5-7]. In this study, we examine the triggering style of debris flows above the town of Ísafjörður in the Westfjords of Iceland. The slope above the town is characterised by a large topographic bench upon which 20-35 m of glacial till is perched. The sediments are unstable at the bench margin and thus generate frequent, large, hillslope debris flows [8, 9]. In our new analysis, we report on the comparison between the two airborne LiDAR elevation models (collected in 2007 and 2013 by the UK Natural Environment Research Council Airborne Research and Survey Facility), which display several new debris flows and also related mass movements. From these analyses, we find that debris flows in the region are triggered by simple failure of the glacial till, as recognised before [8, 9]. However, debris flows may also be regenerated by the "fire hose" effect, when debris that has collapsed into chutes is remobilised by a later snowmelt or precipitation event. Comparing different airborne LiDAR datasets has proven to be a powerful tool, not just in the topographic analysis of landscape, but also in the discrimination of the causes of potentially disastrous phenomena. This suggests new possibilities for using remote sensing analysis to mitigate the effects of natural hazards. References: [1] Rickenmann, D., 1999. Natural Hazards, 19 (1), 47-77. [2] Iverson, R.M., 1997. Reviews of Geophysics, 35 (3), 245-296. [3] Clague, J.J., Evans, S.G., Blown, I.G., 1985. Journal of Earth Sciences, 22 (10), 1492-1502. [4] Kanji, M.A., Cruz, P.T., Massad, F., 2008. Landslides, 5 (1), 71-82. [5] Johnson, A.M. and Rodine, J. R. 1984. Slope Instability. Wiley, New York, 257-361. [6] Coe, J.A., Glancy, P.A., Whitney, J.W., 1997. Geomorphology, 20, 11-28. [7] Griffiths, P.G., Webb, R.H., Melis, T.S., 2004. Journal of Geophysical Research, 109, 321-336. [8] Conway, S. J., Decaulne, A., Balme, M. R., Murray, J. B., Towner, M. C., 2010. Geomorphology, 114 (4), 556-572. [9] Decaulne, A., Sæmundsson, Þ., Pétursson, O., 2005. Geografiska Annaler: Series A, Physical Geography, 87A, 487-500.

Processing LiDAR Data to Predict Natural Hazards

NASA Technical Reports Server (NTRS)

Fairweather, Ian; Crabtree, Robert; Hager, Stacey

2008-01-01

ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.

The Dynamics of a SEIR-SIRC Antigenic Drift Influenza Model.

PubMed

Adi-Kusumo, Fajar

2017-06-01

We consider the dynamics of an influenza model with antigenic drift mechanism. Antigenic drift is an antigen mutation on the skin surface of the influenza virus that do not produce a new virus strain. The mutation produces the same virus but with slightly different antigens that cannot be recognized by the immune receptors formed by the previous infection. There are some type of influenza that involve the interaction between two populations such as human and animal. In this paper, we construct an influenza model with antigenic drift mechanism on the human population that has interaction with the animal population. The animal population is assumed to follow the SEIR epidemic model. Our model is motivated by the fact that some of the influenza cases in human come from the animal such as the swine and the avian. The transmission parameter that shows number of contact between the susceptible human and the infectious animals are important to study. The parameter plays an important role to detect the cycle of infection of the disease. The other important parameters are the seasonality degree, which shows the pathogen appearance and disappearance via annual migration, and the infection rate on the human population. We employ the bifurcation theory to analyze the behavior of the system and to detect the cycle of infection types when the parameters values are varied.

Improving LiDAR Data Post-Processing Techniques for Archaeological Site Management and Analysis: A Case Study from Canaveral National Seashore Park

NASA Astrophysics Data System (ADS)

Griesbach, Christopher

Methods used to process raw Light Detection and Ranging (LiDAR) data can sometimes obscure the digital signatures indicative of an archaeological site. This thesis explains the negative effects that certain LiDAR data processing procedures can have on the preservation of an archaeological site. This thesis also presents methods for effectively integrating LiDAR with other forms of mapping data in a Geographic Information Systems (GIS) environment in order to improve LiDAR archaeological signatures by examining several pre-Columbian Native American shell middens located in Canaveral National Seashore Park (CANA).

Multivitamin supplementation in HIV-positive pregnant women: impact on depression and quality of life in a resource-poor setting.

PubMed

Smith Fawzi, M C; Kaaya, S F; Mbwambo, J; Msamanga, G I; Antelman, G; Wei, R; Hunter, D J; Fawzi, W W

2007-05-01

The primary objective of this study was to examine the effect of vitamin supplementation on health-related quality of life and the risk of elevated depressive symptoms comparable to major depressive disorder (MDD) in HIV-positive pregnant women in Dar es Salaam, Tanzania. From April 1995 to July 1997, 1078 HIV-positive pregnant women were enrolled in a randomized controlled trial. We examined the effects of vitamin supplementation on quality of life and the risk of elevated depressive symptoms, assessed longitudinally every 6-12 months. A substantial prevalence of elevated depressive symptoms (42%) was observed in HIV-positive pregnant women. Multivitamin supplementation (B-complex, C and E) demonstrated a protective effect on depression [relative risk (RR)=0.78; P=0.005] and quality of life [RR=0.72 for social functioning (P=0.001) and vitality (P=0.0001); RR=0.70 for role-physical (P=0.002)]; however, vitamin A showed no effect on these outcomes. Multivitamin supplementation (B-complex, C and E) resulted in a reduction in risk of elevated depressive symptoms comparable to MDD and improvement in quality of life in HIV-positive pregnant women in Tanzania.

The first genetic map of pigeon pea based on diversity arrays technology (DArT) markers.

PubMed

Yang, Shi Ying; Saxena, Rachit K; Kulwal, Pawan L; Ash, Gavin J; Dubey, Anuja; Harper, John D I; Upadhyaya, Hari D; Gothalwal, Ragini; Kilian, Andrzej; Varshney, Rajeev K

2011-04-01

With an objective to develop a genetic map in pigeon pea (Cajanus spp.), a total of 554 diversity arrays technology (DArT) markers showed polymorphism in a pigeon pea F(2) mapping population of 72 progenies derived from an interspecific cross of ICP 28 (Cajanus cajan) and ICPW 94 (Cajanus scarabaeoides). Approximately 13% of markers did not conform to expected segregation ratio. The total number of DArT marker loci segregating in Mendelian manner was 405 with 73.1% (P > 0.001) of DArT markers having unique segregation patterns. Two groups of genetic maps were generated using DArT markers. While the maternal genetic linkage map had 122 unique DArT maternal marker loci, the paternal genetic linkage map has a total of 172 unique DArT paternal marker loci. The length of these two maps covered 270.0 cM and 451.6 cM, respectively. These are the first genetic linkage maps developed for pigeon pea, and this is the first report of genetic mapping in any grain legume using diversity arrays technology.

On the impact of a refined stochastic model for airborne LiDAR measurements

NASA Astrophysics Data System (ADS)

Bolkas, Dimitrios; Fotopoulos, Georgia; Glennie, Craig

2016-09-01

Accurate topographic information is critical for a number of applications in science and engineering. In recent years, airborne light detection and ranging (LiDAR) has become a standard tool for acquiring high quality topographic information. The assessment of airborne LiDAR derived DEMs is typically based on (i) independent ground control points and (ii) forward error propagation utilizing the LiDAR geo-referencing equation. The latter approach is dependent on the stochastic model information of the LiDAR observation components. In this paper, the well-known statistical tool of variance component estimation (VCE) is implemented for a dataset in Houston, Texas, in order to refine the initial stochastic information. Simulations demonstrate the impact of stochastic-model refinement for two practical applications, namely coastal inundation mapping and surface displacement estimation. Results highlight scenarios where erroneous stochastic information is detrimental. Furthermore, the refined stochastic information provides insights on the effect of each LiDAR measurement in the airborne LiDAR error budget. The latter is important for targeting future advancements in order to improve point cloud accuracy.

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

NASA Technical Reports Server (NTRS)

Naesset, Erik; Gobakken, Terje; Bollandsas, Ole Martin; Gregoire, Timothy G.; Nelson, Ross; Stahl, Goeran

2013-01-01

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Biaxial seismic behaviour of reinforced concrete columns =

NASA Astrophysics Data System (ADS)

Rodrigues, Hugo Filipe Pinheiro

A analise dos efeitos dos sismos mostra que a investigacao em engenharia sismica deve dar especial atencao a avaliacao da vulnerabilidade das construcoes existentes, frequentemente desprovidas de adequada resistencia sismica tal como acontece em edificios de betao armado (BA) de muitas cidades em paises do sul da Europa, entre os quais Portugal. Sendo os pilares elementos estruturais fundamentais na resistencia sismica dos edificios, deve ser dada especial atencao a sua resposta sob acoes ciclicas. Acresce que o sismo e um tipo de acao cujos efeitos nos edificios exige a consideracao de duas componentes horizontais, o que tem exigencias mais severas nos pilares comparativamente a acao unidirecional. Assim, esta tese centra-se na avaliacao da resposta estrutural de pilares de betao armado sujeitos a acoes ciclicas horizontais biaxiais, em tres linhas principais. Em primeiro lugar desenvolveu-se uma campanha de ensaios para o estudo do comportamento ciclico uniaxial e biaxial de pilares de betao armado com esforco axial constante. Para tal foram construidas quatro series de pilares retangulares de betao armado (24 no total) com diferentes caracteristicas geometricas e quantidades de armadura longitudinal, tendo os pilares sido ensaiados para diferentes historias de carga. Os resultados experimentais obtidos sao analisados e discutidos dando particular atencao a evolucao do dano, a degradacao de rigidez e resistencia com o aumento das exigencias de deformacao, a energia dissipada, ao amortecimento viscoso equivalente; por fim e proposto um indice de dano para pilares solicitados biaxialmente. De seguida foram aplicadas diferentes estrategias de modelacao nao-linear para a representacao do comportamento biaxial dos pilares ensaiados, considerando nao-linearidade distribuida ao longo dos elementos ou concentrada nas extremidades dos mesmos. Os resultados obtidos com as varias estrategias de modelacao demonstraram representar adequadamente a resposta em termos das curvas envolventes forca-deslocamento, mas foram encontradas algumas dificuldades na representacao da degradacao de resistencia e na evolucao da energia dissipada. Por fim, e proposto um modelo global para a representacao do comportamento nao-linear em flexao de elementos de betao armado sujeitos a acoes biaxiais ciclicas. Este modelo tem por base um modelo uniaxial conhecido, combinado com uma funcao de interacao desenvolvida com base no modelo de Bouc- Wen. Esta funcao de interacao foi calibrada com recurso a tecnicas de otimizacao e usando resultados de uma serie de analises numericas com um modelo refinado. E ainda demonstrada a capacidade do modelo simplificado em reproduzir os resultados experimentais de ensaios biaxiais de pilares.

High Density LiDAR and Orthophotography in UXO Wide Area Assessment

DTIC Science & Technology

2008-01-01

4 Figure 2. Helicopter-Mounted LiDAR and Orthophoto Sensor Equipment...4 Figure 3. LiDAR and Orthophoto System Installed on Helicopter........................................ 6 Figure 4. Kirtland Precision...17 Figure 11. Orthophoto Data Density Results

Cloning, sequence, and disruption of the Saccharomyces diastaticus DAR1 gene encoding a glycerol-3-phosphate dehydrogenase.

PubMed Central

Wang, H T; Rahaim, P; Robbins, P; Yocum, R R

1994-01-01

The Saccharomyces diastaticus DAR1 gene was cloned by complementation in an Escherichia coli strain auxogrophic for glycerol-3-phosphate. DAR1 encodes an NADH-dependent dihydroxyacetone phosphate reductase (sn-glycerol-3-phosphate dehydrogenase [G3PDase; EC 1.1.1.8]) homologous to several other eukaryotic G3PDases. DAR1 is distinct from GUT2, which encodes a glucose-repressed mitochondrial G3PDase, but is identical to GPD1 from S. cerevisiae, a close relative of S. diastaticus. The level of DAR1-encoded G3PDase was increased about threefold in a medium of high osmolarity. Disruption of DAR1 in a haploid S. cerevisiae was not lethal but led to a decrease in cytoplasmic NADH-dependent G3PDase activity, an increase in osmotic sensitivity, and a 25% reduction in glycerol secretion from cells grown anaerobically on glucose. PMID:7961476

Cloning, sequence, and disruption of the Saccharomyces diastaticus DAR1 gene encoding a glycerol-3-phosphate dehydrogenase.

PubMed

Wang, H T; Rahaim, P; Robbins, P; Yocum, R R

1994-11-01

The Saccharomyces diastaticus DAR1 gene was cloned by complementation in an Escherichia coli strain auxogrophic for glycerol-3-phosphate. DAR1 encodes an NADH-dependent dihydroxyacetone phosphate reductase (sn-glycerol-3-phosphate dehydrogenase [G3PDase; EC 1.1.1.8]) homologous to several other eukaryotic G3PDases. DAR1 is distinct from GUT2, which encodes a glucose-repressed mitochondrial G3PDase, but is identical to GPD1 from S. cerevisiae, a close relative of S. diastaticus. The level of DAR1-encoded G3PDase was increased about threefold in a medium of high osmolarity. Disruption of DAR1 in a haploid S. cerevisiae was not lethal but led to a decrease in cytoplasmic NADH-dependent G3PDase activity, an increase in osmotic sensitivity, and a 25% reduction in glycerol secretion from cells grown anaerobically on glucose.

Climate change induced risk analysis of Dar es Salaam city (Tanzania)

NASA Astrophysics Data System (ADS)

Topa, Maria Elena; Herslund, Lise; Cavan, Gina; Printz, Andreas; Simonis, Ingo; Bucchignani, Edoardo; Jean-Baptiste, Nathalie; Hellevik, Siri; Johns, Regina; Kibassa, Deusdedit; Kweka, Clara; Magina, Fredrick; Mangula, Alpha; Mbuya, Elinorata; Uhinga, Guido; Kassenga, Gabriel; Kyessi, Alphonce; Shemdoe, Riziki; Kombe, Wilbard

2013-04-01

CLUVA (CLimate change and Urban Vulnerability in Africa; http://www.cluva.eu/) is a 3 years project, funded by the European Commission in 2010. The main objective of CLUVA is to develop context-centered methods and knowledge to be applied to African cities to assess vulnerabilities and increase knowledge on managing climate related risks. The project estimates the impacts of climate changes in the next 40 years at urban scale and downscales IPCC climate projections to evaluate specific threats to selected African test cities. These are mainly from floods, sea-level rise, droughts, heat waves, and desertification. The project evaluates and links: social vulnerability; urban green structures and ecosystem services; urban-rural interfaces; vulnerability of urban built environment and lifelines; and related institutional and governance dimensions of adaptation. The multi-scale and multi-disciplinary qualitative, quantitative and probabilistic approach of CLUVA is currently being applied to selected African test cities (Addis Ababa - Ethiopia; Dar es Salaam - Tanzania; Douala - Cameroun; Ouagadougou - Burkina Faso; St. Louis - Senegal). In particular, the poster will present preliminary findings for the Dar es Salaam case study. Dar es Salaam, which is Tanzania's largest coastal city, is exposed to floods, coastal erosion, droughts and heat waves, and highly vulnerable to impacts as a result of ineffective urban planning (about 70% unplanned settlements), poverty and lack of basic infrastructure (e.g. lack of or poor quality storm water drainage systems). Climate change could exacerbate the current situation increasing hazard-exposure alongside the impacts of development pressures which act to increase urban vulnerability for example because of informal (unregulated) urbanization. The CLUVA research team - composed of climate and environmental scientists, risk management experts, urban planners and social scientists from both European and African institutions - has started to produce research outputs suitable for use in evidence-based planning activities in the case study cities through interdisciplinary methods and analysis. Climate change projections at 8 km resolution are ready for regions containing each of the case study cities; a preliminary hazard assessment for floods, droughts and heat waves has been performed, based on historical data; urban morphology and related green structures have been characterized; preliminary findings in social vulnerability provide insights how communities and households can resist and cope with, as well as recover from climate induced hazards; vulnerability of informal settlements to floods has been assessed for a case study area (Suna sub ward) and a GIS based identification of urban residential hotspots to flooding is completed. Furthermore, a set of indicators has been identified and the most relevant for Dar es Salaam has been selected by local stakeholders to identify particular vulnerable high risk areas and communities. An investigation of the existing urban planning and governance system and its interface with climate risks and vulnerability has inter-alia suggested severe institutional deficits including over-centralized institutions for disaster risk management and climate change adaptation. A multi-risk framework considering climate-related hazards, and physical and social fragilities has been set up.

A GUI visualization system for airborne lidar image data to reconstruct 3D city model

NASA Astrophysics Data System (ADS)

Kawata, Yoshiyuki; Koizumi, Kohei

2015-10-01

A visualization toolbox system with graphical user interfaces (GUIs) was developed for the analysis of LiDAR point cloud data, as a compound object oriented widget application in IDL (Interractive Data Language). The main features in our system include file input and output abilities, data conversion capability from ascii formatted LiDAR point cloud data to LiDAR image data whose pixel value corresponds the altitude measured by LiDAR, visualization of 2D/3D images in various processing steps and automatic reconstruction ability of 3D city model. The performance and advantages of our graphical user interface (GUI) visualization system for LiDAR data are demonstrated.

How much does the time lag between wildlife field-data collection and LiDAR-data acquisition matter for studies of animal distributions? A case study using bird communities

Treesearch

Kerri T. Vierling; Charles E. Swift; Andrew T. Hudak; Jody C. Vogeler; Lee A. Vierling

2014-01-01

Vegetation structure quantified by light detection and ranging (LiDAR) can improve understanding of wildlife occupancy and species-richness patterns. However, there is often a time lag between the collection of LiDAR data and wildlife data. We investigated whether a time lag between the LiDAR acquisition and field-data acquisition affected mapped wildlife distributions...

Demonstration of LiDAR and Orthophotography for Wide Area Assessment at Pueblo Precision Bombing Range #2, Colorado

DTIC Science & Technology

2008-01-01

Figure 11. Screenshot of OrthoPro seam lines (pink), tiles (blue), and photos (green)................ 26 Figure 12. Calibration craters (existing...with aerial targets for the orthophotography data collection, 1 per data collection tile (1 sq km). For the Phase I data collection, 9 LiDAR ground...Orthophotography data were collected concurrently with the LiDAR data collection. Based on the LiDAR flight line spacing parameters, the orthophoto images were

Development and validation of the Dimensional Anhedonia Rating Scale (DARS) in a community sample and individuals with major depression.

PubMed

Rizvi, Sakina J; Quilty, Lena C; Sproule, Beth A; Cyriac, Anna; Michael Bagby, R; Kennedy, Sidney H

2015-09-30

Anhedonia, a core symptom of Major Depressive Disorder (MDD), is predictive of antidepressant non-response. In contrast to the definition of anhedonia as a "loss of pleasure", neuropsychological studies provide evidence for multiple facets of hedonic function. The aim of the current study was to develop and validate the Dimensional Anhedonia Rating Scale (DARS), a dynamic scale that measures desire, motivation, effort and consummatory pleasure across hedonic domains. Following item selection procedures and reliability testing using data from community participants (N=229) (Study 1), the 17-item scale was validated in an online study with community participants (N=150) (Study 2). The DARS was also validated in unipolar or bipolar depressed patients (n=52) and controls (n=50) (Study 3). Principal components analysis of the 17-item DARS revealed a 4-component structure mapping onto the domains of anhedonia: hobbies, food/drink, social activities, and sensory experience. Reliability of the DARS subscales was high across studies (Cronbach's α=0.75-0.92). The DARS also demonstrated good convergent and divergent validity. Hierarchical regression analysis revealed the DARS showed additional utility over the Snaith-Hamilton Pleasure Scale (SHAPS) in predicting reward function and distinguishing MDD subgroups. These studies provide support for the reliability and validity of the DARS. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast-growing Eucalyptus forest plantation using airborne LiDAR data.

PubMed

Silva, Carlos Alberto; Hudak, Andrew Thomas; Klauberg, Carine; Vierling, Lee Alexandre; Gonzalez-Benecke, Carlos; de Padua Chaves Carvalho, Samuel; Rodriguez, Luiz Carlos Estraviz; Cardil, Adrián

2017-12-01

LiDAR remote sensing is a rapidly evolving technology for quantifying a variety of forest attributes, including aboveground carbon (AGC). Pulse density influences the acquisition cost of LiDAR, and grid cell size influences AGC prediction using plot-based methods; however, little work has evaluated the effects of LiDAR pulse density and cell size for predicting and mapping AGC in fast-growing Eucalyptus forest plantations. The aim of this study was to evaluate the effect of LiDAR pulse density and grid cell size on AGC prediction accuracy at plot and stand-levels using airborne LiDAR and field data. We used the Random Forest (RF) machine learning algorithm to model AGC using LiDAR-derived metrics from LiDAR collections of 5 and 10 pulses m -2 (RF5 and RF10) and grid cell sizes of 5, 10, 15 and 20 m. The results show that LiDAR pulse density of 5 pulses m -2 provides metrics with similar prediction accuracy for AGC as when using a dataset with 10 pulses m -2 in these fast-growing plantations. Relative root mean square errors (RMSEs) for the RF5 and RF10 were 6.14 and 6.01%, respectively. Equivalence tests showed that the predicted AGC from the training and validation models were equivalent to the observed AGC measurements. The grid cell sizes for mapping ranging from 5 to 20 also did not significantly affect the prediction accuracy of AGC at stand level in this system. LiDAR measurements can be used to predict and map AGC across variable-age Eucalyptus plantations with adequate levels of precision and accuracy using 5 pulses m -2 and a grid cell size of 5 m. The promising results for AGC modeling in this study will allow for greater confidence in comparing AGC estimates with varying LiDAR sampling densities for Eucalyptus plantations and assist in decision making towards more cost effective and efficient forest inventory.

Deformity Angular Ratio Describes the Severity of Spinal Deformity and Predicts the Risk of Neurologic Deficit in Posterior Vertebral Column Resection Surgery.

PubMed

Wang, Xiao-Bin; Lenke, Lawrence G; Thuet, Earl; Blanke, Kathy; Koester, Linda A; Roth, Michael

2016-09-15

Retrospective review of prospectively collected data. To assess the value of the deformity angular ratio (DAR, maximum Cobb measurement divided by number of vertebrae involved) in evaluating the severity of spinal deformity, and predicting the risk of neurologic deficit in posterior vertebral column resection (PVCR). Although the literature has demonstrated that PVCR in spinal deformity patients has achieved excellent outcomes, it is still high risk neurologically. This study, to our knowledge, is the largest series of PVCR patients from a single center, evaluating deformity severity, and potential neurologic deficit risk. A total of 202 consecutive pediatric and adult patients undergoing PVCRs from November 2002 to September 2014 were reviewed. The DAR (coronal DAR, sagittal DAR, and total DAR) was used to evaluate the complexity of the deformity. The incidence of spinal cord monitoring (SCM) events was 20.5%. Eight patients (4.0%) had new neurologic deficits. Patients with a high total DAR (≥25) were significantly younger (20.3 vs. 29.0 yr, P = 0.001), had more severe coronal and sagittal deformities, were more myelopathic (33.3% vs. 11.7%, P = 0.000), needed larger vertebral resections (1.8 vs. 1.3, P = 0.000), and had a significantly higher rate of SCM events than seen in the low total DAR (<25) patients (41.1% vs. 10.8%; P = 0.000). Patients with a high sagittal DAR (≥15) also had a significantly higher rate of SCM events (34.0% vs. 15.1%, P = 0.005) and a greater chance of neurologic deficits postoperatively (12.5% vs. 0, P = 0.000). For patients undergoing a PVCR, the DAR can be used to quantify the angularity of the spinal deformity, which is strongly correlated to the risk of neurologic deficits. Patients with a total DAR greater than or equal to 25 or sagittal DAR greater than or equal to 15 are at much higher risk for intraoperative SCM events and new neurologic deficits. 3.

Let’s agree on the casing of Lidar

USGS Publications Warehouse

Deering, Carol; Stoker, Jason M.

2014-01-01

Is it lidar, Lidar, LiDAR, LIDAR, LiDar, LiDaR, or liDAR? A comprehensive review of the scientific/technical literature reveals seven different casings of this short form for light detection and ranging. And there could be more.

Infrastructure Investment Protection with LiDAR

DOT National Transportation Integrated Search

2012-10-15

The primary goal of this research effort was to explore the wide variety of uses of LiDAR technology and to evaluate their : applicability to NCDOT practices. NCDOT can use this information about LiDAR in determining how and when the : technology can...

Assessing LiDAR elevation data for KDOT applications.

DOT National Transportation Integrated Search

2013-02-01

LiDAR-based elevation surveys are a cost-effective means for mapping topography over large areas. LiDAR : surveys use an airplane-mounted or ground-based laser radar unit to scan terrain. Post-processing techniques are : applied to remove vegetation ...

47 CFR 25.164 - Milestones.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Milestones. (a) Licensees of geostationary orbit satellite systems other than DBS and DARS satellite systems.... (b) Licensees of non-geostationary orbit satellite systems other than DBS and DARS satellite systems... both non-geostationary orbit satellites and geostationary orbit satellites, other than DBS and DARS...

47 CFR 25.164 - Milestones.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Milestones. (a) Licensees of geostationary orbit satellite systems other than DBS and DARS satellite systems.... (b) Licensees of non-geostationary orbit satellite systems other than DBS and DARS satellite systems... both non-geostationary orbit satellites and geostationary orbit satellites, other than DBS and DARS...

47 CFR 25.164 - Milestones.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Milestones. (a) Licensees of geostationary orbit satellite systems other than DBS and DARS satellite systems.... (b) Licensees of non-geostationary orbit satellite systems other than DBS and DARS satellite systems... both non-geostationary orbit satellites and geostationary orbit satellites, other than DBS and DARS...

47 CFR 25.164 - Milestones.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Milestones. (a) Licensees of geostationary orbit satellite systems other than DBS and DARS satellite systems.... (b) Licensees of non-geostationary orbit satellite systems other than DBS and DARS satellite systems... both non-geostationary orbit satellites and geostationary orbit satellites, other than DBS and DARS...

LiDAR for Air Quality Measurements

DOT National Transportation Integrated Search

2017-02-02

The overall goal of this research is to investigate a unique light detection and ranging (LiDAR) technology for ambient air quality measurement of particulate matter. The ODU team has recently received a state-of-the-art elastic LiDAR from NASA Langl...

Using Remote Sensing to Visualize and Extract Building Inventories of Urban Areas for Disaster Planning and Response

NASA Astrophysics Data System (ADS)

Lang, A. F.; Salvaggio, C.

2016-12-01

Climate change, skyrocketing global population, and increasing urbanization have set the stage for more so-called "mega-disasters." We possess the knowledge to mitigate and predict the scope of these events, and recent advancements in remote sensing can inform these efforts. Satellite and aerial imagery can be obtained anywhere of interest; unmanned aerial systems can be deployed quickly; and improved sensor resolutions and image processing techniques allow close examination of the built environment. Combined, these technologies offer an unprecedented ability for the disaster community to visualize, assess, and communicate risk. Disaster mitigation and response efforts rely on an accurate representation of the built environment, including knowledge of building types, structural characteristics, and juxtapositions to known hazards. The use of remote sensing to extract these inventory data has come far in the last five years. Researchers in the Digital Imaging and Remote Sensing (DIRS) group at the Rochester Institute of Technology are meeting the needs of the disaster community through the development of novel image processing methods capable of extracting detailed information of individual buildings. DIRS researchers have pioneered the ability to generate three-dimensional building models from point cloud imagery (e.g., LiDAR). This method can process an urban area and recreate it in a navigable virtual reality environment such as Google Earth within hours. Detailed geometry is obtained for individual structures (e.g., footprint, elevation). In a recent step forward, these geometric data can now be combined with imagery from other sources, such as high resolution or multispectral imagery. The latter ascribes a spectral signature to individual pixels, suggesting construction material. Ultimately, these individual building data are amassed over an entire region, facilitating aggregation and risk modeling analyses. The downtown region of Rochester, New York is presented as a case study. High resolution optical, LiDAR, and multi-spectral imagery was captured of this region. Using the techniques described, these imagery sources are combined and processed to produce a holistic representation of the built environment, inclusive of individual building characteristics.

Prevalence of intestinal parasitic infections and associated risk factors among students at Dona Berber primary school, Bahir Dar, Ethiopia.

PubMed

Hailegebriel, Tamirat

2017-05-23

Intestinal parasitic infections are still one of the major health concerns in developing countries. Monitoring of intestinal parasitic infection and associated risk factors are essential for intervention strategies. Therefore, the aim of this study was to assess the prevalence of intestinal parasitic infection and associated risk factors among students at Dona Berber primary school, Bahir Dar, Ethiopia. School based cross-sectional study was conducted among students at Dona Berber primary school from October 2015 to June 2016. Three hundred fifty nine students were involved in the study by providing stool specimens and detailed personal information. Students were selected by stratified and systematic random sampling method. Fresh stool samples were collected from each student and processed by formal-ether fecal concentration technique. Data were analyzed using SPSS version 20.0 statistical software and p value <0.05 were used as statistically significant. Among the 359 students participated in the study, 235 (65.5%) were infected by one or more intestinal parasites. The rates of single and double parasitic infections among students were 49.6% and 16.2%, respectively. The most prevalent parasite detected in the study was E. histolytica/dispar (24.5%) followed by hookworm (22.8%). Among the different variables assessed in the study, family size of 6 (AOR = 4.90; 95% CI, 2.03-11.83), irregularly shoe wearing habit (AOR = 2.85; 95% CI, 1.53-5.32) and unclean finger nail (AOR = 3.68; 95% CI, 1.87-7.26) were independently predict intestinal parasitic infections. Student drinking well water (AOR = 2.51; 95% CI, 2.30-4.86) and unclean finger nail (AOR = 4.42; 95% CI, 2.55-7.65) were strongly associated with E. histolytica/dispar infection. Likewise, irregular shoe wearing habit (AOR = 14.13; 95% CI, 7.06-28.29) was strongly associated with hookworm infections. High prevalence of intestinal parasitic infection among the study participants demands improvement of health education, environmental sanitation and quality of water sources.

A comparison of the accuracy of pixel based and object based classifications of integrated optical and LiDAR data

NASA Astrophysics Data System (ADS)

Gajda, Agnieszka; Wójtowicz-Nowakowska, Anna

2013-04-01

A comparison of the accuracy of pixel based and object based classifications of integrated optical and LiDAR data Land cover maps are generally produced on the basis of high resolution imagery. Recently, LiDAR (Light Detection and Ranging) data have been brought into use in diverse applications including land cover mapping. In this study we attempted to assess the accuracy of land cover classification using both high resolution aerial imagery and LiDAR data (airborne laser scanning, ALS), testing two classification approaches: a pixel-based classification and object-oriented image analysis (OBIA). The study was conducted on three test areas (3 km2 each) in the administrative area of Kraków, Poland, along the course of the Vistula River. They represent three different dominating land cover types of the Vistula River valley. Test site 1 had a semi-natural vegetation, with riparian forests and shrubs, test site 2 represented a densely built-up area, and test site 3 was an industrial site. Point clouds from ALS and ortophotomaps were both captured in November 2007. Point cloud density was on average 16 pt/m2 and it contained additional information about intensity and encoded RGB values. Ortophotomaps had a spatial resolution of 10 cm. From point clouds two raster maps were generated: intensity (1) and (2) normalised Digital Surface Model (nDSM), both with the spatial resolution of 50 cm. To classify the aerial data, a supervised classification approach was selected. Pixel based classification was carried out in ERDAS Imagine software. Ortophotomaps and intensity and nDSM rasters were used in classification. 15 homogenous training areas representing each cover class were chosen. Classified pixels were clumped to avoid salt and pepper effect. Object oriented image object classification was carried out in eCognition software, which implements both the optical and ALS data. Elevation layers (intensity, firs/last reflection, etc.) were used at segmentation stage due to proper wages usage. Thus a more precise and unambiguous boundaries of segments (objects) were received. As a results of the classification 5 classes of land cover (buildings, water, high and low vegetation and others) were extracted. Both pixel-based image analysis and OBIA were conducted with a minimum mapping unit of 10m2. Results were validated on the basis on manual classification and random points (80 per test area), reference data set was manually interpreted using ortophotomaps and expert knowledge of the test site areas.

Applications of High-Resolution LiDAR Data for the Christina River Basin CZO

NASA Astrophysics Data System (ADS)

Hicks, N. S.; Aufdenkampe, A. K.; Hicks, S. D.

2011-12-01

High-resolution LiDAR data allows for fine scale geomorphic assessment over relatively large spatial extents. Previously available DEMs with a resolution of ten meters or more did not provide adequate resolution for geomorphic characterization of small streams and watersheds or the identification of changes in stream morphology over time. High-resolution LiDAR data for a portion of the Christina River Basin Critical Zone Observatory (CRB-CZO) was obtained during both leaf-off and leaf-on time periods in 2010. Topographic data from these flights is being analyzed with the intent of geomorphic applications such as stream morphology, sediment transport studies, and the evaluation of alluvial deposits. These data and resultant products will also be used in hydrologic and biogeochemical modeling and in biologic and biogeochemical studies of these streams, which are long-term study sites. The LiDAR data also facilitate informed instrument placement and will be used for vegetation studies. The LiDAR data for the CRB-CZO has been used to create a variety of LiDAR based topographic data products including TINs and 0.5-m DEMs. LiDAR derived slope and elevation products were combined with LiDAR intensity images to identify stream channel boundaries and stream centerlines for third through first-order streams. High-resolution slope data also aided in floodplain characterization of these small streams. These high precision stream channel and floodplain characterizations would not have been otherwise possible without extensive field surveying. Future LiDAR flights will allow for the identification of changes in channel morphology over time in low order basins. These characterizations are of particular interest in comparisons between forested and meadow reaches, and in studying the effects of changes in land-use on channel morphology. High-resolution LiDAR data allow for the generation of surface characterizations of importance to a wide range of interdisciplinary researchers.

Deflation-activated receptors, not classical inflation-activated receptors, mediate the Hering-Breuer deflation reflex.

PubMed

Yu, Jerry

2016-11-01

Many airway sensory units respond to both lung inflation and deflation. Whether those responses to opposite stimuli come from one sensor (one-sensor theory) or more than one sensor (multiple-sensor theory) is debatable. One-sensor theory is commonly presumed in the literature. This article proposes a multiple-sensor theory in which a sensory unit contains different sensors for sensing different forces. Two major types of mechanical sensors operate in the lung: inflation- and deflation-activated receptors (DARs). Inflation-activated sensors can be further divided into slowly adapting receptors (SARs) and rapidly adapting receptors (RARs). Many SAR and RAR units also respond to lung deflation because they contain DARs. Pure DARs, which respond to lung deflation only, are rare in large animals but are easily identified in small animals. Lung deflation-induced reflex effects previously attributed to RARs should be assigned to DARs (including pure DARs and DARs associated with SARs and RARs) if the multiple-sensor theory is accepted. Thus, based on the information, it is proposed that activation of DARs can attenuate lung deflation, shorten expiratory time, increase respiratory rate, evoke inspiration, and cause airway secretion and dyspnea.

The application of LiDAR to investigate foredune morphology and vegetation

NASA Astrophysics Data System (ADS)

Doyle, Thomas B.; Woodroffe, Colin D.

2018-02-01

LiDAR (Light Detection and Ranging) has been used to investigate coastal landform morphology, evolution, and change for almost a decade. Repeated airborne LiDAR surveys can provide the scientific community with significant observations of how shorelines have evolved, which may then enable forecasts of future patterns of change. However, there have been few studies that have considered the application of this new technology to the specific study of foredune morphology and vegetation. The accuracy and appropriateness of airborne LiDAR needs to be assessed, particularly where the density of vegetation may obscure the underlying topography, prior to interpreting derived geomorphic features. This study: i) tests the vertical accuracy of airborne LiDAR in 37 foredune systems along the coast of south-eastern Australia, and ii) demonstrates that it can be used to describe foredune morphology and vegetation in considerable detail. There was a strong correlation between the remotely-sensed LiDAR-derived elevation and field topographic and vegetation surveys (R2 = 0.96). A protocol for obtaining foredune geomorphic and botanical parameters is described. It enables widespread biogeomorphic characterisation along coasts for which LiDAR data is available, which can benefit both coastal managers and researchers alike.

Georeferenced LiDAR 3D vine plantation map generation.

PubMed

Llorens, Jordi; Gil, Emilio; Llop, Jordi; Queraltó, Meritxell

2011-01-01

The use of electronic devices for canopy characterization has recently been widely discussed. Among such devices, LiDAR sensors appear to be the most accurate and precise. Information obtained with LiDAR sensors during reading while driving a tractor along a crop row can be managed and transformed into canopy density maps by evaluating the frequency of LiDAR returns. This paper describes a proposed methodology to obtain a georeferenced canopy map by combining the information obtained with LiDAR with that generated using a GPS receiver installed on top of a tractor. Data regarding the velocity of LiDAR measurements and UTM coordinates of each measured point on the canopy were obtained by applying the proposed transformation process. The process allows overlap of the canopy density map generated with the image of the intended measured area using Google Earth(®), providing accurate information about the canopy distribution and/or location of damage along the rows. This methodology was applied and tested on different vine varieties and crop stages in two important vine production areas in Spain. The results indicate that the georeferenced information obtained with LiDAR sensors appears to be an interesting tool with the potential to improve crop management processes.

Assessing LiDAR elevation data for KDOT applications : [technical summary].

DOT National Transportation Integrated Search

2013-02-01

LiDAR-based elevation surveys : are a cost-effective means for : mapping topography over large : areas. LiDAR surveys use an : airplane-mounted or ground-based : laser radar unit to scan terrain. : Post-processing techniques are : applied to remove v...

Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters.

PubMed

Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong

2016-05-30

Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R² = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m²), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.

Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data

USGS Publications Warehouse

Hagar, Joan C.; Eskelson, Bianca N.I.; Haggerty, Patricia K.; Nelson, S. Kim; Vesely, David G.

2014-01-01

LiDAR (Light Detection And Ranging) is an emerging remote-sensing tool that can provide fine-scale data describing vertical complexity of vegetation relevant to species that are responsive to forest structure. We used LiDAR data to estimate occupancy probability for the federally threatened marbled murrelet (Brachyramphus marmoratus) in the Oregon Coast Range of the United States. Our goal was to address the need identified in the Recovery Plan for a more accurate estimate of the availability of nesting habitat by developing occupancy maps based on refined measures of nest-strand structure. We used murrelet occupancy data collected by the Bureau of Land Management Coos Bay District, and canopy metrics calculated from discrete return airborne LiDAR data, to fit a logistic regression model predicting the probability of occupancy. Our final model for stand-level occupancy included distance to coast, and 5 LiDAR-derived variables describing canopy structure. With an area under the curve value (AUC) of 0.74, this model had acceptable discrimination and fair agreement (Cohen's κ = 0.24), especially considering that all sites in our sample were regarded by managers as potential habitat. The LiDAR model provided better discrimination between occupied and unoccupied sites than did a model using variables derived from Gradient Nearest Neighbor maps that were previously reported as important predictors of murrelet occupancy (AUC = 0.64, κ = 0.12). We also evaluated LiDAR metrics at 11 known murrelet nest sites. Two LiDAR-derived variables accurately discriminated nest sites from random sites (average AUC = 0.91). LiDAR provided a means of quantifying 3-dimensional canopy structure with variables that are ecologically relevant to murrelet nesting habitat, and have not been as accurately quantified by other mensuration methods.

Detecting understory plant invasion in urban forests using LiDAR

NASA Astrophysics Data System (ADS)

Singh, Kunwar K.; Davis, Amy J.; Meentemeyer, Ross K.

2015-06-01

Light detection and ranging (LiDAR) data are increasingly used to measure structural characteristics of urban forests but are rarely used to detect the growing problem of exotic understory plant invaders. We explored the merits of using LiDAR-derived metrics alone and through integration with spectral data to detect the spatial distribution of the exotic understory plant Ligustrum sinense, a rapidly spreading invader in the urbanizing region of Charlotte, North Carolina, USA. We analyzed regional-scale L. sinense occurrence data collected over the course of three years with LiDAR-derived metrics of forest structure that were categorized into the following groups: overstory, understory, topography, and overall vegetation characteristics, and IKONOS spectral features - optical. Using random forest (RF) and logistic regression (LR) classifiers, we assessed the relative contributions of LiDAR and IKONOS derived variables to the detection of L. sinense. We compared the top performing models developed for a smaller, nested experimental extent using RF and LR classifiers, and used the best overall model to produce a predictive map of the spatial distribution of L. sinense across our country-wide study extent. RF classification of LiDAR-derived topography metrics produced the highest mapping accuracy estimates, outperforming IKONOS data by 17.5% and the integration of LiDAR and IKONOS data by 5.3%. The top performing model from the RF classifier produced the highest kappa of 64.8%, improving on the parsimonious LR model kappa by 31.1% with a moderate gain of 6.2% over the county extent model. Our results demonstrate the superiority of LiDAR-derived metrics over spectral data and fusion of LiDAR and spectral data for accurately mapping the spatial distribution of the forest understory invader L. sinense.

Paleo- and Neo-Tethyan ophiolites of Iran: a progress report

NASA Astrophysics Data System (ADS)

Ghazi, M.; Hassanipak, A.; Babaie, H.

2003-04-01

The Bitlis-Zagros and Alborz stuture zones of Iran mark two collisional plate boundaries in the Alpine-Himalayan orogenic belt. The ophiolites of these zones together with the ophiolites of Makran accretionary prism and Central Iran form discontinuous linear belts of Tethyan oceanic fragments, which form a bridge between the Mediterranean and Himalayan ophiolites. Based on age alone these ophiolites have been divided into less abundant Paleozoic and much more abundant Mesozoic ophiolites. The Paleozoic ophiolites are located along the Alborz orogenic belt [i.e., Rasht and Mashhad ophiolites (297 Ma and 268 Ma)] and near Anarak in Central Iran. which are the remnants of the Paleo-Tethys ocean crust emplaced as result of closure of the Paleo-Tethys between the Turan and the Central Iranian Microplates (CIM). The Mesezoic ophiolites of Iran are more abundant and include the Zagros ophiolites (i.e., Neyriz and the Kermanshah ophiolites which appear to be coeval with the Oman ophiolite obducted onto the Arabian plate (˜96-92 Ma). The Khoy ophiolite in NW Iran which has formation age of Middle to Late Jurrasic (˜159-155 Ma), and emplacement age Albian ages (˜ 109-104 Ma) has a different tectonics than other Zagros ophiolites. Unfragmented ophiolites of the Makran accretionary prism which are located to the south of the Sanandaj-Sirjan microcontinental block, including complexes such as Band-e-Zeyarat/Dar Anar, Ganj and Remeshk/Mokhtarabad (˜140-98 Ma) are similar in age to the Masirah ophiolite (i.e., ˜150-120 Ma). The ophiolites of the Central Iran include those inside of the Sanandaj-Sirjan microcontinental block, such as Shahr-e-Babak (120 Ma), Naien (100 Ma), Baft, Sabzevar in north central Iran (98-70 Ma) and Tchehel Kureh on the eastern boundary of CIM.Geochemically, these ophiolites are quite diverse and show a significant variations in rock composition, representing a wide range of tectonic environment of formation. In terms of radiogenic isotopic data, basalt and gabbros from Neyriz (Zagros), Khoy (NW Zagros ?), and Band-e-Zeyarat (Makran) have Indian Ocean MORB signature.

Appearance of De Geer moraines in southern and western Finland - Implications for reconstructing glacier retreat dynamics

NASA Astrophysics Data System (ADS)

Ojala, Antti E. K.

2016-02-01

LiDAR digital elevation models (DEMs) from southern and western Finland were investigated to map and discriminate features of De Geer moraines, sparser and more scattered end moraines, and larger end moraine features (i.e., ice-marginal complexes). The results indicate that the occurrence and distribution of De Geer moraines and scattered end moraine ridges in Finland are more widespread than previously suggested. This is probably attributed to the ease of detecting and mapping these features with high-resolution DEMs, indicating the efficiency of LiDAR applications in geological and geomorphological studies. The variable appearance and distribution of moraine ridges in Finland support previous interpretations that no single model is likely to be appropriate for the genesis of De Geer moraines at all localities and for all types of end moraines. De Geer moraine appearances and interdistances probably result from a combination of the general rapidity of ice-margin recession during deglaciation, the proglacial water depth in which they were formed, and local glacier dynamics related to climate and terrain topography. The correlation between the varved clay-based rate of deglaciation and interdistances of distinct and regularly spaced De Geer moraine ridges indicates that the rate of deglaciation is probably involved in the De Geer ridge-forming process, but more thorough comparisons are needed to understand the extent to which De Geer interdistances represent an annual rate of ice-margin decay and the rapidity of regional deglaciation.

Developing a Method to Mask Trees in Commercial Multispectral Imagery

NASA Astrophysics Data System (ADS)

Becker, S. J.; Daughtry, C. S. T.; Jain, D.; Karlekar, S. S.

2015-12-01

The US Army has an increasing focus on using automated remote sensing techniques with commercial multispectral imagery (MSI) to map urban and peri-urban agricultural and vegetative features; however, similar spectral profiles between trees (i.e., forest canopy) and other vegetation result in confusion between these cover classes. Established vegetation indices, like the Normalized Difference Vegetation Index (NDVI), are typically not effective in reliably differentiating between trees and other vegetation. Previous research in tree mapping has included integration of hyperspectral imagery (HSI) and LiDAR for tree detection and species identification, as well as the use of MSI to distinguish tree crowns from non-vegetated features. This project developed a straightforward method to model and also mask out trees from eight-band WorldView-2 (1.85 meter x 1.85 meter resolution at nadir) satellite imagery at the Beltsville Agricultural Research Center in Beltsville, MD spanning 2012 - 2015. The study site included tree cover, a range of agricultural and vegetative cover types, and urban features. The modeling method exploits the product of the red and red edge bands and defines accurate thresholds between trees and other land covers. Results show this method outperforms established vegetation indices including the NDVI, Soil Adjusted Vegetation Index, Normalized Difference Water Index, Simple Ratio, and Normalized Difference Red Edge Index in correctly masking trees while preserving the other information in the imagery. This method is useful when HSI and LiDAR collection are not possible or when using archived MSI.

Pollution of water sources due to poor waste management--the case of Dar-es-Salaam.

PubMed

Makule, D E

2000-01-01

Pollution of water sources for the city of Dar-es-Salaam originates from haphazard disposal of solid wastes, discharge of untreated or inadequately treated wastewater to water sources, lack of standard sanitary facilities and poor hygienic practices. Contaminated water used for human consumption can lead to serious health problems e.g. cholera, typhoid, skin diseases, etc., which, in turn, leads to reduced working hours/manpower. This has a direct effect to production output which can lead to a deterioration of local community welfare. Having realised this as a problem, the Government of Tanzania stipulated, in its water policy of 1991, the need for protection of water sources. In achieving this goal, proper waste management was singled out to be of vital importance. Due to economic hardships, however, budget allocation by the central Government could not cover the costs needed for proper handling of waste. This left Tanzania with no alternative other than heavy reliance on donor and bilateral organisations for financial support of programmes. Nevertheless, these sources of funds proved to be unreliable for many different reasons. To deal with these problems, the Government currently emphasises involving local community and NGOs, the formation of stakeholder funds and organisations, and involvement of the private sector. Other efforts are intensification of education programmes to create more awareness to the local communities on the need for protection of water sources. Although at its infancy level, the system is showing some signs of improvement.

Determining Geometric Parameters of Agricultural Trees from Laser Scanning Data Obtained with Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Hadas, E.; Jozkow, G.; Walicka, A.; Borkowski, A.

2018-05-01

The estimation of dendrometric parameters has become an important issue for agriculture planning and for the efficient management of orchards. Airborne Laser Scanning (ALS) data is widely used in forestry and many algorithms for automatic estimation of dendrometric parameters of individual forest trees were developed. Unfortunately, due to significant differences between forest and fruit trees, some contradictions exist against adopting the achievements of forestry science to agricultural studies indiscriminately. In this study we present the methodology to identify individual trees in apple orchard and estimate heights of individual trees, using high-density LiDAR data (3200 points/m2) obtained with Unmanned Aerial Vehicle (UAV) equipped with Velodyne HDL32-E sensor. The processing strategy combines the alpha-shape algorithm, principal component analysis (PCA) and detection of local minima. The alpha-shape algorithm is used to separate tree rows. In order to separate trees in a single row, we detect local minima on the canopy profile and slice polygons from alpha-shape results. We successfully separated 92 % of trees in the test area. 6 % of trees in orchard were not separated from each other and 2 % were sliced into two polygons. The RMSE of tree heights determined from the point clouds compared to field measurements was equal to 0.09 m, and the correlation coefficient was equal to 0.96. The results confirm the usefulness of LiDAR data from UAV platform in orchard inventory.

On validating remote sensing simulations using coincident real data

NASA Astrophysics Data System (ADS)

Wang, Mingming; Yao, Wei; Brown, Scott; Goodenough, Adam; van Aardt, Jan

2016-05-01

The remote sensing community often requires data simulation, either via spectral/spatial downsampling or through virtual, physics-based models, to assess systems and algorithms. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is one such first-principles, physics-based model for simulating imagery for a range of modalities. Complex simulation of vegetation environments subsequently has become possible, as scene rendering technology and software advanced. This in turn has created questions related to the validity of such complex models, with potential multiple scattering, bidirectional distribution function (BRDF), etc. phenomena that could impact results in the case of complex vegetation scenes. We selected three sites, located in the Pacific Southwest domain (Fresno, CA) of the National Ecological Observatory Network (NEON). These sites represent oak savanna, hardwood forests, and conifer-manzanita-mixed forests. We constructed corresponding virtual scenes, using airborne LiDAR and imaging spectroscopy data from NEON, ground-based LiDAR data, and field-collected spectra to characterize the scenes. Imaging spectroscopy data for these virtual sites then were generated using the DIRSIG simulation environment. This simulated imagery was compared to real AVIRIS imagery (15m spatial resolution; 12 pixels/scene) and NEON Airborne Observation Platform (AOP) data (1m spatial resolution; 180 pixels/scene). These tests were performed using a distribution-comparison approach for select spectral statistics, e.g., established the spectra's shape, for each simulated versus real distribution pair. The initial comparison results of the spectral distributions indicated that the shapes of spectra between the virtual and real sites were closely matched.

Applicability Analysis of Cloth Simulation Filtering Algorithm for Mobile LIDAR Point Cloud

NASA Astrophysics Data System (ADS)

Cai, S.; Zhang, W.; Qi, J.; Wan, P.; Shao, J.; Shen, A.

2018-04-01

Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging) data post-processing. Cloth simulation filtering (CSF) algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS) has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM), 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature) for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44 %, 0.77 % and1.20 %. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

Advances in animal ecology from 3D ecosystem mapping with LiDAR

NASA Astrophysics Data System (ADS)

Davies, A.; Asner, G. P.

2015-12-01

The advent and recent advances of Light Detection and Ranging (LiDAR) have enabled accurate measurement of 3D ecosystem structure. Although the use of LiDAR data is widespread in vegetation science, it has only recently (< 14 years) been applied to animal ecology. Despite such recent application, LiDAR has enabled new insights in the field and revealed the fundamental importance of 3D ecosystem structure for animals. We reviewed the studies to date that have used LiDAR in animal ecology, synthesising the insights gained. Structural heterogeneity is most conducive to increased animal richness and abundance, and increased complexity of vertical vegetation structure is more positively influential than traditionally measured canopy cover, which produces mixed results. However, different taxonomic groups interact with a variety of 3D canopy traits and some groups with 3D topography. LiDAR technology can be applied to animal ecology studies in a wide variety of environments to answer an impressive array of questions. Drawing on case studies from vastly different groups, termites and lions, we further demonstrate the applicability of LiDAR and highlight new understanding, ranging from habitat preference to predator-prey interactions, that would not have been possible from studies restricted to field based methods. We conclude with discussion of how future studies will benefit by using LiDAR to consider 3D habitat effects in a wider variety of ecosystems and with more taxa to develop a better understanding of animal dynamics.

Airborne LiDAR reflective linear feature extraction for strip adjustment and horizontal accuracy determination.

DOT National Transportation Integrated Search

2009-02-01

ODOT's Office of Aerial Engineering (OAE) has been using an Opetch 30/70 ALTM airborne LiDAR system for about four years. The introduction of LiDAR technology was a major development towards improving the mapping operations. The overall experiences a...

Stationary LiDAR for traffic and safety applications - vehicles interpretation and tracking.

DOT National Transportation Integrated Search

2014-01-01

The goal of the T-Scan project is to develop a data processing module for a novel LiDAR-based traffic scanner to collect highly accurate microscopic traffic data at road intersections. : T-Scan uses Light Detection and Ranging (LiDAR) technology that...

Reinraumtechnik für die Medizintechnik

NASA Astrophysics Data System (ADS)

Petek, Max; Jungbluth, Martin; Krampe, Erhard

Die Reinraumtechnik ist heute ein unverzichtbarer Bestandteil bei der Fertigung von Produkten der Life Sciences, den Bereichen Pharma, Lebensmittel, Kosmetik und Medizintechnik. In Anbetracht der langen Historie der Medizintechnik ist sie jedoch eine sehr junge Disziplin. Die Bedeutung von Keimen und die richtige Einschätzung ihrer Größe wurden zwar sehr früh bereits durch Paracelsus erkannt, jedoch wurden daraus noch keine speziellen oder kontinuierlich umgesetzten Hygienevorschriften abgeleitet. Die erste bekannte technische Umsetzung von Hygieneempfehlungen geht auf den Franzosen François Nicolas Appert zurück, der eine aseptische Abfüllmethode für Lebensmittel entwickelte und diese 1810 veröffentlichte [1]. Die erste dokumentierte medizinische Umsetzung stellten Hygienevorschriften für Ärzte dar, die Ignaz Philipp Semmelweis nach 1847 in der Wiener Klinik für Geburtshilfe einführte [2].

Automatic Parking of Self-Driving CAR Based on LIDAR

NASA Astrophysics Data System (ADS)

Lee, B.; Wei, Y.; Guo, I. Y.

2017-09-01

To overcome the deficiency of ultrasonic sensor and camera, this paper proposed a method of autonomous parking based on the self-driving car, using HDL-32E LiDAR. First the 3-D point cloud data was preprocessed. Then we calculated the minimum size of parking space according to the dynamic theories of vehicle. Second the rapidly-exploring random tree algorithm (RRT) algorithm was improved in two aspects based on the moving characteristic of autonomous car. And we calculated the parking path on the basis of the vehicle's dynamics and collision constraints. Besides, we used the fuzzy logic controller to control the brake and accelerator in order to realize the stably of speed. At last the experiments were conducted in an autonomous car, and the results show that the proposed automatic parking system is feasible and effective.

Airborne LiDAR reflective linear feature extraction for strip adjustment and horizontal accuracy determination : executive summary.

DOT National Transportation Integrated Search

2009-02-01

The Office of Aerial Engineering (OAE) has been : using an Optech 30/70 ALTM airborne LiDAR system : for about four years. The introduction of LiDAR : technology was a major development towards : improving the mapping operations, and the overall : ex...

LiDAR-guided Archaeological Survey of a Mediterranean Landscape: Lessons from the Ancient Greek Polis of Kolophon (Ionia, Western Anatolia).

PubMed

Grammer, Benedikt; Draganits, Erich; Gretscher, Martin; Muss, Ulrike

2017-01-01

In 2013, an airborne laser scan survey was conducted in the territory of the Ionian city of Kolophon near the western coast of modern Turkey as part of an archaeological survey project carried out by the Mimar Sinan University of Istanbul (Turkey) and the University of Vienna (Austria). Several light detection and ranging (LiDAR) studies have been carried out in the temperate climate zones of Europe, but only a few in Mediterranean landscapes. Our study is based on the first LiDAR survey carried out for an archaeological purpose in Turkey and one of the first in the Mediterranean that have been planned, measured and filtered especially for archaeological research questions. The interpretation of LiDAR data combined with ground-observations proved extremely useful for the detection and documentation of archaeological remains below Mediterranean evergreen vegetation and dense maquis. This article deals with the methodological aspects of interpreting LiDAR data, using the Kolophon data as a case study. We offer a discussion of the strengths and limitations of LiDAR as an archaeological remote sensing method and suggest a best practice model for interpreting LiDAR data in a Mediterranean context. © 2017 The Authors. Archaeological Prospection published by John Wiley & Sons Ltd.

[Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

PubMed

Liu, Feng; Tan, Chang; Lei, Pi-Feng

2014-11-01

Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation.

Diversity Arrays Technology (DArT) for whole-genome profiling of barley

PubMed Central

Wenzl, Peter; Carling, Jason; Kudrna, David; Jaccoud, Damian; Huttner, Eric; Kleinhofs, Andris; Kilian, Andrzej

2004-01-01

Diversity Arrays Technology (DArT) can detect and type DNA variation at several hundred genomic loci in parallel without relying on sequence information. Here we show that it can be effectively applied to genetic mapping and diversity analyses of barley, a species with a 5,000-Mbp genome. We tested several complexity reduction methods and selected two that generated the most polymorphic genomic representations. Arrays containing individual fragments from these representations generated DArT fingerprints with a genotype call rate of 98.0% and a scoring reproducibility of at least 99.8%. The fingerprints grouped barley lines according to known genetic relationships. To validate the Mendelian behavior of DArT markers, we constructed a genetic map for a cross between cultivars Steptoe and Morex. Nearly all polymorphic array features could be incorporated into one of seven linkage groups (98.8%). The resulting map comprised ≈385 unique DArT markers and spanned 1,137 centimorgans. A comparison with the restriction fragment length polymorphism-based framework map indicated that the quality of the DArT map was equivalent, if not superior, to that of the framework map. These results highlight the potential of DArT as a generic technique for genome profiling in the context of molecular breeding and genomics. PMID:15192146

Combining a Complex Network Approach and a SEIR Compartmental Model to link Fast Spreading of Infectious Diseases with Climate Change

NASA Astrophysics Data System (ADS)

Brenner, F.; Hoffmann, P.; Marwan, N.

2016-12-01

Infectious diseases are a major threat to human health. The spreading of airborne diseases has become fast and hard to predict. Global air travelling created a network which allows a pathogen to migrate worldwide in only a few days. Pandemics of SARS (2002/03) and H1N1 (2009) have impressively shown the epidemiological danger in a strongly connected world. In this study we simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human. We use a regular Susceptible-Infected-Recovered (SIR) model and a modified Susceptible-Exposed-Infected-Recovered (SEIR) compartmental approach with the basis of a complex network built by global air traffic data (from openflights.org). Local Disease propagation is modeled with a global population dataset (from SEDAC and MaxMind) and parameterizations of human behavior regarding mobility, contacts and awareness. As a final component we combine the worldwide outbreak simulation with daily averaged climate data from WATCH-Forcing-Data-ERA-Interim (WFDEI) and Coupled Model Intercomparison Project Phase 5 (CMIP5). Here we focus on Influenza-like illnesses (ILI), whose transmission rate has a dependency on relative humidity and temperature. Even small changes in relative humidity are sufficient to trigger significant differences in the global outbreak behavior. Apart from the direct effect of climate change on the transmission of airborne diseases, there are indirect ramifications that alter spreading patterns. For example seasonal changing human mobility is influenced by climate settings.

Comparisons of Simultaneously Acquired Airborne Sfm Photogrammetry and Lidar

NASA Astrophysics Data System (ADS)

Larsen, C. F.

2014-12-01

Digital elevation models (DEMs) created using images from a consumer DSLR camera are compared against simultaneously acquired LiDAR on a number of airborne mapping projects across Alaska, California and Utah. The aircraft used is a Cessna 180, and is equipped with the University of Alaska Geophysical Institute (UAF-GI) scanning airborne LiDAR system. This LiDAR is the same as described in Johnson et al, 2013, and is the principal instrument used for NASA's Operation IceBridge flights in Alaska. The system has been in extensive use since 2009, and is particularly well characterized with dozens of calibration flights and a careful program of boresight angle determination and monitoring. The UAF-GI LiDAR has a precision of +/- 8 cm and accuracy of +/- 15 cm. The photogrammetry DEM simultaneously acquired with the LiDAR relies on precise shutter timing using an event marker input to the IMU associated with the LiDAR system. The photo positions are derived from the fully coupled GPS/IMU processing, which samples at 100 Hz and is able to directly calculate the antenna to image plane offset displacements from the full orientation data. This use of the GPS/IMU solution means that both the LiDAR and Cessna 180 photogrammetry DEM share trajectory input data, however no orientation data nor ground control is used for the photorammetry processing. The photogrammetry DEMs are overlaid on the LiDAR point cloud and analyzed for horizontal shifts or warps relative to the LiDAR. No warping or horizontal shifts have been detectable for a number of photogrammetry DEMs. Vertical offsets range from +/- 30 cm, with a typical standard deviation about that mean of 10 cm or better. LiDAR and photogrammetry function inherently differently over trees and brush, and direct comparisons between the two methods show much larger differences over vegetated areas. Finally, the differences in flight patterns associated with the two methods will be discussed, highlighting the photogrammetry requirements for a well planned grid pattern and the effects of significant end lap and side lap in the imagery coverage.

a View of the Marble-Cake Mantle from the Southeast Indian Ridge

NASA Astrophysics Data System (ADS)

Hanan, B. B.; Graham, D. W.; Hemond, C.; Blichert-Toft, J.; Albarede, F.

2014-12-01

Along the Southeast Indian Ridge, variations in axial depth, crustal thickness, hydrothermal venting [1], basaltic major elements and U-series disequilibria [2] all indicate a west-to-east decrease in magma supply and mantle temperature from the Amsterdam-St. Paul hotspot to the Australian-Antarctic Discordance. Paired Hf-Pb isotopes in closely spaced glasses (5-10 km) from 81-100°E define two populations revealing compositional streaks in the upper mantle [3]. The number density of the streaks follows a Poisson distribution with a characteristic thickness of ~20 km. K/Ti and Na8 do not correlate with Pb or Hf isotopes, and both isotopic domains encompass N- and E-MORB types indicating the variations represent mantle source heterogeneities. 3He/4He varies from 7.5 - 10.2 RA, more than half the range in global MORB away from hotspot influence [4]. No systematic relationship exists between 3He/4He and Pb or Hf isotopes. A general negative correlation between K/Ti and Fe8 for the SEIR resembles that for MORBs globally, with higher K/Ti associated with lower 3He/4He. Collectively the observations suggest the presence of lithologically heterogeneous mantle. Lower 3He/4He derives from a source containing a few percent pyroxenite or ecologite, while 3He/4He > 9 RA arises from peridotite. Mantle convection has folded together distinct composite reservoirs of heterogeneous mantle, and stretched them into streaks that remain discernible units. The mantle 'unit' giving rise to each MORB sample represents a 'mixture of mixtures' with a multi-stage mixing history. Spectral analysis of the length scales of Hf, Pb and He isotopic variability allows a visual representation of this upper mantle 'texture'. The dominant length scales reflect large (1000, 500 km) and regional scale (100-150 km) structures in mantle flow, and sampling of heterogeneities during partial melting (20-30 km). 1-Baker et al., doi:10.1002/2014GC005344; 2-Russo et al., doi:10.1016/j.epsl.2008.11.016; 3-Hanan et al., doi:10.1016/j.epsl.2013.05.028; 4-Graham et al., doi:10.1002/2014GC005264

Systematic Analysis of Rocky Shore Morphology along 700km of Coastline Using LiDAR-derived DEMs

NASA Astrophysics Data System (ADS)

Matsumoto, H.; Dickson, M. E.; Masselink, G.

2016-12-01

Rock shore platforms occur along much of the world's coast and have a long history of study; however, uncertainty remains concerning the relative importance of various formative controls in different settings (e.g. wave erosion, weathering, tidal range, rock resistance, inheritance). Ambiguity is often attributed to intrinsic natural variability and the lack of preserved evidence on eroding rocky shores, but it could also be argued that previous studies are limited in scale, focusing on a small number of local sites, which restricts the potential for insights from broad, regional analyses. Here we describe a method, using LiDAR-derived digital elevation models (DEMs), for analysing shore platform morphology over an unprecedentedly wide area in which there are large variations in environmental conditions. The new method semi-automatically extracts shore platform profiles and systematically conducts morphometric analysis. We apply the method to 700 km of coast in the SW UK that is exposed to (i) highly energetic swell waves to local wind waves, (ii) macro to mega tidal ranges, and (iii) highly resistant igneous rocks to moderately hard sedimentary rocks. Computer programs are developed to estimate mean sea level, mean spring tidal range, wave height, and rock strength along the coastline. Filtering routines automatically select and remove profiles that are unsuitable for analysis. The large data-set of remaining profiles supports broad and systematic investigation of possible controls on platform morphology. Results, as expected, show wide scatter, because many formative controls are in play, but several trends exist that are generally consistent with relationships that have been inferred from local site studies. This paper will describe correlation analysis on platform morphology in relation to environmental conditions and also present a multi-variable empirical model derived from multi linear regression analysis. Interesting matches exist between platform gradients obtained from the field, and empirical model predictions, particularly when morphological variability found in LiDAR-based shore platform morphology analysis is considered. These findings frame a discussion on formative controls of rocky shore morphology.

Immersive Virtual Reality Field Trips in the Geosciences: Integrating Geodetic Data in Undergraduate Geoscience Courses

NASA Astrophysics Data System (ADS)

La Femina, P. C.; Klippel, A.; Zhao, J.; Walgruen, J. O.; Stubbs, C.; Jackson, K. L.; Wetzel, R.

2017-12-01

High-quality geodetic data and data products, including GPS-GNSS, InSAR, LiDAR, and Structure from Motion (SfM) are opening the doors to visualizing, quantifying, and modeling geologic, tectonic, geomorphic, and geodynamic processes. The integration of these data sets with other geophysical, geochemical and geologic data is providing opportunities for the development of immersive Virtual Reality (iVR) field trips in the geosciences. iVR fieldtrips increase accessibility in the geosciences, by providing experiences that allow for: 1) exploration of field locations that might not be tenable for introductory or majors courses; 2) accessibility to outcrops for students with physical disabilities; and 3) the development of online geosciences courses. We have developed a workflow for producing iVR fieldtrips and tools to make quantitative observations (e.g., distance, area, and volume) within the iVR environment. We use a combination of terrestrial LiDAR and SfM data, 360° photos and videos, and other geophysical, geochemical and geologic data to develop realistic experiences for students to be exposed to the geosciences from sedimentary geology to physical volcanology. We present two of our iVR field trips: 1) Inside the Volcano: Exploring monogenetic volcanism at Thrihnukagigar Iceland; and 2) Changes in Depositional Environment in a Sedimentary Sequence: The Reedsville and Bald Eagle Formations, Pennsylvania. The Thrihnukagigar experience provides the opportunity to investigate monogenetic volcanism through the exploration of the upper 125 m of a fissure-cinder cone eruptive system. Students start at the plate boundary scale, then zoom into a single volcano where they can view the 3D geometry from either terrestrial LiDAR or SfM point clouds, view geochemical data and petrologic thins sections of rock samples, and a presentation of data collection and analysis, results and interpretation. Our sedimentary geology experience is based on a field lab from our introductory Physical Geology course for majors in Geoscience and Engineering. The lab explores formation of a turbidite sequence, and the transition to a shallower marine environment using the tools described above and data from SfM and 360° photos. We are evaluating the effectiveness of both iVR field trips on student learning.

Beyond edge effects: landscape controls on forest structure in the southeastern US

NASA Astrophysics Data System (ADS)

Fagan, M. E.; Morton, D. C.; Cook, B.; Masek, J. G.; Zhao, F. A.; Nelson, R.; Huang, C.

2016-12-01

The structure of forest canopies (i.e., their height and complexity) is known to be influenced by a variety of factors, including forest age, species composition, disturbance, edaphic and topographical conditions, and exposure to edge environments. The combined impact of each of these factors on canopy structure is not well characterized for most forest ecosystems, however, which limits our ability to predict the regional impacts of forest fragmentation. The objective of this study was to elucidate the main biophysical drivers of canopy structure across two dominant ecosystems in the southeastern U.S: natural mixed deciduous forests, and industrial conifer plantations. We analyzed spatial changes in canopy structure along aerial transects of LiDAR data ( 3,000 km in all). High-resolution (1 m) LiDAR data from Goddard's LiDAR, Hyperspectral, and Thermal Airborne Imager (G-LiHT) were combined with time series of Landsat imagery to quantify forest type, age, composition, and fragmentation. Forest structural metrics (height, gap fraction, and canopy roughness) were examined across forest types, ages, topography, and decreasing edge exposure. We hypothesized that 1) structural edge effects would be weak in both natural and plantation forest types, and 2) age, composition, and topography would be the dominant influences on natural forest structure. We analyzed all large (>4 ha) fragments from the 8562 distinct forests measured during G-LiHT data collections in 2011 across the southeastern U.S. In general, the relationship between forest structural metrics and edge exposure was highly variable in both natural forests and plantations. However, variability in all structural metrics decreased with distance from an edge. Forest age and topography were strong predictors of canopy structure in natural forests. However plantations tended to be located in sites with limited topographical variation, and thinning disturbances of conifer plantations decreased the strength of the age-structure relationship. We found that canopy structure in our region is influenced by edge effects, but other factors played a larger role in determining forest characteristics. Our results highlight the importance of endogenous, stand-specific processes for forest structure, biomass, and biodiversity in the southeastern U.S.

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase one, volume 3 : use of scanning LiDAR in structural evaluation of bridges.

DOT National Transportation Integrated Search

2009-12-01

This volume introduces several applications of remote bridge inspection technologies studied in : this Integrated Remote Sensing and Visualization (IRSV) study using ground-based LiDAR : systems. In particular, the application of terrestrial LiDAR fo...

Utility of LiDAR for large area forest inventory applications

Treesearch

Nicholas S. Skowronski; Andrew J. Lister

2012-01-01

Multi-resource inventory data are used in conjunction with Light Detection and Ranging (LiDAR) data from the Pennsylvania Department of Natural Resource's PAMAP Program to assess the utility of extensive LiDAR acquisitions for large area forest assessments. Background, justification, and initial study designs are presented. The proposed study will involve three...

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 3 : advanced consideration in LiDAR technology for bridge evaluation.

DOT National Transportation Integrated Search

2012-03-01

This report describes Phase Two enhancement of terrestrial LiDAR scanning for bridge damage : evaluation that was initially developed in Phase One. Considering the spatial and reflectivity : information contained in LiDAR scans, two detection algorit...

Simulated full-waveform lidar compared to Riegl VZ-400 terrestrial laser scans

NASA Astrophysics Data System (ADS)

Kim, Angela M.; Olsen, Richard C.; Béland, Martin

2016-05-01

A 3-D Monte Carlo ray-tracing simulation of LiDAR propagation models the reflection, transmission and ab- sorption interactions of laser energy with materials in a simulated scene. In this presentation, a model scene consisting of a single Victorian Boxwood (Pittosporum undulatum) tree is generated by the high-fidelity tree voxel model VoxLAD using high-spatial resolution point cloud data from a Riegl VZ-400 terrestrial laser scanner. The VoxLAD model uses terrestrial LiDAR scanner data to determine Leaf Area Density (LAD) measurements for small volume voxels (20 cm sides) of a single tree canopy. VoxLAD is also used in a non-traditional fashion in this case to generate a voxel model of wood density. Information from the VoxLAD model is used within the LiDAR simulation to determine the probability of LiDAR energy interacting with materials at a given voxel location. The LiDAR simulation is defined to replicate the scanning arrangement of the Riegl VZ-400; the resulting simulated full-waveform LiDAR signals compare favorably to those obtained with the Riegl VZ-400 terrestrial laser scanner.

Modelling rating curves using remotely sensed LiDAR data

USGS Publications Warehouse

Nathanson, Marcus; Kean, Jason W.; Grabs, Thomas J.; Seibert, Jan; Laudon, Hjalmar; Lyon, Steve W.

2012-01-01

Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage-discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics-based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m-wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90-m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a 'hybrid model' rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see 'below' the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics-based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote locations.

Raster Vs. Point Cloud LiDAR Data Classification

NASA Astrophysics Data System (ADS)

El-Ashmawy, N.; Shaker, A.

2014-09-01

Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the classification results can be achieved by using the proposed approach.

A novel DARS2 mutation in a Japanese patient with leukoencephalopathy with brainstem and spinal cord involvement but no lactate elevation

PubMed Central

Shimojima, Keiko; Higashiguchi, Takafumi; Kishimoto, Kanako; Miyatake, Satoko; Miyake, Noriko; Takanashi, Jun-ichi; Matsumoto, Naomichi; Yamamoto, Toshiyuki

2017-01-01

The mitochondrial aspartyl-tRNA synthetase 2 gene (DARS2) is responsible for leukoencephalopathy with brainstem and spinal cord involvement and lactate elevation (LBSL). A Japanese patient with LBSL showed compound heterozygous DARS2 mutations c.358_359delinsTC (p.Gly120Ser) and c.228-15C>G (splicing error). This provides further evidence that most patients with LBSL show compound heterozygous mutations in DARS2 in association with a common splicing mutation in the splicing acceptor site of intron 2. PMID:29138691

Timely binding of IHF and Fis to DARS2 regulates ATP–DnaA production and replication initiation

PubMed Central

Kasho, Kazutoshi; Fujimitsu, Kazuyuki; Matoba, Toshihiro; Oshima, Taku; Katayama, Tsutomu

2014-01-01

In Escherichia coli, the ATP-bound form of DnaA (ATP–DnaA) promotes replication initiation. During replication, the bound ATP is hydrolyzed to ADP to yield the ADP-bound form (ADP–DnaA), which is inactive for initiation. The chromosomal site DARS2 facilitates the regeneration of ATP–DnaA by catalyzing nucleotide exchange between free ATP and ADP bound to DnaA. However, the regulatory mechanisms governing this exchange reaction are unclear. Here, using in vitro reconstituted experiments, we show that two nucleoid-associated proteins, IHF and Fis, bind site-specifically to DARS2 to activate coordinately the exchange reaction. The regenerated ATP–DnaA was fully active in replication initiation and underwent DnaA–ATP hydrolysis. ADP–DnaA formed heteromultimeric complexes with IHF and Fis on DARS2, and underwent nucleotide dissociation more efficiently than ATP–DnaA. Consistently, mutant analyses demonstrated that specific binding of IHF and Fis to DARS2 stimulates the formation of ATP–DnaA production, thereby promoting timely initiation. Moreover, we show that IHF–DARS2 binding is temporally regulated during the cell cycle, whereas Fis only binds to DARS2 in exponentially growing cells. These results elucidate the regulation of ATP–DnaA and replication initiation in coordination with the cell cycle and growth phase. PMID:25378325

NEON Data Products: Supporting the Validation of GCOS Essential Climate Variables

NASA Astrophysics Data System (ADS)

Petroy, S. B.; Fox, A. M.; Metzger, S.; Thorpe, A.; Meier, C. L.

2014-12-01

The National Ecological Observatory Network (NEON) is a continental-scale ecological observation platform designed to collect and disseminate data that contributes to understanding and forecasting the impacts of climate change, land use change, and invasive species on ecology. NEON will collect in-situ and airborne data over 60 sites across the US, including Alaska, Hawaii, and Puerto Rico. The NEON Biomass, Productivity, and Biogeochemistry protocols currently direct the collection of samples from distributed, gradient, and tower plots at each site, with sampling occurring either multiple times during the growing season, annually, or on three- or five-year centers (e.g. for coarse woody debris). These data are processed into a series of field-derived data products (e.g. Biogeochemistry, LAI, above ground Biomass, etc.), and when combined with the NEON airborne hyperspectral and LiDAR imagery, are used support validation efforts of algorithms for deriving vegetation characteristics from the airborne data. Sites are further characterized using airborne data combined with in-situ tower measurements, to create additional data products of interest to the GCOS community, such as Albedo and fPAR. Presented here are a summary of tower/field/airborne sampling and observation protocols and examples of provisional datasets collected at NEON sites that may be used to support the ongoing validation of GCOS Essential Climate Variables.

Fast and Robust Registration of Multimodal Remote Sensing Images via Dense Orientated Gradient Feature

NASA Astrophysics Data System (ADS)

Ye, Y.

2017-09-01

This paper presents a fast and robust method for the registration of multimodal remote sensing data (e.g., optical, LiDAR, SAR and map). The proposed method is based on the hypothesis that structural similarity between images is preserved across different modalities. In the definition of the proposed method, we first develop a pixel-wise feature descriptor named Dense Orientated Gradient Histogram (DOGH), which can be computed effectively at every pixel and is robust to non-linear intensity differences between images. Then a fast similarity metric based on DOGH is built in frequency domain using the Fast Fourier Transform (FFT) technique. Finally, a template matching scheme is applied to detect tie points between images. Experimental results on different types of multimodal remote sensing images show that the proposed similarity metric has the superior matching performance and computational efficiency than the state-of-the-art methods. Moreover, based on the proposed similarity metric, we also design a fast and robust automatic registration system for multimodal images. This system has been evaluated using a pair of very large SAR and optical images (more than 20000 × 20000 pixels). Experimental results show that our system outperforms the two popular commercial software systems (i.e. ENVI and ERDAS) in both registration accuracy and computational efficiency.

Comparing LiDAR-Generated to ground- surveyed channel cross-sectional profiles in a forested mountain stream

Treesearch

Brian C. Dietterick; Russell White; Ryan Hilburn

2012-01-01

Airborne Light Detection and Ranging (LiDAR) holds promise to provide an alternative to traditional ground-based survey methods for stream channel characterization and some change detection purposes, even under challenging landscape conditions. This study compared channel characteristics measured at 53 ground-surveyed and LiDAR-derived crosssectional profiles located...

LiDAR and Image Point Cloud Comparison

DTIC Science & Technology

2014-09-01

UAV unmanned aerial vehicle USGS United States Geological Survey UTM Universal Transverse Mercator WGS 84 World Geodetic System 1984 WSI...19  1.  Physics of LiDAR Systems ................................................................20  III.  DATA AND SOFTWARE...ground control point GPS Global Positioning System IMU inertial measurements unit LiDAR light detection and ranging MI mutual information MVS

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

Leo, Laura

The University of Notre Dame (ND) scanning LiDAR dataset used for the WFIP2 Campaign is provided. The LiDAR is a Halo Photonics Stream Line Scanning Doppler LiDAR. **It is highly recommended to discuss any planned use of these data with University of Notre Dame scientists**. For more information refer to the attached "WFIP2 Project (lidar.z07)" Readme file.

Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon

USGS Publications Warehouse

Burns, W.J.; Coe, J.A.; Kaya, B.S.; Ma, Liwang

2010-01-01

We examined elevation changes detected from two successive sets of Light Detection and Ranging (LiDAR) data in the northern Coast Range of Oregon. The first set of LiDAR data was acquired during leafon conditions and the second set during leaf-off conditions. We were able to successfully identify and map active landslides using a differential digital elevation model (DEM) created from the two LiDAR data sets, but this required the use of thresholds (0.50 and 0.75 m) to remove noise from the differential elevation data, visual pattern recognition of landslideinduced elevation changes, and supplemental QuickBird satellite imagery. After mapping, we field-verified 88 percent of the landslides that we had mapped with high confidence, but we could not detect active landslides with elevation changes of less than 0.50 m. Volumetric calculations showed that a total of about 18,100 m3 of material was missing from landslide areas, probably as a result of systematic negative elevation errors in the differential DEM and as a result of removal of material by erosion and transport. We also examined the accuracies of 285 leaf-off LiDAR elevations at four landslide sites using Global Positioning System and total station surveys. A comparison of LiDAR and survey data indicated an overall root mean square error of 0.50 m, a maximum error of 2.21 m, and a systematic error of 0.09 m. LiDAR ground-point densities were lowest in areas with young conifer forests and deciduous vegetation, which resulted in extensive interpolations of elevations in the leaf-on, bare-earth DEM. For optimal use of multi-temporal LiDAR data in forested areas, we recommend that all data sets be flown during leaf-off seasons.

The Deformity Angular Ratio: Does It Correlate With High-Risk Cases for Potential Spinal Cord Monitoring Alerts in Pediatric 3-Column Thoracic Spinal Deformity Corrective Surgery?

PubMed

Lewis, Noah D H; Keshen, Sam G N; Lenke, Lawrence G; Zywiel, Michael G; Skaggs, David L; Dear, Taylor E; Strantzas, Samuel; Lewis, Stephen J

2015-08-01

A retrospective analysis. The purpose of this study was to determine whether the deformity angular ratio (DAR) can reliably assess the neurological risks of patients undergoing deformity correction. Identifying high-risk patients and procedures can help ensure that appropriate measures are taken to minimize neurological complications during spinal deformity corrections. Subjectively, surgeons look at radiographs and evaluate the riskiness of the procedure. However, 2 curves of similar magnitude and location can have significantly different risks of neurological deficit during surgery. Whether the curve spans many levels or just a few can significantly influence surgical strategies. Lenke et al have proposed the DAR, which is a measure of curve magnitude per level of deformity. The data from 35 pediatric spinal deformity correction procedures with thoracic 3-column osteotomies were reviewed. Measurements from preoperative radiographs were used to calculate the DAR. Binary logistic regression was used to model the relationship between DARs (independent variables) and presence or absence of an intraoperative alert (dependent variable). In patients undergoing 3-column osteotomies, sagittal curve magnitude and total curve magnitude were associated with increased incidence of transcranial motor evoked potential changes. Total DAR greater than 45° per level and sagittal DAR greater than 22° per level were associated with a 75% incidence of a motor evoked potential alert, with the incidence increasing to 90% with sagittal DAR of 28° per level. In patients undergoing 3-column osteotomies for severe spinal deformities, the DAR was predictive of patients developing intraoperative motor evoked potential alerts. Identifying accurate radiographical, patient, and procedural risk factors in the correction of severe deformities can help prepare the surgical team to improve safety and outcomes when carrying out complex spinal corrections. 3.

Quantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR

USGS Publications Warehouse

Reddy, Ashwan D.; Hawbaker, Todd J.; Wurster, F.; Zhu, Zhiliang; Ward, S.; Newcomb, Doug; Murray, R.

2015-01-01

Peatlands are a major reservoir of global soil carbon, yet account for just 3% of global land cover. Human impacts like draining can hinder the ability of peatlands to sequester carbon and expose their soils to fire under dry conditions. Estimating soil carbon loss from peat fires can be challenging due to uncertainty about pre-fire surface elevations. This study uses multi-temporal LiDAR to obtain pre- and post-fire elevations and estimate soil carbon loss caused by the 2011 Lateral West fire in the Great Dismal Swamp National Wildlife Refuge, VA, USA. We also determine how LiDAR elevation error affects uncertainty in our carbon loss estimate by randomly perturbing the LiDAR point elevations and recalculating elevation change and carbon loss, iterating this process 1000 times. We calculated a total loss using LiDAR of 1.10 Tg C across the 25 km2 burned area. The fire burned an average of 47 cm deep, equivalent to 44 kg C/m2, a value larger than the 1997 Indonesian peat fires (29 kg C/m2). Carbon loss via the First-Order Fire Effects Model (FOFEM) was estimated to be 0.06 Tg C. Propagating the LiDAR elevation error to the carbon loss estimates, we calculated a standard deviation of 0.00009 Tg C, equivalent to 0.008% of total carbon loss. We conclude that LiDAR elevation error is not a significant contributor to uncertainty in soil carbon loss under severe fire conditions with substantial peat consumption. However, uncertainties may be more substantial when soil elevation loss is of a similar or smaller magnitude than the reported LiDAR error.

Independent evaluation of the SNODAS snow depth product using regional scale LiDAR-derived measurements

NASA Astrophysics Data System (ADS)

Hedrick, A.; Marshall, H.-P.; Winstral, A.; Elder, K.; Yueh, S.; Cline, D.

2014-06-01

Repeated Light Detection and Ranging (LiDAR) surveys are quickly becoming the de facto method for measuring spatial variability of montane snowpacks at high resolution. This study examines the potential of a 750 km2 LiDAR-derived dataset of snow depths, collected during the 2007 northern Colorado Cold Lands Processes Experiment (CLPX-2), as a validation source for an operational hydrologic snow model. The SNOw Data Assimilation System (SNODAS) model framework, operated by the US National Weather Service, combines a physically-based energy-and-mass-balance snow model with satellite, airborne and automated ground-based observations to provide daily estimates of snowpack properties at nominally 1 km resolution over the coterminous United States. Independent validation data is scarce due to the assimilating nature of SNODAS, compelling the need for an independent validation dataset with substantial geographic coverage. Within twelve distinctive 500 m × 500 m study areas located throughout the survey swath, ground crews performed approximately 600 manual snow depth measurements during each of the CLPX-2 LiDAR acquisitions. This supplied a dataset for constraining the uncertainty of upscaled LiDAR estimates of snow depth at the 1 km SNODAS resolution, resulting in a root-mean-square difference of 13 cm. Upscaled LiDAR snow depths were then compared to the SNODAS-estimates over the entire study area for the dates of the LiDAR flights. The remotely-sensed snow depths provided a more spatially continuous comparison dataset and agreed more closely to the model estimates than that of the in situ measurements alone. Finally, the results revealed three distinct areas where the differences between LiDAR observations and SNODAS estimates were most drastic, suggesting natural processes specific to these regions as causal influences on model uncertainty.

Surface characteristics modeling and performance evaluation of urban building materials using LiDAR data.

PubMed

Li, Xiaolu; Liang, Yu

2015-05-20

Analysis of light detection and ranging (LiDAR) intensity data to extract surface features is of great interest in remote sensing research. One potential application of LiDAR intensity data is target classification. A new bidirectional reflectance distribution function (BRDF) model is derived for target characterization of rough and smooth surfaces. Based on the geometry of our coaxial full-waveform LiDAR system, the integration method is improved through coordinate transformation to establish the relationship between the BRDF model and intensity data of LiDAR. A series of experiments using typical urban building materials are implemented to validate the proposed BRDF model and integration method. The fitting results show that three parameters extracted from the proposed BRDF model can distinguish the urban building materials from perspectives of roughness, specular reflectance, and diffuse reflectance. A comprehensive analysis of these parameters will help characterize surface features in a physically rigorous manner.

Global stability in a tuberculosis model of imperfect treatment with age-dependent latency and relapse.

PubMed

Ren, Shanjing

In this paper, an SEIR epidemic model for an imperfect treatment disease with age-dependent latency and relapse is proposed. The model is well-suited to model tuberculosis. The basic reproduction number R0 is calculated. We obtain the global behavior of the model in terms of R0. If R0< 1, the disease-free equilibrium is globally asymptotically stable, whereas if R0>1, a Lyapunov functional is used to show that the endemic equilibrium is globally stable amongst solutions for which the disease is present.

A theoretical model for Zika virus transmission

PubMed Central

Khan, Muhammad Altaf; Okosun, K. O.; Islam, Saeed

2017-01-01

In this paper, we present and analyze an SEIR Zika epidemic model. Firstly, we investigate the model with constant controls. The steady states of the model is found to be locally and globally asymptotically stable. Thereafter, we incorporate time dependent controls into the model in order to investigate the optimal effects of bednets, treatments of infective and spray of insecticides on the disease spread. Furthermore, we used Pontryagin’s Maximum Principle to determine the necessary conditions for effective control of the disease. Also, the numerical results were presented. PMID:28977007

Comparing helicopter-borne profiling radar with airborne laser scanner data for forest structure estimation.

NASA Astrophysics Data System (ADS)

Piermattei, Livia; Hollaus, Markus; Pfeifer, Norbert; Chen, Yuwei; Karjalainen, Mika; Hakala, Teemu; Hyyppä, Juha; Wagner, Wolfgang

2017-04-01

Forests are complex ecosystems that show substantial variation with respect to climate, management regime, stand history, disturbance, and needs of local communities. The dynamic processes of growth and disturbance are reflected in the structural components of forests that include the canopy vertical structure and geometry (e.g. size, height, and form), tree position and species diversity. Current remote-sensing systems to measure forest structural attributes include passive optical sensors and active sensors. The technological capabilities of active remote sensing like the ability to penetrate the vegetation and provide information about its vertical structure has promoted an extensive use of LiDAR (Light Detection And Ranging) and radar (RAdio Detection And Ranging) system over the last 20 years. LiDAR measurements from aircraft (airborne laser scanning, ALS) currently represents the primary data source for three-dimensional information on forest vertical structure. Contrary, despite the potential of radar remote sensing, their use is not yet established in forest monitoring. In order to better understand the interaction of pulsed radar with the forest canopy, and to increase the feasibility of this system, the Finnish Geospatial Research Institute has developed a helicopter-borne profiling radar system, called TomoRadar. TomoRadar is capable of recording a canopy-penetrating profile of forests. To georeference the radar measurements the system was equipped with a global navigation satellite system and an inertial measurement unit with a centimeter level accuracy of the flight trajectory. The TomoRadar operates at Ku-band, (wave lengths λ 1.5cm) with two separated parabolic antennas providing co- and cross-polarization modes. The purpose of this work is to investigate the capability of the TomoRadar system, for estimating the forest vertical profile, terrain topography and tree height. We analysed 600 m TomoRadar crosspolarized (i.e. horizontal - vertical) profile, acquired in October 2016 over a boreal test site in Evo, Finland. The intensity of the reflected backscatter energy was used to measure the height canopy distribution within an individual footprint. As the intensity of the backscatter energy from the ground is exceeding the intensity from vegetation, the estimation of canopy height and the forest structure were based on i) a threshold between canopy and ground and ii) a peak analysis of the backscattering profile. ALS data collected simultaneously was used to validate the TomoRadar results (i.e. canopy height) and to obtain elevation ground truth. The first results show a high agreement between ALS and TomoRadar derived canopy heights. The derived knowledge about the energy distribution within the canopy height profile leads to an increased understanding of the interactions between the radar signal and the forest canopy and will support optimization of future radar systems with respect to forest structure observation.

Investigating the influence of LiDAR ground surface errors on the utility of derived forest inventories

Treesearch

Wade T. Tinkham; Alistair M. S. Smith; Chad Hoffman; Andrew T. Hudak; Michael J. Falkowski; Mark E. Swanson; Paul E. Gessler

2012-01-01

Light detection and ranging, or LiDAR, effectively produces products spatially characterizing both terrain and vegetation structure; however, development and use of those products has outpaced our understanding of the errors within them. LiDAR's ability to capture three-dimensional structure has led to interest in conducting or augmenting forest inventories with...

Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale

Treesearch

Lee A. Vierling; Kerri T. Vierling; Patrick Adam; Andrew T. Hudak

2013-01-01

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR...

Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys

Treesearch

Andrew T. Hudak; Eva K. Strand; Lee A. Vierling; John C. Byrne; Jan U. H. Eitel; Sebastian Martinuzzi; Michael J. Falkowski

2012-01-01

Sound forest policy and management decisions to mitigate rising atmospheric CO2 depend upon accurate methodologies to quantify forest carbon pools and fluxes over large tracts of land. LiDAR remote sensing is a rapidly evolving technology for quantifying aboveground biomass and thereby carbon pools; however, little work has evaluated the efficacy of repeat LiDAR...

Status and prospects for LiDAR remote sensing of forested ecosystems

Treesearch

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

2013-01-01

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

Performance modelling of miniaturized flash-imaging lidars for future mars exploration missions

NASA Astrophysics Data System (ADS)

Mitev, V.; Pollini, A.; Haesler, J.; Pereira do Carmo, João.

2017-11-01

Future planetary exploration missions require the support of 3D vision in the GN&C during key spacecraft's proximity phases, namely: i) spacecraft precision and soft Landing on the planet's surface; ii) Rendezvous and Docking (RVD) between a Sample Canister (SC) and an orbiter spacecraft; iii) Rover Navigation (RN) on planetary surface. The imaging LiDARs are among the best candidate for such tasks [1-3]. The combination of measurement requirements and environmental conditions seems to find its optimum in the flash 3D LiDAR architecture. Here we present key steps is the evaluation of novelty light detectors and MOEMS (Micro-Opto- Electro-Mechanical Systems) technologies with respect to LiDAR system performance and miniaturization. The objectives of the project MILS (Miniaturized Imaging LiDAR System, Phase 1) concentrated on the evaluation of novel detection and scanning technologies for the miniaturization of 3D LiDARs intended for planetary mission. Preliminary designs for an elegant breadboard (EBB) for the three tasks stated above (Landing, RVD and RN) were proposed, based on results obtained with a numerical model developed in the project and providing the performances evaluation of imaging LiDARs.

INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm

PubMed Central

Gao, Yanbin; Liu, Shifei; Atia, Mohamed M.; Noureldin, Aboelmagd

2015-01-01

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory. PMID:26389906

Unveiling topographical changes using LiDAR mapping capability: case study of Belaga in Sarawak, East-Malaysia

NASA Astrophysics Data System (ADS)

Ganendra, T. R.; Khan, N. M.; Razak, W. J.; Kouame, Y.; Mobarakeh, E. T.

2016-06-01

The use of Light Detection and Ranging (LiDAR) remote sensing technology to scan and map landscapes has proven to be one of the most popular techniques to accurately map topography. Thus, LiDAR technology is the ultimate method of unveiling the surface feature under dense vegetation, and, this paper intends to emphasize the diverse techniques that can be utilized to elucidate topographical changes over the study area, using multi-temporal airborne full waveform LiDAR datasets collected in 2012 and 2014. Full waveform LiDAR data offers access to an almost unlimited number of returns per shot, which enables the user to explore in detail topographical changes, such as vegetation growth measurement. The study also found out topography changes at the study area due to earthwork activities contributing to soil consolidation, soil erosion and runoff, requiring cautious monitoring. The implications of this study not only concurs with numerous investigations undertaken by prominent researchers to improve decision making, but also corroborates once again that investigations employing multi-temporal LiDAR data to unveil topography changes in vegetated terrains, produce more detailed and accurate results than most other remote sensing data.

INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm.

PubMed

Gao, Yanbin; Liu, Shifei; Atia, Mohamed M; Noureldin, Aboelmagd

2015-09-15

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.

Scaling wood volume estimates from inventory plots to landscapes with airborne LiDAR in temperate deciduous forest.

PubMed

Levick, Shaun R; Hessenmöller, Dominik; Schulze, E-Detlef

2016-12-01

Monitoring and managing carbon stocks in forested ecosystems requires accurate and repeatable quantification of the spatial distribution of wood volume at landscape to regional scales. Grid-based forest inventory networks have provided valuable records of forest structure and dynamics at individual plot scales, but in isolation they may not represent the carbon dynamics of heterogeneous landscapes encompassing diverse land-management strategies and site conditions. Airborne LiDAR has greatly enhanced forest structural characterisation and, in conjunction with field-based inventories, it provides avenues for monitoring carbon over broader spatial scales. Here we aim to enhance the integration of airborne LiDAR surveying with field-based inventories by exploring the effect of inventory plot size and number on the relationship between field-estimated and LiDAR-predicted wood volume in deciduous broad-leafed forest in central Germany. Estimation of wood volume from airborne LiDAR was most robust (R 2  = 0.92, RMSE = 50.57 m 3 ha -1  ~14.13 Mg C ha -1 ) when trained and tested with 1 ha experimental plot data (n = 50). Predictions based on a more extensive (n = 1100) plot network with considerably smaller (0.05 ha) plots were inferior (R 2  = 0.68, RMSE = 101.01 ~28.09 Mg C ha -1 ). Differences between the 1 and 0.05 ha volume models from LiDAR were negligible however at the scale of individual land-management units. Sample size permutation tests showed that increasing the number of inventory plots above 350 for the 0.05 ha plots returned no improvement in R 2 and RMSE variability of the LiDAR-predicted wood volume model. Our results from this study confirm the utility of LiDAR for estimating wood volume in deciduous broad-leafed forest, but highlight the challenges associated with field plot size and number in establishing robust relationships between airborne LiDAR and field derived wood volume. We are moving into a forest management era where field-inventory and airborne LiDAR are inextricably linked, and we encourage field inventory campaigns to strive for increased plot size and give greater attention to precise stem geolocation for better integration with remote sensing strategies.

Geotechnical applications of LiDAR pertaining to geomechanical evaluation and hazard identification

NASA Astrophysics Data System (ADS)

Lato, Matthew J.

Natural hazards related to ground movement that directly affect the safety of motorists and highway infrastructure include, but are not limited to, rockfalls, rockslides, debris flows, and landslides. This thesis specifically deals with the evaluation of rockfall hazards through the evaluation of LiDAR data. Light Detection And Ranging (LiDAR) is an imaging technology that can be used to delineate and evaluate geomechanically-controlled hazards. LiDAR has been adopted to conduct hazard evaluations pertaining to rockfall, rock-avalanches, debris flows, and landslides. Characteristics of LiDAR surveying, such as rapid data acquisition rates, mobile data collection, and high data densities, pose problems to traditional CAD or GIS-based mapping methods. New analyses methods, including tools specifically oriented to geomechanical analyses, are needed. The research completed in this thesis supports development of new methods, including improved survey techniques, innovative software workflows, and processing algorithms to aid in the detection and evaluation of geomechanically controlled rockfall hazards. The scientific research conducted between the years of 2006-2010, as presented in this thesis, are divided into five chapters, each of which has been published by or is under review by an international journal. The five research foci are: (i) geomechanical feature extraction and analysis using LiDAR data in active mining environments; (ii) engineered monitoring of rockfall hazards along transportation corridors: using mobile terrestrial LiDAR; (iii) optimization of LiDAR scanning and processing for automated structural evaluation of discontinuities in rockmasses; (iv) location orientation bias when using static LiDAR data for geomechanical analysis; and (v) evaluating roadside rockmasses for rockfall hazards from LiDAR data: optimizing data collection and processing protocols. The research conducted pertaining to this thesis has direct and significant implications with respect to numerous engineering projects that are affected by geomechanical stability issues. The ability to efficiently and accurately map discontinuities, detect changes, and standardize roadside geomechanical stability analyses from remote locations will fundamentally change the state-of-practice of geotechnical investigation workflows and repeatable monitoring. This, in turn, will lead to earlier detection and definition of potential zones of instability, will allow for progressive monitoring and risk analysis, and will indicate the need for pro-active slope improvement and stabilization.

[Not Available].

PubMed

Sendrós Madroño, José M

2016-06-03

La atención nutricional en el paciente oncohematológico debe formar parte del tratamiento global del paciente. Las alteraciones debidas a la localización de la neoplasia y los efectos secundarios del tratamiento oncoespecífico muchas veces dificultan o impiden la alimentación oral. Esto puede dar lugar a una desnutrición y es de gran importancia su detección, valoración e intervención temprana. El primer paso en la intervención nutricional es el consejo dietético. Este artículo muestra qué aspectos deben tenerse en cuenta para poder elaborar un consejo dietético y la importancia de que este sea individualizado. Se describen como ejemplo cuatro situaciones especiales, donde es necesario trasladar las recomendaciones nutricionales a un plan dietético. También se incide en el uso de los probióticos en pacientes inmunocomprometidos.

Parenting practices and styles associated with adolescent sexual health in Dar es Salaam, Tanzania.

PubMed

Kajula, Lusajo J; Darling, Nancy; Kaaya, Sylvia F; De Vries, Hein

2016-11-01

Parenting styles and practices are suggested to be important predictors of adolescent sexual health, mostly in Europe and North America. Limited research has been conducted on these processes in Sub-Saharan Africa, which has different patterns of adolescent sexual behavior and family traditions. This study qualitatively explored parenting practices and styles associated with adolescent sexual health in Tanzania, with 12 adolescents and 12 parents of adolescents. The themes we identified from the data included parental monitoring, preventive, and punitive behaviors. Parents were reported to use mostly punitive behaviors to correct or prohibit sexual behavior; parents also set clear rules about appropriate sexual behavior (e.g., modesty and abstinence). Parents were also reported to closely monitor their adolescent children's friendships and sexual behavior to minimize sexual behavior. However, some parents also engaged in positive preventive practices aimed at protecting their adolescent children.

The New Physics

NASA Astrophysics Data System (ADS)

Fraser, Gordon

2006-04-01

Introduction Gordon Fraser; Part I. Matter and the Universe: 1. Cosmology Wendy Freedman and Rocky Kolb; 2. Gravity Ronald Adler; 3. Astrophysics Arnon Dar; 4. Particles and the standard model Chris Quigg; 5. Superstrings Michael Green; Part II. Quantum Matter: 6. Atoms and photons Claude Cohen-Tannoudji and Jean Dalibard; 7. The quantum world of ultra-cold atoms Christopher Foot and William Phillips; 8. Superfluidity Henry Hall; 9. Quantum phase transitions Subir Sachdev; Part III. Quanta in Action: 10. Quantum entanglement Anton Zeilinger; 11. Quanta, ciphers and computers Artur Ekert; 12. Small-scale structure and nanoscience Yoseph Imry; Part IV. Calculation and Computation: 13. Nonlinearity Henry Abarbanel; 14. Complexity Antonio Politi; 15. Collaborative physics, e-science and the grid Tony Hey and Anne Trefethen; Part V. Science in Action: 16. Biophysics Cyrus Safinya; 17. Medical physics Nicolaj Pavel; 18. Physics and materials Robert Cahn; 19. Physics and society Ugo Amaldi.

The New Physics

NASA Astrophysics Data System (ADS)

Fraser, Gordon

2009-08-01

Introduction Gordon Fraser; Part I. Matter and the Universe: 1. Cosmology Wendy Freedman and Rocky Kolb; 2. Gravity Ronald Adler; 3. Astrophysics Arnon Dar; 4. Particles and the standard model Chris Quigg; 5. Superstrings Michael Green; Part II. Quantum Matter: 6. Atoms and photons Claude Cohen-Tannoudji and Jean Dalibard; 7. The quantum world of ultra-cold atoms Christopher Foot and William Phillips; 8. Superfluidity Henry Hall; 9. Quantum phase transitions Subir Sachdev; Part III. Quanta in Action: 10. Quantum entanglement Anton Zeilinger; 11. Quanta, ciphers and computers Artur Ekert; 12. Small-scale structure and nanoscience Yoseph Imry; Part IV. Calculation and Computation: 13. Nonlinearity Henry Abarbanel; 14. Complexity Antonio Politi; 15. Collaborative physics, e-science and the grid Tony Hey and Anne Trefethen; Part V. Science in Action: 16. Biophysics Cyrus Safinya; 17. Medical physics Nicolaj Pavel; 18. Physics and materials Robert Cahn; 19. Physics and society Ugo Amaldi.

Real-time depth processing for embedded platforms

NASA Astrophysics Data System (ADS)

Rahnama, Oscar; Makarov, Aleksej; Torr, Philip

2017-05-01

Obtaining depth information of a scene is an important requirement in many computer-vision and robotics applications. For embedded platforms, passive stereo systems have many advantages over their active counterparts (i.e. LiDAR, Infrared). They are power efficient, cheap, robust to lighting conditions and inherently synchronized to the RGB images of the scene. However, stereo depth estimation is a computationally expensive task that operates over large amounts of data. For embedded applications which are often constrained by power consumption, obtaining accurate results in real-time is a challenge. We demonstrate a computationally and memory efficient implementation of a stereo block-matching algorithm in FPGA. The computational core achieves a throughput of 577 fps at standard VGA resolution whilst consuming less than 3 Watts of power. The data is processed using an in-stream approach that minimizes memory-access bottlenecks and best matches the raster scan readout of modern digital image sensors.

Ionospheric irregularities over Bahir Dar, Ethiopia during selected geomagnetic storms

NASA Astrophysics Data System (ADS)

Kassa, Tsegaye; Damtie, Baylie

2017-07-01

We have analyzed the effect of geomagnetic storms on the occurrence of ionospheric irregularities by considering seven case studies in the period of 2013-2014 over Bahir Dar, Ethiopia (11° N , 38° E). We inferred the irregularity indices from GPS phase fluctuation by computing the median of 1-min rate of change of total electron content (fp) along the ray paths from all satellites observed. The Fp -index was calculated as an hourly average fp -index values along the ray paths from all satellites observed during each hour. Our results revealed that the irregularity level was inhibited during post sunset hours of the main phase of the storms we considered. On average, the irregularity index has dropped from 400 (0.4 TECU/min) during quiet time to 50 (0.05 TECU/min) on disturbed time with an amount of 350 (0.35 TECU/min). However, in some of the cases, immediately after the onset of the storm, we observed the enhancement of irregularities. We found that only the observations on 01 June 2013 and 19 February 2014 exhibited a correspondence of the time of occurrence of the minimum of the Dst-index with inhibition of irregularities noted by other researchers. Our observations of the enhancement of irregularities on 17 March 2013 and 19 February 2014 can partly be explained by the orientation of the IMF BZ . Other measurements such as neutral wind, electric field are required to explain the observations on 29 June 2013, 06 July 2013, 09 November 2013 and 27 February 2014.

Toward Improved Hyperspectral Analysis in Semiarid Systems

NASA Astrophysics Data System (ADS)

Glenn, N. F.; Mitchell, J.

2012-12-01

Idaho State University's Boise Center Aerospace Laboratory (BCAL) has processed and applied hyperspectral data for a variety of biophysical sciences in semiarid systems over the past 10 years. HyMap hyperspectral data have been used in most of these studies, along with AVIRIS, CASI, and PIKA-II data. Our studies began with the detection of individual weed species, such as leafy spurge, corroborated with extensive field analysis, including spectrometer data. Early contributions to the field of hyperspectral analysis included the use of: time-series datasets and classification threshold methods for target detection, and subpixel analysis for characterizing weed invasions and post-fire vegetation and soil conditions. Subsequent studies optimized subpixel unmixing performance using spectral subsetting and vegetation abundance investigations. More recent studies have extended the application of hyperspectral data from individual plant species detection to identification of biochemical constituents. We demonstrated field and airborne hyperspectral Nitrogen absorption in sagebrush using combinations of data reduction and spectral transformation techniques (i.e., continuum removal, derivative analysis, partial least squares regression). In spite of these and many other successful demonstrations, gaps still exist in effective species level discrimination due to the high complexity of soil and nonlinear mixing in semiarid shrubland. BCAL studies are currently focusing on complimenting narrowband vegetation indices with LiDAR (light detection and ranging, both airborne and ground-based) derivatives to improve vegetation cover predictions. Future combinations of LiDAR and hyperspectral data will involve exploring the full range spectral information and serve as an integral step in scaling shrub biomass estimates from plot to landscape and regional scales.

Integrating GIS-based geologic mapping, LiDAR-based lineament analysis and site specific rock slope data to delineate a zone of existing and potential rock slope instability located along the grandfather mountain window-Linville Falls shear zone contact, Southern Appalachian Mountains, Watauga County, North Carolina

USGS Publications Warehouse

Gillon, K.A.; Wooten, R.M.; Latham, R.L.; Witt, A.W.; Douglas, T.J.; Bauer, J.B.; Fuemmeler, S.J.

2009-01-01

Landslide hazard maps of Watauga County identify >2200 landslides, model debris flow susceptibility, and evaluate a 14km x 0.5km zone of existing and potential rock slope instability (ZEPRSI) near the Town of Boone. The ZEPRSI encompasses west-northwest trending (WNWT) topographic ridges where 14 active/past-active rock/weathered rock slides occur mainly in rocks of the Grandfather Mountain Window (GMW). The north side of this ridgeline is the GMW / Linville Falls Fault (LFF) contact. Sheared rocks of the Linville Falls Shear Zone (LFSZ) occur along the ridge and locally in the valley north of the contact. The valley is underlain principally by layered granitic gneiss comprising the Linville Falls/Beech Mountain/Stone Mountain Thrust Sheet. The integration of ArcGIS??? - format digital geologic and lineament mapping on a 6m LiDAR (Light Detecting and Ranging) digital elevation model (DEM) base, and kinematic analyses of site specific rock slope data (e.g., presence and degree of ductile and brittle deformation fabrics, rock type, rock weathering state) indicate: WNWT lineaments are expressions of a regionally extensive zone of fractures and faults; and ZEPRSI rock slope failures concentrate along excavated, north-facing LFF/LFSZ slopes where brittle fabrics overprint older metamorphic foliations, and other fractures create side and back release surfaces. Copyright 2009 ARMA, American Rock Mechanics Association.

Ground based remote sensing and physiological measurements provide novel insights into canopy photosynthetic optimization in arctic shrubs

NASA Astrophysics Data System (ADS)

Magney, T. S.; Griffin, K. L.; Boelman, N.; Eitel, J.; Greaves, H.; Prager, C.; Logan, B.; Oliver, R.; Fortin, L.; Vierling, L. A.

2014-12-01

Because changes in vegetation structure and function in the Arctic are rapid and highly dynamic phenomena, efforts to understand the C balance of the tundra require repeatable, objective, and accurate remote sensing methods for estimating aboveground C pools and fluxes over large areas. A key challenge addressing the modelling of aboveground C is to utilize process-level information from fine-scale studies. Utilizing information obtained from high resolution remote sensing systems could help to better understand the C source/sink strength of the tundra, which will in part depend on changes in photosynthesis resulting from the partitioning of photosynthetic machinery within and among deciduous shrub canopies. Terrestrial LiDAR and passive hyperspectral remote sensing measurements offer an effective, repeatable, and scalable method to understand photosynthetic performance and partitioning at the canopy scale previously unexplored in arctic systems. Using a 3-D shrub canopy model derived from LiDAR, we quantified the light regime of leaves within shrub canopies to gain a better understanding of how light interception varies in response to the Arctic's complex radiation regime. This information was then coupled with pigment sampling (i.e., xanthophylls, and Chl a/b) to evaluate the optimization of foliage photosynthetic capacity within shrub canopies due to light availability. In addition, a lab experiment was performed to validate evidence of canopy level optimization via gradients of light intensity and leaf light environment. For this, hyperspectral reflectance (photochemical reflectance index (PRI)), and solar induced fluorescence (SIF)) was collected in conjunction with destructive pigment samples (xanthophylls) and chlorophyll fluorescence measurements in both sunlit and shaded canopy positions.

Tree species classification in subtropical forests using small-footprint full-waveform LiDAR data

NASA Astrophysics Data System (ADS)

Cao, Lin; Coops, Nicholas C.; Innes, John L.; Dai, Jinsong; Ruan, Honghua; She, Guanghui

2016-07-01

The accurate classification of tree species is critical for the management of forest ecosystems, particularly subtropical forests, which are highly diverse and complex ecosystems. While airborne Light Detection and Ranging (LiDAR) technology offers significant potential to estimate forest structural attributes, the capacity of this new tool to classify species is less well known. In this research, full-waveform metrics were extracted by a voxel-based composite waveform approach and examined with a Random Forests classifier to discriminate six subtropical tree species (i.e., Masson pine (Pinus massoniana Lamb.)), Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), Slash pines (Pinus elliottii Engelm.), Sawtooth oak (Quercus acutissima Carruth.) and Chinese holly (Ilex chinensis Sims.) at three levels of discrimination. As part of the analysis, the optimal voxel size for modelling the composite waveforms was investigated, the most important predictor metrics for species classification assessed and the effect of scan angle on species discrimination examined. Results demonstrate that all tree species were classified with relatively high accuracy (68.6% for six classes, 75.8% for four main species and 86.2% for conifers and broadleaved trees). Full-waveform metrics (based on height of median energy, waveform distance and number of waveform peaks) demonstrated high classification importance and were stable among various voxel sizes. The results also suggest that the voxel based approach can alleviate some of the issues associated with large scan angles. In summary, the results indicate that full-waveform LIDAR data have significant potential for tree species classification in the subtropical forests.

Multisensor Equipped Uav/ugv for Automated Exploration

NASA Astrophysics Data System (ADS)

Batzdorfer, S.; Bobbe, M.; Becker, M.; Harms, H.; Bestmann, U.

2017-08-01

The usage of unmanned systems for exploring disaster scenarios has become more and more important in recent times as a supporting system for action forces. These systems have to offer a well-balanced relationship between the quality of support and additional workload. Therefore within the joint research project ANKommEn - german acronym for Automated Navigation and Communication for Exploration - a system for exploration of disaster scenarios is build-up using multiple UAV und UGV controlled via a central ground station. The ground station serves as user interface for defining missions and tasks conducted by the unmanned systems, equipped with different environmental sensors like cameras - RGB as well as IR - or LiDAR. Depending on the exploration task results, in form of pictures, 2D stitched orthophoto or LiDAR point clouds will be transmitted via datalinks and displayed online at the ground station or will be processed in short-term after a mission, e.g. 3D photogrammetry. For mission planning and its execution, UAV/UGV monitoring and georeferencing of environmental sensor data, reliable positioning and attitude information is required. This is gathered using an integrated GNSS/IMU positioning system. In order to increase availability of positioning information in GNSS challenging scenarios, a GNSS-Multiconstellation based approach is used, amongst others. The present paper focuses on the overall system design including the ground station and sensor setups on the UAVs and UGVs, the underlying positioning techniques as well as 2D and 3D exploration based on a RGB camera mounted on board the UAV and its evaluation based on real world field tests.

Photogrammetric DSM denoising

NASA Astrophysics Data System (ADS)

Nex, F.; Gerke, M.

2014-08-01

Image matching techniques can nowadays provide very dense point clouds and they are often considered a valid alternative to LiDAR point cloud. However, photogrammetric point clouds are often characterized by a higher level of random noise compared to LiDAR data and by the presence of large outliers. These problems constitute a limitation in the practical use of photogrammetric data for many applications but an effective way to enhance the generated point cloud has still to be found. In this paper we concentrate on the restoration of Digital Surface Models (DSM), computed from dense image matching point clouds. A photogrammetric DSM, i.e. a 2.5D representation of the surface is still one of the major products derived from point clouds. Four different algorithms devoted to DSM denoising are presented: a standard median filter approach, a bilateral filter, a variational approach (TGV: Total Generalized Variation), as well as a newly developed algorithm, which is embedded into a Markov Random Field (MRF) framework and optimized through graph-cuts. The ability of each algorithm to recover the original DSM has been quantitatively evaluated. To do that, a synthetic DSM has been generated and different typologies of noise have been added to mimic the typical errors of photogrammetric DSMs. The evaluation reveals that standard filters like median and edge preserving smoothing through a bilateral filter approach cannot sufficiently remove typical errors occurring in a photogrammetric DSM. The TGV-based approach much better removes random noise, but large areas with outliers still remain. Our own method which explicitly models the degradation properties of those DSM outperforms the others in all aspects.

EnviroAtlas -- Memphis, TN (2012) -- One Meter Resolution Urban Land Cover Data Web Service

EPA Pesticide Factsheets

This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas ). The Memphis, TN EnviroAtlas One Meter-scale Urban Land Cover (MULC) dataset comprises 2,733 km2 around the city of Memphis, surrounding towns, and rural areas. These leaf-on LC data and maps were derived from 1-m pixel, four-band (red, green, blue, and near-infrared) aerial photography acquired from the United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) on four dates in 2012: June 15, June 18, June 21 and June 23, and one date in 2013: July 12. Three separate LiDAR (Light Detection and Ranging) data sets collected on February 19, 2009 00e2?? August 2, 2010, December 1-2, 2011 and January 23-24, 2012 were integrated for Shelby Co., TN, Crittenden Co., AR, and DeSoto Co, MS. Five MULC classes were mapped directly from the NAIP and LiDAR data: Water, Impervious, Soil, Trees, and Grass/Herbaceous. Agriculture was derived from USDA Common Land Unit (CLU) data. Woody and emergent wetlands were copied from existing National Wetlands Inventory (NWI) data. Analysis of a random sampling of 612 photo-interpreted land cover reference points yielded an overall users accuracy of 86.9%. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-u

EnviroAtlas -- Memphis, TN (2012) -- One Meter Resolution Urban Land Cover Data

EPA Pesticide Factsheets

The Memphis, TN EnviroAtlas One Meter-scale Urban Land Cover (MULC) dataset comprises 2,733 km2 around the city of Memphis, surrounding towns, and rural areas. These leaf-on LC data and maps were derived from 1-m pixel, four-band (red, green, blue, and near-infrared) aerial photography acquired from the United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) on four dates in 2012: June 15, June 18, June 21 and June 23, and one date in 2013: July 12. Three separate LiDAR (Light Detection and Ranging) data sets collected on February 19, 2009 00e2?? August 2, 2010, December 1-2, 2011 and January 23-24, 2012 were integrated for Shelby Co., TN, Crittenden Co., AR, and DeSoto Co, MS. Five MULC classes were mapped directly from the NAIP and LiDAR data: Water, Impervious, Soil, Trees, and Grass/Herbaceous. Agriculture was derived from USDA Common Land Unit (CLU) data. Woody and emergent wetlands were copied from existing National Wetlands Inventory (NWI) data. Analysis of a random sampling of 612 photo-interpreted land cover reference points yielded an overall users accuracy of 86.9%. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as do

Landslide detection using LiDAR data and data mining technology: Ali Mountain Highway case study (Taiwan)

NASA Astrophysics Data System (ADS)

Cheng, Youg-Sin; Yu, Teng-To; Tarolli, Paolo

2017-04-01

Taiwan mountains are severely affected each year by landslides, rock falls, and debris flows where the roads system suffer the most critical consequences. Among all mountain highways, Ali Highway, located into the main entrance of Alishan Mountain region, is one of the most landslide-prone areas in southern Taiwan. During the typhoon season, between May and August, the probability of occurrence of mass movements is at higher level than usual seeing great erosion rates. In fact, during Typhoon Morakot, in 2009, the intense rainfall caused abrupt interruption of the circulation for three months triggering several landslides (Liu et al. 2012). The topographic features such as slope, roughness and curvature among others have been extracted from 1 m DTM derived by a LiDAR dataset (collected in 2015) to investigate the slope failures along the Ali Mountain Highway. The high-resolution DTM highlighted that the hydrogeomorphological (e.g. density of stream, the distance from the ridge and terrain) features are one of the most influencing factors affecting the change and the instability of the slopes. To detect the landslide area, the decision tree classifier and the random forest algorithm (RF) have been adopted. The results provided a suitable analysis of the area involved in the failure. This will be a useful step in the understanding (and management) landslide processes of study area. References Liu CN, Dong JJ, Chen CJ, Lee WF (2012) Typical landslides and related mechanisms in Ali Mountain highway induced by typhoon Morakot: Perspectives from engineering geology. Landslides 9:239-254.

Estimating Above-Ground Carbon Biomass in a Newly Restored Coastal Plain Wetland Using Remote Sensing

PubMed Central

Riegel, Joseph B.; Bernhardt, Emily; Swenson, Jennifer

2013-01-01

Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R2 values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R2 of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas. PMID:23840837

Identifying Populace Susceptible to Flooding Using ArcGIS and Remote Sensing Datasets

NASA Astrophysics Data System (ADS)

Fernandez, Sim Joseph; Milano, Alan

2016-07-01

Remote sensing technologies are growing vastly as with its various applications. The Department of Science and Technology (DOST), Republic of the Philippines, has made projects exploiting LiDAR datasets from remote sensing technologies. The Phil-LiDAR 1 project of DOST is a flood hazard mapping project. Among the project's objectives is the identification of building features which can be associated to the flood-exposed population. The extraction of building features from the LiDAR dataset is arduous as it requires manual identification of building features on an elevation map. The mapping of building footprints is made meticulous in order to compensate the accuracy between building floor area and building height both of which are crucial in flood decision making. A building identification method was developed to generate a LiDAR derivative which will serve as a guide in mapping building footprints. The method utilizes several tools of a Geographic Information System (GIS) software called ArcGIS which can operate on physical attributes of buildings such as roofing curvature, slope and blueprint area in order to obtain the LiDAR derivative from LiDAR dataset. The method also uses an intermediary process called building removal process wherein buildings and other features lying below the defined minimum building height - 2 meters in the case of Phil-LiDAR 1 project - are removed. The building identification method was developed in the hope to hasten the identification of building features especially when orthophotographs and/or satellite imageries are not made available.

Diversity arrays technology (DArT) markers in apple for genetic linkage maps.

PubMed

Schouten, Henk J; van de Weg, W Eric; Carling, Jason; Khan, Sabaz Ali; McKay, Steven J; van Kaauwen, Martijn P W; Wittenberg, Alexander H J; Koehorst-van Putten, Herma J J; Noordijk, Yolanda; Gao, Zhongshan; Rees, D Jasper G; Van Dyk, Maria M; Jaccoud, Damian; Considine, Michael J; Kilian, Andrzej

2012-03-01

Diversity Arrays Technology (DArT) provides a high-throughput whole-genome genotyping platform for the detection and scoring of hundreds of polymorphic loci without any need for prior sequence information. The work presented here details the development and performance of a DArT genotyping array for apple. This is the first paper on DArT in horticultural trees. Genetic mapping of DArT markers in two mapping populations and their integration with other marker types showed that DArT is a powerful high-throughput method for obtaining accurate and reproducible marker data, despite the low cost per data point. This method appears to be suitable for aligning the genetic maps of different segregating populations. The standard complexity reduction method, based on the methylation-sensitive PstI restriction enzyme, resulted in a high frequency of markers, although there was 52-54% redundancy due to the repeated sampling of highly similar sequences. Sequencing of the marker clones showed that they are significantly enriched for low-copy, genic regions. The genome coverage using the standard method was 55-76%. For improved genome coverage, an alternative complexity reduction method was examined, which resulted in less redundancy and additional segregating markers. The DArT markers proved to be of high quality and were very suitable for genetic mapping at low cost for the apple, providing moderate genome coverage. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11032-011-9579-5) contains supplementary material, which is available to authorized users.

Timely binding of IHF and Fis to DARS2 regulates ATP-DnaA production and replication initiation.

PubMed

Kasho, Kazutoshi; Fujimitsu, Kazuyuki; Matoba, Toshihiro; Oshima, Taku; Katayama, Tsutomu

2014-12-01

In Escherichia coli, the ATP-bound form of DnaA (ATP-DnaA) promotes replication initiation. During replication, the bound ATP is hydrolyzed to ADP to yield the ADP-bound form (ADP-DnaA), which is inactive for initiation. The chromosomal site DARS2 facilitates the regeneration of ATP-DnaA by catalyzing nucleotide exchange between free ATP and ADP bound to DnaA. However, the regulatory mechanisms governing this exchange reaction are unclear. Here, using in vitro reconstituted experiments, we show that two nucleoid-associated proteins, IHF and Fis, bind site-specifically to DARS2 to activate coordinately the exchange reaction. The regenerated ATP-DnaA was fully active in replication initiation and underwent DnaA-ATP hydrolysis. ADP-DnaA formed heteromultimeric complexes with IHF and Fis on DARS2, and underwent nucleotide dissociation more efficiently than ATP-DnaA. Consistently, mutant analyses demonstrated that specific binding of IHF and Fis to DARS2 stimulates the formation of ATP-DnaA production, thereby promoting timely initiation. Moreover, we show that IHF-DARS2 binding is temporally regulated during the cell cycle, whereas Fis only binds to DARS2 in exponentially growing cells. These results elucidate the regulation of ATP-DnaA and replication initiation in coordination with the cell cycle and growth phase. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Visualization of High-Resolution LiDAR Topography in Google Earth

NASA Astrophysics Data System (ADS)

Crosby, C. J.; Nandigam, V.; Arrowsmith, R.; Blair, J. L.

2009-12-01

The growing availability of high-resolution LiDAR (Light Detection And Ranging) topographic data has proven to be revolutionary for Earth science research. These data allow scientists to study the processes acting on the Earth’s surfaces at resolutions not previously possible yet essential for their appropriate representation. In addition to their utility for research, the data have also been recognized as powerful tools for communicating earth science concepts for education and outreach purposes. Unfortunately, the massive volume of data produced by LiDAR mapping technology can be a barrier to their use. To facilitate access to these powerful data for research and educational purposes, we have been exploring the use of Keyhole Markup Language (KML) and Google Earth to deliver LiDAR-derived visualizations. The OpenTopography Portal (http://www.opentopography.org/) is a National Science Foundation-funded facility designed to provide access to Earth science-oriented LiDAR data. OpenTopography hosts a growing collection of LiDAR data for a variety of geologic domains, including many of the active faults in the western United States. We have found that the wide spectrum of LiDAR users have variable scientific applications, computing resources, and technical experience and thus require a data distribution system that provides various levels of access to the data. For users seeking a synoptic view of the data, and for education and outreach purposes, delivering full-resolution images derived from LiDAR topography into the Google Earth virtual globe is powerful. The virtual globe environment provides a freely available and easily navigated viewer and enables quick integration of the LiDAR visualizations with imagery, geographic layers, and other relevant data available in KML format. Through region-dependant network linked KML, OpenTopography currently delivers over 20 GB of LiDAR-derived imagery to users via simple, easily downloaded KMZ files hosted at the Portal. This method provides seamlessly access to hillshaded imagery for both bare earth and first return terrain models with various angles of illumination. Seamless access to LiDAR-derived imagery in Google Earth has proven to be the most popular product available in the OpenTopography Portal. The hillshade KMZ files have been downloaded over 3000 times by users ranging from earthquake scientists to K-12 educators who wish to introduce cutting edge real world data into their earth science lessons. OpenTopography also provides dynamically generated KMZ visualizations of LiDAR data products produced when users choose to use the OpenTopography point cloud access and processing system. These Google Earth compatible products allow users to quickly visualize the custom terrain products they have generated without the burden of loading the data into a GIS environment. For users who have installed the Google Earth browser plug-in, these visualizations can be launched directly from the OpenTopography results page and viewed directly in the browser.

Modelling Sensor and Target effects on LiDAR Waveforms

NASA Astrophysics Data System (ADS)

Rosette, J.; North, P. R.; Rubio, J.; Cook, B. D.; Suárez, J.

2010-12-01

The aim of this research is to explore the influence of sensor characteristics and interactions with vegetation and terrain properties on the estimation of vegetation parameters from LiDAR waveforms. This is carried out using waveform simulations produced by the FLIGHT radiative transfer model which is based on Monte Carlo simulation of photon transport (North, 1996; North et al., 2010). The opportunities for vegetation analysis that are offered by LiDAR modelling are also demonstrated by other authors e.g. Sun and Ranson, 2000; Ni-Meister et al., 2001. Simulations from the FLIGHT model were driven using reflectance and transmittance properties collected from the Howland Research Forest, Maine, USA in 2003 together with a tree list for a 200m x 150m area. This was generated using field measurements of location, species and diameter at breast height. Tree height and crown dimensions of individual trees were calculated using relationships established with a competition index determined for this site. Waveforms obtained by the Laser Vegetation Imaging Sensor (LVIS) were used as validation of simulations. This provided a base from which factors such as slope, laser incidence angle and pulse width could be varied. This has enabled the effect of instrument design and laser interactions with different surface characteristics to be tested. As such, waveform simulation is relevant for the development of future satellite LiDAR sensors, such as NASA’s forthcoming DESDynI mission (NASA, 2010), which aim to improve capabilities of vegetation parameter estimation. ACKNOWLEDGMENTS We would like to thank scientists at the Biospheric Sciences Branch of NASA Goddard Space Flight Center, in particular to Jon Ranson and Bryan Blair. This work forms part of research funded by the NASA DESDynI project and the UK Natural Environment Research Council (NE/F021437/1). REFERENCES NASA, 2010, DESDynI: Deformation, Ecosystem Structure and Dynamics of Ice. http://desdyni.jpl.nasa.gov/ (accessed May 2010). NI-MEISTER, W., JUPP, D. L. B. and DUBAYAH, R., 2001, Modeling Lidar Waveforms in Heterogeneous and Discrete Canopies. IEEE Transactions on Geoscience and Remote Sensing, 39 (9): 1943-1958. NORTH, P. R. J., 1996, Three-Dimensional Forest Light Interaction Model Using a Monte Carlo Method. IEEE Transactions on Geoscience and Remote Sensing, 34 (4): 946-956. NORTH, P. R. J., ROSETTE, J. A. B., SUÁREZ, J. C. and LOS, S. O., 2010, A Monte Carlo radiative transfer model of satellite waveform lidar. International Journal of Remote Sensing, 31 (5): 1343-1358. SUN, G. and RANSON, K. J., 2000, Modeling lidar returns from forest canopies. IEEE Transactions on Geoscience and Remote Sensing, 38 (6): 2617-2626.

VPAC1 Targeted 64Cu-TP3805 kit preparation and its evaluation.

PubMed

Tripathi, Sushil K; Kumar, Pardeep; Trabulsi, Edouard J; Kim, Sung; McCue, Peter A; Intenzo, Charles; Berger, Adam; Gomella, Leonard; Thakur, Mathew L

2017-08-01

Previously, our laboratory has shown that 64 Cu-TP3805 can specifically target VPAC1 receptors and be used for positron emission tomography (PET) imaging of breast (BC) and prostate cancer (PC) in humans. Present work is aimed at the formulation of a freeze-dried diaminedithiol-peptide (N 2 S 2 -TP3805) kit and it's evaluation for the preparation of 64 Cu labeled TP3805. Parameters such as pH, temperature and incubation time were examined that influenced the radiolabeling efficiency and stability of the product. Kits were prepared under different conditions and radiolabeling efficiency of TP3805 kit was evaluated for a range of pH3.5-8.5, after addition of 64 Cu in 30μl, 0.1M HCl. Incubation temperature (37-90°C) and time (30-120min.) were also investigated. Kits were stored at -10°C and their long term stability was determined as a function of their radiolabeling efficiency. Further, stability of 64 Cu-TP3805 complex was evaluated in presence of fetal bovine serum and bovine serum albumin by using SDS polyacrylamide gel electrophoresis. Kits were then used for PET imaging of BC and PC following eIND (101550) and institutional approvals. Specificity of 64 Cu-TP3805 for VPAC1 was examined with digital autoradiography (DAR) of prostate tissues obtained after prostatectomy, benign prostatic hyperplasia (BPH) tissue, and benign and malignant lymph nodes. Results were compared with corresponding tissue histology. Radiolabeling efficiency was ≥95% at final pH ~7.2 when incubated at 50°C for 90min. Kits were stable up to 18months when stored at -10°C, and 64 Cu-TP3805 complex exhibited excellent stability for up to 4h at room temperature. 64 Cu-TP3805 complex did not show any transchelation even after 2h incubation at 37°C in 10% FBS as well as in BSA as determined by SDS PAGE analysis. DAR identified ≥95% of malignant lesions 11 new PC lesions, 20 high grade prostatic intraepithelial neoplasia, 2/2 ejaculatory ducts and 5/5 urethra verumontanum not previously identified The malignant lymph nodes were correctly identified by DAR and for 3/3 BPH patients, and 5/5 cysts, DAR was negative. In human BC (n=19) and PC (n=26) were imaged with 100% sensitivity. Availability of ready to use N 2 S 2 -peptide kits for 64 Cu labeling is convenient and eliminates possible day to day variation during its routine preparation for clinical use. Copyright © 2017 Elsevier Inc. All rights reserved.

Layer stacking: A novel algorithm for individual forest tree segmentation from LiDAR point clouds

Treesearch

Elias Ayrey; Shawn Fraver; John A. Kershaw; Laura S. Kenefic; Daniel Hayes; Aaron R. Weiskittel; Brian E. Roth

2017-01-01

As light detection and ranging (LiDAR) technology advances, it has become common for datasets to be acquired at a point density high enough to capture structural information from individual trees. To process these data, an automatic method of isolating individual trees from a LiDAR point cloud is required. Traditional methods for segmenting trees attempt to isolate...

Comparisons between field- and LiDAR-based measures of stand structrual complexity

Treesearch

Van R. Kane; Robert J. McGaughey; Jonathan D. Bakker; Rolf F. Gersonde; James A. Lutz; Jerry F. Franklin

2010-01-01

Forest structure, as measured by the physical arrangement of trees and their crowns, is a fundamental attribute of forest ecosystems that changes as forests progress through successional stages. We examined whether LiDAR data could be used to directly assess the successional stage of forests by determining the degree to which the LiDAR data would show the same relative...

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 2 : applications of LiDAR technology in structural evaluation under normal traffic operation and post blast loading.

DOT National Transportation Integrated Search

2012-03-01

This report focused on two potential applications of terrestrial LiDAR scans on highway : bridges: 1) vehicle crossing effects measured by3-D, terrestrial LiDAR scans of highway bridges : measuring clearance distance; and 2) bridge post-blast geometr...

A comparison of accuracy and cost of LiDAR versus stand exam data for landscape management on the Malheur National Forest

Treesearch

Susan Hummel; A. T. Hudak; E. H. Uebler; M. J. Falkowski; K. A. Megown

2011-01-01

Foresters are increasingly interested in remote sensing data because they provide an overview of landscape conditions, which is impractical with field sample data alone. Light Detection and Ranging (LiDAR) provides exceptional spatial detail of forest structure, but difficulties in processing LiDAR data have limited their application beyond the research community....

Comparison of LiDAR-derived data and high resolution true color imagery for extracting urban forest cover

Treesearch

Aaron E. Maxwell; Adam C. Riley; Paul Kinder

2013-01-01

Remote sensing has many applications in forestry. Light detection and ranging (LiDAR) and high resolution aerial photography have been investigated as means to extract forest data, such as biomass, timber volume, stand dynamics, and gap characteristics. LiDAR return intensity data are often overlooked as a source of input raster data for thematic map creation. We...

Using Landsat Time-Series and LiDAR to Inform Aboveground Forest Biomass Baselines in Northern Minnesota, USA

Treesearch

Ram K. Deo; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall; Michael J. Falkowski; Warren B. Cohen

2017-01-01

The publicly accessible archive of Landsat imagery and increasing regional-scale LiDAR acquisitions offer an opportunity to periodically estimate aboveground forest biomass (AGB) from 1990 to the present to alignwith the reporting needs ofNationalGreenhouseGas Inventories (NGHGIs). This study integrated Landsat time-series data, a state-wide LiDAR dataset, and a recent...

Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey

Treesearch

Lei Wang; Andrew G. Birt; Charles W. Lafon; David M. Cairns; Robert N. Coulson; Maria D. Tchakerian; Weimin Xi; Sorin C. Popescu; James M. Guldin

2013-01-01

Small Footprint LiDAR (Light Detection And Ranging) has been proposed as an effective tool for measuring detailed biophysical characteristics of forests over broad spatial scales. However, by itself LiDAR yields only a sample of the true 3D structure of a forest. In order to extract useful forestry relevant information, this data must be interpreted using mathematical...

Lidar - ND Halo Scanning Doppler, Boardman - Derived Data

DOE Data Explorer

Leo, Laura

2018-01-26

The University of Notre Dame (ND) scanning LiDAR dataset used for the WFIP2 Campaign is provided. The LiDAR is a Halo Photonics Stream Line Scanning Doppler LiDAR. **It is highly recommended to discuss any planned use of these data with University of Notre Dame scientists**. For more information refer to the attached "WFIP2 Project (lidar.z07)" Readme file.

Roles of dopamine receptors in mediating acute modulation of immunological responses in Macrobrachium rosenbergii.

PubMed

Chang, Zhong-Wen; Ke, Zhi-Han; Chang, Chin-Chyuan

2016-02-01

Dopamine (DA) was found to influence the immunological responses and resistance to pathogen infection in invertebrates. To clarify the possible modulation of DA through dopamine receptors (DAR) against acute environmental stress, the levels of DA, glucose and lactate in the haemolymph of Macrobrachium rosenbergii under hypo- and hyperthermal stresses were measured. The changes in immune parameters such as total haemocyte count (THC), differential haemocyte count (DHC), phenoloxidase (PO) activity, respiratory bursts (RBs), superoxide dismutase (SOD) and glutathione peroxidase (GPx) activities and phagocytic activity (PA) were evaluated in prawns which received DAR antagonists (SCH23390, SCH, D1 antagonist; domperidone, DOM, D2 antagonist; chlorpromazine, CH, D1+2 antagonist) followed by hypo- (15 °C) and hyperthermal (34 °C) stresses. In addition, pharmacological analysis of the effect DA modulation was studied in haemocytes incubated with DA and DAR antagonists. The results revealed a significant increase in haemolymph DA accompanied with upregulated levels of glucose and lactate in prawns exposed to both hypo- and hyperthermal stresses in 2 h. In addition, a significant decrease in RBs per haemocyte was noted in prawns which received DAR antagonists when they exposed to hyperthermal stress for 30 min. In in vitro test, antagonism on RBs, SOD and GPx activity of haemocytes were further evidenced through D1, D1, D1+D2 DARs, respectively, in the meantime, no significant difference in PO activity and PA was observed among the treatment groups. These results suggest that the upregulation of DA, glucose and lactate in haemolymph might be the response to acute thermal stress for the demand of energy, and the DAR occupied by its antagonistic action impart no effect on immunological responses except RBs in vivo even though the modulation mediated through D1 DAR was further evidenced in RBs, SOD and GPx activities in vitro. It is therefore concluded that thermal stress mediate stress responses not only through DAR but also via diverse pathways, and DA might modulate the levels of RBs, SOD and GPx activities mainly through D1 DAR. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantification of LiDAR measurement uncertainty through propagation of errors due to sensor sub-systems and terrain morphology

NASA Astrophysics Data System (ADS)

Goulden, T.; Hopkinson, C.

2013-12-01

The quantification of LiDAR sensor measurement uncertainty is important for evaluating the quality of derived DEM products, compiling risk assessment of management decisions based from LiDAR information, and enhancing LiDAR mission planning capabilities. Current quality assurance estimates of LiDAR measurement uncertainty are limited to post-survey empirical assessments or vendor estimates from commercial literature. Empirical evidence can provide valuable information for the performance of the sensor in validated areas; however, it cannot characterize the spatial distribution of measurement uncertainty throughout the extensive coverage of typical LiDAR surveys. Vendor advertised error estimates are often restricted to strict and optimal survey conditions, resulting in idealized values. Numerical modeling of individual pulse uncertainty provides an alternative method for estimating LiDAR measurement uncertainty. LiDAR measurement uncertainty is theoretically assumed to fall into three distinct categories, 1) sensor sub-system errors, 2) terrain influences, and 3) vegetative influences. This research details the procedures for numerical modeling of measurement uncertainty from the sensor sub-system (GPS, IMU, laser scanner, laser ranger) and terrain influences. Results show that errors tend to increase as the laser scan angle, altitude or laser beam incidence angle increase. An experimental survey over a flat and paved runway site, performed with an Optech ALTM 3100 sensor, showed an increase in modeled vertical errors of 5 cm, at a nadir scan orientation, to 8 cm at scan edges; for an aircraft altitude of 1200 m and half scan angle of 15°. In a survey with the same sensor, at a highly sloped glacial basin site absent of vegetation, modeled vertical errors reached over 2 m. Validation of error models within the glacial environment, over three separate flight lines, respectively showed 100%, 85%, and 75% of elevation residuals fell below error predictions. Future work in LiDAR sensor measurement uncertainty must focus on the development of vegetative error models to create more robust error prediction algorithms. To achieve this objective, comprehensive empirical exploratory analysis is recommended to relate vegetative parameters to observed errors.

A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits

PubMed Central

Wenzl, Peter; Li, Haobing; Carling, Jason; Zhou, Meixue; Raman, Harsh; Paul, Edie; Hearnden, Phillippa; Maier, Christina; Xia, Ling; Caig, Vanessa; Ovesná, Jaroslava; Cakir, Mehmet; Poulsen, David; Wang, Junping; Raman, Rosy; Smith, Kevin P; Muehlbauer, Gary J; Chalmers, Ken J; Kleinhofs, Andris; Huttner, Eric; Kilian, Andrzej

2006-01-01

Background Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding schemes. The study also highlights the need for improved software for building consensus maps from high-density segregation data of multiple populations. PMID:16904008

Dopamine receptor antagonists as new mode-of-action insecticide leads for control of Aedes and Culex mosquito vectors.

PubMed

Nuss, Andrew B; Ejendal, Karin F K; Doyle, Trevor B; Meyer, Jason M; Lang, Emma G; Watts, Val J; Hill, Catherine A

2015-03-01

New mode-of-action insecticides are sought to provide continued control of pesticide resistant arthropod vectors of neglected tropical diseases (NTDs). We previously identified antagonists of the AaDOP2 D1-like dopamine receptor (DAR) from the yellow fever mosquito, Aedes aegypti, with toxicity to Ae. aegypti larvae as leads for novel insecticides. To extend DAR-based insecticide discovery, we evaluated the molecular and pharmacological characteristics of an orthologous DAR target, CqDOP2, from Culex quinquefasciatus, the vector of lymphatic filariasis and West Nile virus. CqDOP2 has 94.7% amino acid identity to AaDOP2 and 28.3% identity to the human D1-like DAR, hD1. CqDOP2 and AaDOP2 exhibited similar pharmacological responses to biogenic amines and DAR antagonists in cell-based assays. The antagonists amitriptyline, amperozide, asenapine, chlorpromazine and doxepin were between 35 to 227-fold more selective at inhibiting the response of CqDOP2 and AaDOP2 in comparison to hD1. Antagonists were toxic to both C. quinquefasciatus and Ae. aegypti larvae, with LC50 values ranging from 41 to 208 μM 72 h post-exposure. Orthologous DOP2 receptors identified from the African malaria mosquito, Anopheles gambiae, the sand fly, Phlebotomus papatasi and the tsetse fly, Glossina morsitans, had high sequence similarity to CqDOP2 and AaDOP2. DAR antagonists represent a putative new insecticide class with activity against C. quinquefasciatus and Ae. aegypti, the two most important mosquito vectors of NTDs. There has been limited change in the sequence and pharmacological properties of the DOP2 DARs of these species since divergence of the tribes Culicini and Aedini. We identified antagonists selective for mosquito versus human DARs and observed a correlation between DAR pharmacology and the in vivo larval toxicity of antagonists. These data demonstrate that sequence similarity can be predictive of target potential. On this basis, we propose expanded insecticide discovery around orthologous DOP2 targets from additional dipteran vectors.

Recent advances in analysis and prediction of Rock Falls, Rock Slides, and Rock Avalanches using 3D point clouds

NASA Astrophysics Data System (ADS)

Abellan, A.; Carrea, D.; Jaboyedoff, M.; Riquelme, A.; Tomas, R.; Royan, M. J.; Vilaplana, J. M.; Gauvin, N.

2014-12-01

The acquisition of dense terrain information using well-established 3D techniques (e.g. LiDAR, photogrammetry) and the use of new mobile platforms (e.g. Unmanned Aerial Vehicles) together with the increasingly efficient post-processing workflows for image treatment (e.g. Structure From Motion) are opening up new possibilities for analysing, modeling and predicting rock slope failures. Examples of applications at different scales ranging from the monitoring of small changes at unprecedented level of detail (e.g. sub millimeter-scale deformation under lab-scale conditions) to the detection of slope deformation at regional scale. In this communication we will show the main accomplishments of the Swiss National Foundation project "Characterizing and analysing 3D temporal slope evolution" carried out at Risk Analysis group (Univ. of Lausanne) in close collaboration with the RISKNAT and INTERES groups (Univ. of Barcelona and Univ. of Alicante, respectively). We have recently developed a series of innovative approaches for rock slope analysis using 3D point clouds, some examples include: the development of semi-automatic methodologies for the identification and extraction of rock-slope features such as discontinuities, type of material, rockfalls occurrence and deformation. Moreover, we have been improving our knowledge in progressive rupture characterization thanks to several algorithms, some examples include the computing of 3D deformation, the use of filtering techniques on permanently based TLS, the use of rock slope failure analogies at different scales (laboratory simulations, monitoring at glacier's front, etc.), the modelling of the influence of external forces such as precipitation on the acceleration of the deformation rate, etc. We have also been interested on the analysis of rock slope deformation prior to the occurrence of fragmental rockfalls and the interaction of this deformation with the spatial location of future events. In spite of these recent advances, a great challenge still remains in the development of new algorithms for more accurate techniques for 3D point cloud treatment (e.g. filtering, segmentation, etc.) aiming to improve rock slope characterization and monitoring, a series of exciting research findings are expected in the forthcoming years.

COMMITTEES: Committees

NASA Astrophysics Data System (ADS)

2010-01-01

TAUP STEERING COMMITTEE F T Avignone, University of South Carolina B C Barish, CALTECH E Bellotti, University of Milano, INFN J Bernabeu, University of Valencia A Bottino (Chair), University of Torino, INFN N Fornengo, University of Torino, INFN T Kajita, ICRR University of Tokyo C W Kim, Johns Hopkins University, KIAS V Matveev, INR Moscow J Morales, University of Zaragoza G Raffelt, MPI Munchen D Sinclair, University of Carleton M Spiro, IN2P3 TAUP 2009 INTERNATIONAL ADVISORY COMMITTEE J J Aubert, CNRS Marseille M Baldo-Ceolin, University of Padova, INFN G Bellini, University of Milano, INFN L Bergstrom, University of Stockholm R Bernabei, University of Roma Tor Vergata, INFN A Bettini, University of Padova, INFN, LSC S Bilenky, JINR Dubna D O Caldwell, UCSB J Cronin, University of Chicago A Dar, Technion Haifa G Domogatsky, INR Moscow J Ellis, CERN E Fernandez, IFAE Barcelona E Fiorini, University of Milano, INFN T Gaisser, University of Delaware G Gelmini, UCLA G Gerbier, CEA Saclay A Giazotto, INFN Pisa F Halzen, University of Wisconsin W Haxton, University of Washington T Kirsten MPI Heidelberg L Maiani, University of Roma La Sapienza, INFN A McDonald, Queen's University K Nakamura, KEK R Petronzio, INFN, University of Roma Tor Vergata L Resvanis, University of Athens F Ronga INFN, LNF C Rubbia INFN, LNGS A Smirnov, ICTP Trieste C Spiering, DESY N Spooner, University of Sheffield A Suzuki, KEK S Ting MIT, CERN M S Turner, FNAL, University of Chicago J W F Valle, IFIC Valencia D Vignaud, APC Paris G Zatsepin, INR Moscow TAUP 2009 ORGANIZING COMMITTEE R Aloisio, LNGS R Antolini, LNGS F Arneodo, LNGS Z Berezhiani, University of L'Aquila, INFN V Berezinsky, LNGS R Cerulli, LNGS E Coccia [Chair], LNGS/INFN, U of Roma Tor Vergata N D'Ambrosio, LNGS N Fornengo, University of Torino, INFN M Laubenstein, LNGS O Palamara, LNGS L Pandola [Scientific Secretary], LNGS

Study of geomorphological changes by high quality DEMs, obtained from UAVs-Structure from Motion in highest continental cliffs of Europe: A Capelada (Galicia, Spain)

NASA Astrophysics Data System (ADS)

Muñoz Narciso, Efrén; García, Horacio; Sierra Pernas, Chema; Pérez-Alberti, Augusto

2017-04-01

This study analyses the geomorphological evolution of a highly dynamic coastal environment, one of the higher cliffs in Continental Europe (A Capelada, NW Spain), using Structure from Motion-Multi View Stereoscan techniques (hereafter referred to as SfM-MVS). Comparing orthoimages from the last 10 years we observed several topographical changes in one specific valley (Teixidelo). Interestingly, these changes were caused by 2 different processes: (i) heavy coastal erosion and (ii) slow complex landslides, working in opposite directions. The main challenge was obtaining high quality topographical data for quantifying the changes during the last few years using low cost-high quality techniques in remote areas. Unmanned Aerial Vehicle platforms (drones, hereafter referred to as UAVs) and SFM-MVS offer ultrahigh-density topographical data. Furthermore, the use of drones and SfM-MVS close range images requires new applications in geomorphology for understanding the workflow and limitations. In this paper we present the 2 main results: (i) a centimeter spatial resolution DEM from august 2016 was obtained using a @DJI Phantom 3 advanced model drone. The pictures were processed in Agisoft PhotoScan Pro 1.2.6 version by SfM-MVS techniques, generating a high-density point cloud (i.e. ˜2000 points/m2) with 3mm of RMSE (i.e. the point cloud was georeferenced in a geographical coordinates system using ˜40 Ground Control Points obtained from differential RTK-GPS and a Total Station network) and (ii) a DEM of Differences, which compares official freely available 2010 LiDAR data (i.e. ˜2 points/m2) with a 2016 DEM derived by UAVs-SfM, where we have observed meter-scale elevation changes (i.e. sediment and erosion processes). During this time, 75% of the sediment has been mobilized. The novel UAVs and SfM-MVS techniques prove to be great for advancing the study of geomorphological processes in remote areas.

Visualizing lava flow interiors with LiDAR

NASA Astrophysics Data System (ADS)

Whelley, P.; Garry, W. B.; Young, K.; Kruse, S.; Esmaeili, S.; Bell, E.; Paylor, R.

2017-12-01

Lava tube caves provide unprecedented access to the shallow (meters to tens of meters) interiors of lava flows. Surveying tube geometry and morphology can illuminate lava flow thermal history and emplacement mechanics. In an expedition to Lava Beds National Monument, California, our team collected ultra-high-resolution (< 10 cm) topography from the interiors of four lava tubes using a terrestrial laser scanner (TLS). More than 78 GB of point data (latitude, longitude, elevation) of the surface and interiors of Hercules Leg, Skull, Valentine and, Indian Well Caves were collected. For example, our point cloud for 50 m of Valentine Cave contains 748 million points (interior: 478 million, exterior: 270 million) from 28 TLS scans. The tubes visited range in diameter from < 1 m to > 10 m, and from 1 m to < 20 m of overburden. The interior morphology of the tubes remain pristine (i.e., un-eroded) after more than 10,000 years. The TLS data illuminate fresh-looking lava tube flow features (e.g., lava-coils, pillars, benches, and ropes) and post-emplacement deformation features (e.g., fractures, lava-drips, molded ceilings, and drop-blocks). Furthermore, the data provide context for geochemical and geophysical observations made in conjunction with the TLS survey. Lava tube morphology, observable in the TLS data, informs each tube's emplacement history. Skull cave is the largest ( 20 m in diameter) requiring a comparatively high lava discharge rate and suggesting this cave formed by roofing over a lava channel. In contrast, Valentine, Hercules Leg, and Indian Well Caves are narrower, (1 to 4 m) and have many branches, some of which rejoin the "main passage", suggesting they formed by developing a network of pathways within the lava flow. We will showcase video fly-throughs for these lava tubes, plus manipulable point clouds. The interactive eLighning presentation will encourage hands-on exploration of these unique data. We will guide them on a tour of the underground to discover and compare different morphologies of lava tubes.

Faulted terrace risers place new constraints on the late Quaternary slip rate for the central Altyn Tagh fault, northwest Tibet

USGS Publications Warehouse

Gold, R.D.; Cowgill, E.; Arrowsmith, J.R.; Chen, X.; Sharp, W.D.; Cooper, K.M.; Wang, X.-F.

2011-01-01

The active, left-lateral Altyn Tagh fault defines the northwestern margin of the Tibetan Plateau in western China. To clarify late Quaternary temporal and spatial variations in slip rate along the central portion of this fault system (85??-90??E), we have more than doubled the number of dated offset markers along the central Altyn Tagh fault. In particular, we determined offset-age relations for seven left-laterally faulted terrace risers at three sites (Kelutelage, Yukuang, and Keke Qiapu) spanning a 140-km-long fault reach by integrating surficial geologic mapping, topographic surveys (total station and tripod-light detection and ranging [T-LiDAR]), and geochronology (radiocarbon dating of organic samples, 230Th/U dating of pedogenic carbonate coatings on buried clasts, and terrestrial cosmogenic radionuclide exposure age dating applied to quartz-rich gravels). At Kelutelage, which is the westernmost site (37.72??N, 86.67??E), two faulted terrace risers are offset 58 ?? 3 m and 48 ?? 4 m, and formed at 6.2-6.1 ka and 5.9-3.7 ka, respectively. At the Yukuang site (38.00??N, 87.87??E), four faulted terrace risers are offset 92 ?? 12 m, 68 ?? 6 m, 55 ?? 13 m, and 59 ?? 9 m and formed at 24.2-9.5 ka, 6.4-5.0 ka, 5.1-3.9 ka, and 24.2-6.4 ka, respectively. At the easternmost site, Keke Qiapu (38.08??N, 88.12??E), a faulted terrace riser is offset 33 ?? 6 m and has an age of 17.1-2.2 ka. The displacement-age relationships derived from these markers can be satisfied by an approximately uniform slip rate of 8-12 mm/yr. However, additional analysis is required to test how much temporal variability in slip rate is permitted by this data set. ?? 2011 Geological Society of America.

Urban morphological determinants of temperature regulating ecosystem services in African cities: the case of Dar es Salaam, Tanzania

NASA Astrophysics Data System (ADS)

Cavan, Gina; Lindley, Sarah; Kibassa, Deusdedit; Shemdoe, Riziki; Capuano, Paolo; De Paola, Francesco; Renner, Florian; Pauleit, Stephan

2013-04-01

Urban green structure provides important regulating ecosystem services, such as temperature and flood regulation, and thus, has the potential to increase the resilience of African cities to climate change. Green structures within urban areas are not only limited to discrete units associated with recreational parks, agricultural areas and open spaces: they also exist within zones which have other primary functions, such as church yards, along transport routes, and within residential areas. Differing characteristics of urban areas can be conceptualised and subsequently mapped through the idea of urban morphology types. Urban morphology types are classifications which combine facets of urban form and function. When mapped, UMT units provide biophysically relevant meso-scale geographical zones which can be used as the basis for understanding climate-related impacts and adaptations. For example, they support the assessment of urban temperature patterns and the temperature regulating services provided by urban green structures. There are some examples of the use of UMTs for assessing regulating ecosystem services in European cities but little similar knowledge is available in an African context. This paper outlines the concept of urban morphology types (UMTs) and how they were applied to African case study cities (Cavan et al., 2012). It then presents the methods used to understand temperature regulating ecosystem services across an example African case study city, including (i) a GIS-based assessment of urban green structures, and (ii) applying an energy balance model to estimate current and future surface temperatures under climate change projections. The assessment is carried out for Dar es Salaam, Tanzania. Existing evidence suggests increases in both mean and extreme temperatures in the city. Historical analysis of the number of hot days per year suggests a rise from a maximum of 47 days per year in the period 1961-87 to 72 days per year in 2003-2011 (Giugni et al., 2012). Mean temperatures in the climate zone are estimated to increase by at least 1°C between 1971-2000 and 2021-2050(CSIR, 2012). Dar es Salaam is represented using around 1700 UMT units mapped across 43 UMT categories for the year 2008. Modelled surface temperature profiles for the city are presented, including an assessment of the potential impact of changing green structure cover within selected UMT categories. Provisional recommendations are made concerning the potential contribution of green structures as a climate adaptation response to the increasing temperatures in Dar es Salaam, which could be relevant for other African cities in similar climate zones. References Cavan, G., Lindley, S., Yeshitela, K., Nebebe, A., Woldegerima, T., Shemdoe, R., Kibassa, D., Pauleit, S., Renner, R., Printz, A., Buchta, K., Coly, A., Sall, F., Ndour, N. M., Ouédraogo, Y., Samari, B. S., Sankara, B. T., Feumba, R. A., Ngapgue, J. N., Ngoumo, M. T., Tsalefac, M., Tonye, E. (2012) CLUVA deliverable D2.7 Green infrastructure maps for selected case studies and a report with an urban green infrastructure mapping methodology adapted to African cities. http://www.cluva.eu/deliverables/CLUVA_D2.7.pdf. Accessed 18/12/12. CSIR (2012) CLUVA deliverable D1.5 Regional climate change simulations available for the selected areas http://www.cluva.eu/deliverables/CLUVA_D1.5.pdf. Accessed 8/1/13. Giugni, M., Adamo, P., Capuano, P., De Paola, F., Di Ruocco, A., Giordano, S., Iavazzo, P., Sellerino, M., Terracciano, S., Topa, M. E. (2012) CLUVA deliverable D.1.2 Hazard scenarios for test cities using available data. http://www.cluva.eu/deliverables/CLUVA_D1.2.pdf. Accessed 8/1/13

The kinematic evolution of the Macquarie Plate: A case study for the fragmentation of oceanic lithosphere

NASA Astrophysics Data System (ADS)

Choi, Hakkyum; Kim, Seung-Sep; Dyment, Jérôme; Granot, Roi; Park, Sung-Hyun; Hong, Jong Kuk

2017-11-01

The tectonic evolution of the Southeast Indian Ridge (SEIR), and in particular of its easternmost edge, has not been constrained by high-resolution shipboard data and therefore the kinematic details of its behavior are uncertain. Using new shipboard magnetic data obtained by R/VIB Araon and M/V L'Astrolabe along the easternmost SEIR and available archived magnetic data, we estimated the finite rotation parameters of the Macquarie-Antarctic and Australian-Antarctic motions for eight anomalies (1o, 2, 2Ay, 2Ao, 3y, 3o, 3Ay, and 3Ao). These new finite rotations indicate that the Macquarie Plate since its creation ∼6.24 million years ago behaved as an independent and rigid plate, confirming previous estimates. The change in the Australian-Antarctic spreading direction from N-S to NW-SE appears to coincide with the formation of the Macquarie Plate at ∼6.24 Ma. Analysis of the estimated plate motions indicates that the initiation and growth stages of the Macquarie Plate resemble the kinematic evolution of other microplates and continental breakup, whereby a rapid acceleration in angular velocity took place after its initial formation, followed by a slow decay, suggesting that a decrease in the resistive strength force might have played a significant role in the kinematic evolution of the microplate. The motions of the Macquarie Plate during its growth stages may have been further enhanced by the increased subducting rates along the Hjort Trench, while the Macquarie Plate has exhibited constant growth by seafloor spreading.

Relating rock avalanche morphology to emplacement processes

NASA Astrophysics Data System (ADS)

Dufresne, Anja; Prager, Christoph; Bösmeier, Annette

2015-04-01

The morphology, structure and sedimentological characteristics of rock avalanche deposits reflect both internal emplacement processes and external influences, such as runout path characteristics. The latter is mainly predisposed by topography, substrate types, and hydrogeological conditions. Additionally, the geological setting at the source slope controls, e.g. the spatial distribution of accumulated lithologies and hence material property-related changes in morphology, or the maximum clast size and amount of fines of different lithological units. The Holocene Tschirgant rock avalanche (Tyrol, Austria) resulted from failure of an intensely deformed carbonate rock mass on the southeast face of a 2,370-m-high mountain ridge. The initially sliding rock mass rapidly fragmented as it moved towards the floor of the Inn River valley. Part of the 200-250 x 106 m3 (Patzelt 2012) rock avalanche debris collided with and moved around an opposing bedrock ridge and flowed into the Ötz valley, reaching up to 6.3 km from source. Where the Tschirgant rock avalanche spread freely it formed longitudinal ridges aligned along motion direction as well as smaller hummocks. Encountering high topography, it left runup ridges, fallback patterns (i.e. secondary collapse), and compressional morphology (successively elevated, transverse ridges). Further evidence for the mechanical landslide behaviour is given by large volumes of mobilized valley-fill sediments (polymict gravels and sands). These sediments indicate both shearing and compressional faulting within the rock avalanche mass (forming their own morphological units through, e.g. in situ bulldozing or as distinctly different hummocky terrain), but also indicate extension of the spreading landslide mass (i.e. intercalated/injected gravels encountered mainly in morphological depressions between hummocks). Further influences on its morphology are given by the different lithological units. E.g. the transition from massive dolomite/limestone sequences to weaker siliciclastic and evaporitic beds (sand-/siltstones, rauhwacken) can be pinpointed on LiDAR shaded relief images of the rock avalanche deposit. Hence, several morphological signatures are clearly related to differences in mechanical behaviour of the involved lithologies, whereas others reflect particular emplacement modes of the same rock unit: e.g. rockslide motion versus rock avalanche spreading. Reference Patzelt G. 2012. The rock avalanches of Tschirgant and Haiming (Upper Inn Valley, Tyrol, Austria), comment on the map supply. (German language only). Jahrbuch der Geologischen Bundesanstalt 152(1-4): 13-24.

LiDAR collection in August 2015 over the East River Watershed, Colorado, USA

DOE Data Explorer

Wainwright, Haruko [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Kenneth

2017-01-01

Airborne LiDAR data were acquired over the study area on August 10th, 2015, using a Riegl Q1560 dual-channel LiDAR system mounted on a Piper Navajo. The survey was performed by Quantum Spatial in collaboration with Eagle Mapping Ltd. The data complies with the USGS QL1 standard [Heideman, 2014] with the point density more than 8 pulse per m2.

Understanding the Unique Equatorial Density Irregularities

DTIC Science & Technology

2015-04-01

3 Bahir Dar, 79 ETHIOPIA EOARD GRANT #FA8655-13-1-3052 Report Date: April 2015 Final Report from 15 June 2013 to 30 March 2015 Air Force...ADDRESS(ES) Bahir Dar University Peda Straight, Region 3 Bahir Dar, 79 ETHIOPIA 8. PERFORMING ORGANIZATION REPORT NUMBER N/A 9. SPONSORING/MONITORING...satellite signal receivers and others in collaboration with institutions outside Ethiopia . This effort provided some support for the installation of the

Quantitative analysis of woodpecker habitat using high-resolution airborne LiDAR estimates of forest structure and composition

Treesearch

James E. Garabedian; Robert J. McGaughey; Stephen E. Reutebuch; Bernard R. Parresol; John C. Kilgo; Christopher E. Moorman; M. Nils. Peterson

2014-01-01

Light detection and ranging (LiDAR) technology has the potential to radically alter the way researchers and managers collect data on wildlife–habitat relationships. To date, the technology has fostered several novel approaches to characterizing avian habitat, but has been limited by the lack of detailed LiDAR-habitat attributes relevant to species across a continuum of...

Aggregating pixel-level basal area predictions derived from LiDAR data to industrial forest stands in North-Central Idaho

Treesearch

Andrew T. Hudak; Jeffrey S. Evans; Nicholas L. Crookston; Michael J. Falkowski; Brant K. Steigers; Rob Taylor; Halli Hemingway

2008-01-01

Stand exams are the principal means by which timber companies monitor and manage their forested lands. Airborne LiDAR surveys sample forest stands at much finer spatial resolution and broader spatial extent than is practical on the ground. In this paper, we developed models that leverage spatially intensive and extensive LiDAR data and a stratified random sample of...

LiDAR‐guided Archaeological Survey of a Mediterranean Landscape: Lessons from the Ancient Greek Polis of Kolophon (Ionia, Western Anatolia)

PubMed Central

Draganits, Erich; Gretscher, Martin; Muss, Ulrike

2017-01-01

Abstract In 2013, an airborne laser scan survey was conducted in the territory of the Ionian city of Kolophon near the western coast of modern Turkey as part of an archaeological survey project carried out by the Mimar Sinan University of Istanbul (Turkey) and the University of Vienna (Austria). Several light detection and ranging (LiDAR) studies have been carried out in the temperate climate zones of Europe, but only a few in Mediterranean landscapes. Our study is based on the first LiDAR survey carried out for an archaeological purpose in Turkey and one of the first in the Mediterranean that have been planned, measured and filtered especially for archaeological research questions. The interpretation of LiDAR data combined with ground‐observations proved extremely useful for the detection and documentation of archaeological remains below Mediterranean evergreen vegetation and dense maquis. This article deals with the methodological aspects of interpreting LiDAR data, using the Kolophon data as a case study. We offer a discussion of the strengths and limitations of LiDAR as an archaeological remote sensing method and suggest a best practice model for interpreting LiDAR data in a Mediterranean context. © 2017 The Authors. Archaeological Prospection published by John Wiley & Sons Ltd. PMID:29242700

a Novel Method for Automation of 3d Hydro Break Line Generation from LIDAR Data Using Matlab

NASA Astrophysics Data System (ADS)

Toscano, G. J.; Gopalam, U.; Devarajan, V.

2013-08-01

Water body detection is necessary to generate hydro break lines, which are in turn useful in creating deliverables such as TINs, contours, DEMs from LiDAR data. Hydro flattening follows the detection and delineation of water bodies (lakes, rivers, ponds, reservoirs, streams etc.) with hydro break lines. Manual hydro break line generation is time consuming and expensive. Accuracy and processing time depend on the number of vertices marked for delineation of break lines. Automation with minimal human intervention is desired for this operation. This paper proposes using a novel histogram analysis of LiDAR elevation data and LiDAR intensity data to automatically detect water bodies. Detection of water bodies using elevation information was verified by checking against LiDAR intensity data since the spectral reflectance of water bodies is very small compared with that of land and vegetation in near infra-red wavelength range. Detection of water bodies using LiDAR intensity data was also verified by checking against LiDAR elevation data. False detections were removed using morphological operations and 3D break lines were generated. Finally, a comparison of automatically generated break lines with their semi-automated/manual counterparts was performed to assess the accuracy of the proposed method and the results were discussed.

Adjustment of Measurements with Multiplicative Errors: Error Analysis, Estimates of the Variance of Unit Weight, and Effect on Volume Estimation from LiDAR-Type Digital Elevation Models

PubMed Central

Shi, Yun; Xu, Peiliang; Peng, Junhuan; Shi, Chuang; Liu, Jingnan

2014-01-01

Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS) adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM) have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM. PMID:24434880

Waveform LiDAR across forest biomass gradients

NASA Astrophysics Data System (ADS)

Montesano, P. M.; Nelson, R. F.; Dubayah, R.; Sun, G.; Ranson, J.

2011-12-01

Detailed information on the quantity and distribution of aboveground biomass (AGB) is needed to understand how it varies across space and changes over time. Waveform LiDAR data is routinely used to derive the heights of scattering elements in each illuminated footprint, and the vertical structure of vegetation is related to AGB. Changes in LiDAR waveforms across vegetation structure gradients can demonstrate instrument sensitivity to land cover transitions. A close examination of LiDAR waveforms in footprints across a forest gradient can provide new insight into the relationship of vegetation structure and forest AGB. In this study we use field measurements of individual trees within Laser Vegetation Imaging Sensor (LVIS) footprints along transects crossing forest to non-forest gradients to examine changes in LVIS waveform characteristics at sites with low (< 50Mg/ha) AGB. We relate field AGB measurements to original and adjusted LVIS waveforms to detect the forest AGB interval along a forest - non-forest transition in which the LVIS waveform lose the ability to discern differences in AGB. Our results help identify the lower end the forest biomass range that a ~20m footprint waveform LiDAR can detect, which can help infer accumulation of biomass after disturbances and during forest expansion, and which can guide the use of LiDAR within a multi-sensor fusion biomass mapping approach.

Light Detection and Ranging-Based Terrain Navigation: A Concept Exploration

NASA Technical Reports Server (NTRS)

Campbell, Jacob; UijtdeHaag, Maarten; vanGraas, Frank; Young, Steve

2003-01-01

This paper discusses the use of Airborne Light Detection And Ranging (LiDAR) equipment for terrain navigation. Airborne LiDAR is a relatively new technology used primarily by the geo-spatial mapping community to produce highly accurate and dense terrain elevation maps. In this paper, the term LiDAR refers to a scanning laser ranger rigidly mounted to an aircraft, as opposed to an integrated sensor system that consists of a scanning laser ranger integrated with Global Positioning System (GPS) and Inertial Measurement Unit (IMU) data. Data from the laser range scanner and IMU will be integrated with a terrain database to estimate the aircraft position and data from the laser range scanner will be integrated with GPS to estimate the aircraft attitude. LiDAR data was collected using NASA Dryden's DC-8 flying laboratory in Reno, NV and was used to test the proposed terrain navigation system. The results of LiDAR-based terrain navigation shown in this paper indicate that airborne LiDAR is a viable technology enabler for fully autonomous aircraft navigation. The navigation performance is highly dependent on the quality of the terrain databases used for positioning and therefore high-resolution (2 m post-spacing) data was used as the terrain reference.

Building block extraction and classification by means of aerial images fused with super-resolution reconstructed elevation data

NASA Astrophysics Data System (ADS)

Panagiotopoulou, Antigoni; Bratsolis, Emmanuel; Charou, Eleni; Perantonis, Stavros

2017-10-01

The detailed three-dimensional modeling of buildings utilizing elevation data, such as those provided by light detection and ranging (LiDAR) airborne scanners, is increasingly demanded today. There are certain application requirements and available datasets to which any research effort has to be adapted. Our dataset includes aerial orthophotos, with a spatial resolution 20 cm, and a digital surface model generated from LiDAR, with a spatial resolution 1 m and an elevation resolution 20 cm, from an area of Athens, Greece. The aerial images are fused with LiDAR, and we classify these data with a multilayer feedforward neural network for building block extraction. The innovation of our approach lies in the preprocessing step in which the original LiDAR data are super-resolution (SR) reconstructed by means of a stochastic regularized technique before their fusion with the aerial images takes place. The Lorentzian estimator combined with the bilateral total variation regularization performs the SR reconstruction. We evaluate the performance of our approach against that of fusing unprocessed LiDAR data with aerial images. We present the classified images and the statistical measures confusion matrix, kappa coefficient, and overall accuracy. The results demonstrate that our approach predominates over that of fusing unprocessed LiDAR data with aerial images.

Using LiDAR to Estimate Total Aboveground Biomass of Redwood Stands in the Jackson Demonstration State Forest, Mendocino, California

NASA Astrophysics Data System (ADS)

Rao, M.; Vuong, H.

2013-12-01

The overall objective of this study is to develop a method for estimating total aboveground biomass of redwood stands in Jackson Demonstration State Forest, Mendocino, California using airborne LiDAR data. LiDAR data owing to its vertical and horizontal accuracy are increasingly being used to characterize landscape features including ground surface elevation and canopy height. These LiDAR-derived metrics involving structural signatures at higher precision and accuracy can help better understand ecological processes at various spatial scales. Our study is focused on two major species of the forest: redwood (Sequoia semperirens [D.Don] Engl.) and Douglas-fir (Pseudotsuga mensiezii [Mirb.] Franco). Specifically, the objectives included linear regression models fitting tree diameter at breast height (dbh) to LiDAR derived height for each species. From 23 random points on the study area, field measurement (dbh and tree coordinate) were collected for more than 500 trees of Redwood and Douglas-fir over 0.2 ha- plots. The USFS-FUSION application software along with its LiDAR Data Viewer (LDV) were used to to extract Canopy Height Model (CHM) from which tree heights would be derived. Based on the LiDAR derived height and ground based dbh, a linear regression model was developed to predict dbh. The predicted dbh was used to estimate the biomass at the single tree level using Jenkin's formula (Jenkin et al 2003). The linear regression models were able to explain 65% of the variability associated with Redwood's dbh and 80% of that associated with Douglas-fir's dbh.

The effect of various factors on the dental arch relationship in non-syndromic unilateral cleft lip and palate children assessed by new approach: a retrospective study.

PubMed

Haque, Sanjida; Alam, Mohammad Khursheed; Khamis, Mohd Fadhli

2017-05-06

Cleft lip and palate (CLP) is one of the most common birth defects. Multiple factors are believed to be responsible for an unfavorable dental arch relationship in CLP. Facial growth (maxillary) retardation, which results in class III malocclusion, is the primary challenge that CLP patients face. Phenotype factors and postnatal treatment factors influence treatment outcomes in unilateral cleft lip and palate (UCLP) children, which has led to a great diversity in protocols and surgical techniques by various cleft groups worldwide. The aim of this study was to illustrate the dental arch relationship (DAR) and palatal morphology (PM) of UCLP in Bangladeshi children and to explore the various factors that are responsible for poor DAR and PM. Dental models of 84 subjects were taken before orthodontic treatment and alveolar bone grafting. The mean age was 7.69 (SD 2.46) years. The DAR and PM were assessed blindly by five raters using the EUROCRAN index (EI). Kappa statistics was used to evaluate the intra- and inter-examiner agreement, chi square was used to assess the associations, and logistic regression analysis was used to explore the responsible factors that affect DAR and PM. The mean EUROCRAN scores were 2.44 and 1.93 for DAR and PM, respectively. Intra- and inter-examiner agreement was moderate to very good. Using crude and stepwise backward regression analyses, significant associations were found between the modified Millard technique (P = 0.047, P = 0.034 respectively) of cheiloplasty and unfavorable DAR. Complete UCLP (P = 0.017) was also significantly correlated with unfavorable DAR. The PM showed a significant association with the type of cleft, type of cheiloplasty and type of palatoplasty. This multivariate study determined that the complete type of UCLP and the modified Millard technique of cheiloplasty had significantly unfavorable effects on both the DAR and PM.

Effects of LiDAR point density and landscape context on estimates of urban forest biomass

NASA Astrophysics Data System (ADS)

Singh, Kunwar K.; Chen, Gang; McCarter, James B.; Meentemeyer, Ross K.

2015-03-01

Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest assessment without compromising the accuracy of biomass estimates, and these estimates can be further improved using development density.

Forest structures retrieval from LiDAR onboard ULA

NASA Astrophysics Data System (ADS)

Shang, Xiaoxia; Chazette, Patrick; Totems, Julien; Marnas, Fabien; Sanak, Joseph

2013-04-01

Following the United Nations Framework Convention on Climate Change, the assessment of forest carbon stock is one of the main elements for a better understanding of the carbon cycle and its evolution following the climate change. The forests sequester 80% of the continental biospheric carbon and this efficiency is a function of the tree species and the tree health. The airborne backscatter LiDAR onboard the ultra light aircraft (ULA) can provide the key information on the forest vertical structures and evolution in the time. The most important structural parameter is the tree top height, which is directly linked to the above-ground biomass using non-linear relationships. In order to test the LiDAR capability for retrieving the tree top height, the LiDAR ULICE (Ultraviolet LIdar for Canopy Experiment) has been used over different forest types, from coniferous (maritime pins) to deciduous (oaks, hornbeams ...) trees. ULICE works at the wavelength of 355 nm with a sampling along the line-of-sight between 15 and 75 cm. According to the LiDAR signal to noise ratio (SNR), two different algorithms have been used in our study. The first algorithm is a threshold method directly based on the comparison between the LiDAR signal and the noise distributions, while the second one used a low pass filter by fitting a Gaussian curve family. In this paper, we will present these two algorithms and their evolution as a function of the SNR. The main error sources will be also discussed and assessed for each algorithm. The results show that these algorithms have great potential for ground-segment of future space borne LiDAR missions dedicated to the forest survey at the global scale. Acknowledgements: the canopy LiDAR system ULICE has been developed by CEA (Commissariat à l'Energie Atomique). It has been deployed with the support of CNES (Centre National d'Etude Spariales) and ANR (Agence Nationale de la Recherche). We acknowledge the ULA pilots Franck Toussaint for logistical help during the ULA campaign.

NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and aquatic organics.

Evaluation of thermochemical biomass conversion in fluidized bed =

NASA Astrophysics Data System (ADS)

Neves, Daniel dos Santos Felix das

Dado o aumento acelerado dos precos dos combustiveis fosseis e as incertezas quanto a sua disponibilidade futura, tem surgido um novo interesse nas tecnologias da biomassa aplicadas a producao de calor, eletricidade ou combustiveis sinteticos. Nao obstante, para a conversao termoquimica de uma particula de biomassa solida concorrem fenomenos bastante complexos que levam, em primeiro lugar, a secagem do combustivel, depois a pirolise e finalmente a combustao ou gasificacao propriamente ditas. Uma descricao relativamente incompleta de alguns desses estagios de conversao constitui ainda um obstaculo ao desenvolvimento das tecnologias que importa ultrapassar. Em particular, a presenca de elevados conteudos de materia volatil na biomassa poe em evidencia o interesse pratico do estudo da pirolise. A importância da pirolise durante a combustao de biomassa foi evidenciada neste trabalho atraves de ensaios realizados num reator piloto de leito fluidizado borbulhante. Verificou-se que o processo ocorre em grande parte a superficie do leito com chamas de difusao devido a libertacao de volateis, o que dificulta o controlo da temperatura do reator acima do leito. No caso da gasificacao de biomassa a pirolise pode inclusivamente determinar a eficiencia quimica do processo. Isso foi mostrado neste trabalho durante ensaios de gasificacao num reator de leito fluidizado de 2MWth, onde um novo metodo de medicao permitiu fechar o balanco de massa ao gasificador e monitorizar o grau de conversao da biomassa. A partir destes resultados tornou-se clara a necessidade de descrever adequadamente a pirolise de biomassa com vista ao projeto e controlo dos processos. Em aplicacoes de engenharia ha particular interesse na estequiometria e propriedades dos principais produtos piroliticos. Neste trabalho procurou-se responder a esta necessidade, inicialmente atraves da estruturacao de dados bibliograficos sobre rendimentos de carbonizado, liquidos piroliticos e gases, assim como composicoes elementares e poderes calorificos. O resultado traduziu-se num conjunto de parâmetros empiricos de interesse pratico que permitiram elucidar o comportamento geral da pirolise de biomassa numa gama ampla de condicoes operatorias. Para alem disso, propos-se um modelo empirico para a composicao dos volateis que pode ser integrado em modelos compreensivos de reatores desde que os parâmetros usados sejam adequados ao combustivel ensaiado. Esta abordagem despoletou um conjunto de ensaios de pirolise com varias biomassas, lenhina e celulose, e temperaturas entre os 600 e 975ºC. Elevadas taxas de aquecimento do combustivel foram alcancadas em reatores laboratoriais de leito fluidizado borbulhante e leito fixo, ao passo que um sistema termo-gravimetrico permitiu estudar o efeito de taxas de aquecimento mais baixas. Os resultados mostram que, em condicoes tipicas de processos de combustao e gasificacao, a quantidade de volateis libertada da biomassa e pouco influenciada pela temperatura do reator mas varia bastante entre combustiveis. Uma analise mais aprofundada deste assunto permitiu mostrar que o rendimento de carbonizado esta intimamente relacionado com o racio O/C do combustivel original, sendo proposto um modelo simples para descrever esta relacao. Embora a quantidade total de volateis libertada seja estabelecida pela composicao da biomassa, a respetiva composicao quimica depende bastante da temperatura do reator. Rendimentos de especies condensaveis (agua e especies orgânicas), CO2 e hidrocarbonetos leves descrevem um maximo relativamente a temperatura para dar lugar a CO e H2 as temperaturas mais altas. Nao obstante, em certas gamas de temperatura, os rendimentos de algumas das principais especies gasosas (e.g. CO, H2, CH4) estao bem correlacionados entre si, o que permitiu desenvolver modelos empiricos que minimizam o efeito das condicoes operatorias e, ao mesmo tempo, realcam o efeito do combustivel na composicao do gas. Em suma, os ensaios de pirolise realizados neste trabalho permitiram constatar que a estequiometria da pirolise de biomassa se relaciona de varias formas com a composicao elementar do combustivel original o que levanta varias possibilidades para a avaliacao e projeto de processos de combustao e gasificacao de biomassa.

LiDAR point classification based on sparse representation

NASA Astrophysics Data System (ADS)

Li, Nan; Pfeifer, Norbert; Liu, Chun

2017-04-01

In order to combine the initial spatial structure and features of LiDAR data for accurate classification. The LiDAR data is represented as a 4-order tensor. Sparse representation for classification(SRC) method is used for LiDAR tensor classification. It turns out SRC need only a few of training samples from each class, meanwhile can achieve good classification result. Multiple features are extracted from raw LiDAR points to generate a high-dimensional vector at each point. Then the LiDAR tensor is built by the spatial distribution and feature vectors of the point neighborhood. The entries of LiDAR tensor are accessed via four indexes. Each index is called mode: three spatial modes in direction X ,Y ,Z and one feature mode. Sparse representation for classification(SRC) method is proposed in this paper. The sparsity algorithm is to find the best represent the test sample by sparse linear combination of training samples from a dictionary. To explore the sparsity of LiDAR tensor, the tucker decomposition is used. It decomposes a tensor into a core tensor multiplied by a matrix along each mode. Those matrices could be considered as the principal components in each mode. The entries of core tensor show the level of interaction between the different components. Therefore, the LiDAR tensor can be approximately represented by a sparse tensor multiplied by a matrix selected from a dictionary along each mode. The matrices decomposed from training samples are arranged as initial elements in the dictionary. By dictionary learning, a reconstructive and discriminative structure dictionary along each mode is built. The overall structure dictionary composes of class-specified sub-dictionaries. Then the sparse core tensor is calculated by tensor OMP(Orthogonal Matching Pursuit) method based on dictionaries along each mode. It is expected that original tensor should be well recovered by sub-dictionary associated with relevant class, while entries in the sparse tensor associated with other classed should be nearly zero. Therefore, SRC use the reconstruction error associated with each class to do data classification. A section of airborne LiDAR points of Vienna city is used and classified into 6classes: ground, roofs, vegetation, covered ground, walls and other points. Only 6 training samples from each class are taken. For the final classification result, ground and covered ground are merged into one same class(ground). The classification accuracy for ground is 94.60%, roof is 95.47%, vegetation is 85.55%, wall is 76.17%, other object is 20.39%.

The Uncertainty of Biomass Estimates from Modeled ICESat-2 Returns Across a Boreal Forest Gradient

NASA Technical Reports Server (NTRS)

Montesano, P. M.; Rosette, J.; Sun, G.; North, P.; Nelson, R. F.; Dubayah, R. O.; Ranson, K. J.; Kharuk, V.

2014-01-01

The Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg · ha(exp -1) interval in the 0-100 Mg · ha(exp -1) above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined. Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for approximately 67% of all LiDAR returns, while approximately 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p greater than 0.05) for AGB intervals greater than 20 Mg · ha(exp -1). The 50m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model fits and minimizes forest structure uncertainty in the synthetic Larix stands. At this link-scale AGB greater than 20 Mg · ha(exp -1) has AGB error from 20-50% at the 95% confidence level. These results suggest that the theoretical sensitivity of ICESat-2 photon counting LiDAR measurements alone lack the ability to consistently discern differences in inferred AGB at 10 Mg · ha(exp -1) intervals in sparse forests characteristic of the taiga-tundra ecotone.

KML-Based Access and Visualization of High Resolution LiDAR Topography

NASA Astrophysics Data System (ADS)

Crosby, C. J.; Blair, J. L.; Nandigam, V.; Memon, A.; Baru, C.; Arrowsmith, J. R.

2008-12-01

Over the past decade, there has been dramatic growth in the acquisition of LiDAR (Light Detection And Ranging) high-resolution topographic data for earth science studies. Capable of providing digital elevation models (DEMs) more than an order of magnitude higher resolution than those currently available, LiDAR data allow earth scientists to study the processes that contribute to landscape evolution at resolutions not previously possible yet essential for their appropriate representation. These datasets also have significant implications for earth science education and outreach because they provide an accurate representation of landforms and geologic hazards. Unfortunately, the massive volume of data produced by LiDAR mapping technology can be a barrier to their use. To make these data available to a larger user community, we have been exploring the use of Keyhole Markup Language (KML) and Google Earth to provide access to LiDAR data products and visualizations. LiDAR digital elevation models are typically delivered in a tiled format that lends itself well to a KML-based distribution system. For LiDAR datasets hosted in the GEON OpenTopography Portal (www.opentopography.org) we have developed KML files that show the extent of available LiDAR DEMs and provide direct access to the data products. Users interact with these KML files to explore the extent of the available data and are able to select DEMs that correspond to their area of interest. Selection of a tile loads a download that the user can then save locally for analysis in their software of choice. The GEON topography system also has tools available that allow users to generate custom DEMs from LiDAR point cloud data. This system is powerful because it enables users to access massive volumes of raw LiDAR data and to produce DEM products that are optimized to their science applications. We have developed a web service that converts the custom DEM models produced by the system to a hillshade that is delivered to the user as a KML groundoverlay. The KML product enables users to quickly and easily visualize the DEMs in Google Earth. By combining internet-based LiDAR data processing with KML visualization products, users are able to execute computationally intensive data sub-setting, processing and visualization without having local access to computing resources, GIS software, or data processing expertise. Finally, GEON has partnered with the US Geological Survey to generate region-dependant network linked KML visualizations for large volumes of LiDAR derived hillshades of the Northern San Andreas fault system. These data, acquired by the NSF-funded GeoEarthScope project, offer an unprecedented look at active faults in the northern portion of the San Andreas system. Through the region-dependant network linked KML, users can seamlessly access 1 meter hillshades (both 315 and 45 degree sun angles) for the full 1400 square kilometer dataset, without downloading huge volumes of data. This type of data access has great utility for users ranging from earthquake scientists to K-12 educators who wish to introduce cutting edge real world data into their earth science lessons.

Delayed adverse reactions to the parenteral administration of iodinated contrast media.

PubMed

Egbert, Robert E; De Cecco, Carlo N; Schoepf, U Joseph; McQuiston, Andrew D; Meinel, Felix G; Katzberg, Richard W

2014-12-01

This article presents an overview of delayed adverse reactions (DARs) to parenteral iodinated contrast media and discusses the clinical nature, risk factors, mechanisms, and potential economic implications of these DARs. DARs to contrast media are not rare but are often not recognized as being linked to contrast administration and may be falsely ascribed to other drugs. These side effects are problematic because the patient is usually without medical supervision.

Use of LiDAR to Assist in Delineating Waters of the United States, Including Wetlands

DTIC Science & Technology

2014-03-01

investigator’s objective. For example, if the sole objective is to identify geomorphic breaks in slope associated with the OHWM, points representing vegetation... geomorphic position. During the data-gathering stage of wetland delinea- tions, measurements made using LiDAR data should be considered esti- mates...field. Field validation of LiDAR topographic data is essential before using them as evidence of a secondary hydrology indicator, such as geomorphic

ASSESSMENT FORM - NEW IMPROVEMENT OF ACTIONS: CONCENTRATION AND RESEARCH AREAS / CURRICULUM STRUCTURE / FUNDRAISING.

PubMed

Calderon, Iracema Mp

2015-01-01

This review aims to develop a critical and current analysis of the basic structure of a Postgraduate program for proposing improvement actions and new evaluation criteria. To examine the items that are areas of concentration (AC), research lines (LP), research projects (PP), curricular structure and fundraising were consulted the Area Document, the 2013 Evaluation Report and the Assessment Sheets of Medicine III programs, evaluated in the 2010-2012 period. Consistency is recommended especially among AC, LP and PP, with genuine link between activities and permanent teachers skills and based on structured curriculum in the education of the student. The Program Proposal interfere, and much, in qualifying a program. The curriculum should provide subsidy to the formation of the researcher, through the core subjects, and development of PP, being the concept of disciplines to support lines and research projects. Fundraise should be set out in research projects and in the CV-Lattes. The area recommended that at least 40-50% of permanent teachers present fundraising and the minimum 20-25% of these teachers to have productivity scholarship PQ / CNPq during the triennium. It is necessary to promote wide discussion and find a consensus denominator for these issues. The actions should contribute to the improvement of evaluation forms and certainly for the qualification of the programs but graduate. Essa revisão tem como objetivo elaborar uma análise crítica e atual da estrutura básica de um programa de Pós-Graduação para a proposição de ações de aperfeiçoamento e novos critérios de avaliação. Para analisarem-se os itens áreas de concentração (AC), linhas de pesquisa (LP), projetos de pesquisa (PP), estrutura curricular e captação de recursos/fomentos foram consultados o documento de área, o relatório de avaliação 2013 e as fichas de avaliação dos programas da Medicina III, avaliados no triênio 2010-2012. A coerência é recomendada especialmente entre AC, LP e PP, com substancial vínculo entre atividades e competências do corpo de docentes permanentes e embasamento da grade curricular na formação do aluno. A Proposta do Programa interfere, e muito, na qualificação de um programa. A estrutura curricular deverá dar subsídio à formação do pesquisador, por meio das disciplinas nucleares, e ao desenvolvimento dos PP, de competência das disciplinas de apoio às linhas e aos projetos de pesquisa. Os fomentos devem ser indicados nos projetos de pesquisa e no CV-Lattes dos beneficiados/responsáveis pelos projetos. A área recomenda que, no mínimo, 40 a 50% dos docentes permanentes apresentem captação de recursos e que o mínimo de 20 a 25% desses docentes tenham bolsa de produtividade PQ/CNPq durante o triênio. Há que se promover ampla discussão e encontrar um denominador de consenso para essas questões. As ações deverão contribuir para o aprimoramento das fichas de avaliação e, certamente, para a qualificação dos programas de pós-graduação.

Cellular-V2X Communications for Platooning: Design and Evaluation

PubMed Central

2018-01-01

Platooning is a cooperative driving application where autonomous/semi-autonomous vehicles move on the same lane in a train-like manner, keeping a small constant inter-vehicle distance, in order to reduce fuel consumption and gas emissions and to achieve safe and efficient transport. To this aim, they may exploit multiple on-board sensors (e.g., radars, LiDARs, positioning systems) and direct vehicle-to-vehicle communications to synchronize their manoeuvres. The main objective of this paper is to discuss the design choices and factors that determine the performance of a platooning application, when exploiting the emerging cellular vehicle-to-everything (C-V2X) communication technology and considering the scheduled mode, specified by 3GPP for communications over the sidelink assisted by the eNodeB. Since no resource management algorithm is currently mandated by 3GPP for this new challenging context, we focus on analyzing the feasibility and performance of the dynamic scheduling approach, with platoon members asking for radio resources on a per-packet basis. We consider two ways of implementing dynamic scheduling, currently unspecified by 3GPP: the sequential mode, that is somehow reminiscent of time division multiple access solutions based on IEEE 802.11p—till now the only investigated access technology for platooning—and the simultaneous mode with spatial frequency reuse enabled by the eNodeB. The evaluation conducted through system-level simulations provides helpful insights about the proposed configurations and C-V2X parameter settings that mainly affect the reliability and latency performance of data exchange in platoons, under different load settings. Achieved results show that the proposed simultaneous mode succeeds in reducing the latency in the update cycle in each vehicle’s controller, thus enabling future high-density platooning scenarios. PMID:29751690

Patterns of Reproductive Isolation in Eucalyptus-A Phylogenetic Perspective.

PubMed

Larcombe, Matthew J; Holland, Barbara; Steane, Dorothy A; Jones, Rebecca C; Nicolle, Dean; Vaillancourt, René E; Potts, Brad M

2015-07-01

We assess phylogenetic patterns of hybridization in the speciose, ecologically and economically important genus Eucalyptus, in order to better understand the evolution of reproductive isolation. Eucalyptus globulus pollen was applied to 99 eucalypt species, mainly from the large commercially important subgenus, Symphyomyrtus. In the 64 species that produce seeds, hybrid compatibility was assessed at two stages, hybrid-production (at approximately 1 month) and hybrid-survival (at 9 months), and compared with phylogenies based on 8,350 genome-wide DArT (diversity arrays technology) markers. Model fitting was used to assess the relationship between compatibility and genetic distance, and whether or not the strength of incompatibility "snowballs" with divergence. There was a decline in compatibility with increasing genetic distance between species. Hybridization was common within two closely related clades (one including E. globulus), but rare between E. globulus and species in two phylogenetically distant clades. Of three alternative models tested (linear, slowdown, and snowball), we found consistent support for a snowball model, indicating that the strength of incompatibility accelerates relative to genetic distance. Although we can only speculate about the genetic basis of this pattern, it is consistent with a Dobzhansky-Muller-model prediction that incompatibilities should snowball with divergence due to negative epistasis. Different rates of compatibility decline in the hybrid-production and hybrid-survival measures suggest that early-acting postmating barriers developed first and are stronger than later-acting barriers. We estimated that complete reproductive isolation can take up to 21-31 My in Eucalyptus. Practical implications for hybrid eucalypt breeding and genetic risk assessment in Australia are discussed. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Cellular-V2X Communications for Platooning: Design and Evaluation.

PubMed

Nardini, Giovanni; Virdis, Antonio; Campolo, Claudia; Molinaro, Antonella; Stea, Giovanni

2018-05-11

Platooning is a cooperative driving application where autonomous/semi-autonomous vehicles move on the same lane in a train-like manner, keeping a small constant inter-vehicle distance, in order to reduce fuel consumption and gas emissions and to achieve safe and efficient transport. To this aim, they may exploit multiple on-board sensors (e.g., radars, LiDARs, positioning systems) and direct vehicle-to-vehicle communications to synchronize their manoeuvres. The main objective of this paper is to discuss the design choices and factors that determine the performance of a platooning application, when exploiting the emerging cellular vehicle-to-everything (C-V2X) communication technology and considering the scheduled mode, specified by 3GPP for communications over the sidelink assisted by the eNodeB. Since no resource management algorithm is currently mandated by 3GPP for this new challenging context, we focus on analyzing the feasibility and performance of the dynamic scheduling approach, with platoon members asking for radio resources on a per-packet basis. We consider two ways of implementing dynamic scheduling, currently unspecified by 3GPP: the sequential mode, that is somehow reminiscent of time division multiple access solutions based on IEEE 802.11p-till now the only investigated access technology for platooning-and the simultaneous mode with spatial frequency reuse enabled by the eNodeB. The evaluation conducted through system-level simulations provides helpful insights about the proposed configurations and C-V2X parameter settings that mainly affect the reliability and latency performance of data exchange in platoons, under different load settings. Achieved results show that the proposed simultaneous mode succeeds in reducing the latency in the update cycle in each vehicle's controller, thus enabling future high-density platooning scenarios.

Surface expression of intraplate postglacial faults in Sweden: from LiDAR data

NASA Astrophysics Data System (ADS)

Abduljabbar, Mawaheb; Ask, Maria; Bauer, Tobias; Lund, Björn; Smith, Colby; Mikko, Henrik; Munier, Raymond

2016-04-01

Large intraplate earthquakes, up to magnitude 8.0±0.3 (Lindblom et al. 2015) are inferred to have occurred in northern Fennoscandia at the end of, or just after the Weichselian deglaciation. More than a dozen large so-called postglacial faults (PGF) have been found in the region. The present-day microseismic activity is rather high in north Sweden, and there is a correlation between microseismicity and mapped PGF scarps: 71% of the observed earthquakes north of 66°N locate within 30 km to the southeast and 10 km to the northwest of PGFs (Lindblom et al., 2015). Surface expressions of PGFs in Sweden have mainly been mapped using aerial photogrammetry and trenching (e.g. Lagerbäck & Sundh 2008). Their detailed surface geometry may be investigated using the new high-resolution elevation model of Sweden (NNH) that has a vertical- and lateral resolution of 2 m and 0.25 m, respectively. With NNH data, known PGFs have been modified, and a number of new potential PGFs have been identified (Smith et al. 2014; Mikko et al. 2015). However, the detailed variation of their surface expression remains to be determined. Our main objective is to constrain the strike and surface offset (i.e., apparent vertical throw because of soil cover overlays the bedrock) across the PGF scarps. We anticipate using the results to constrain direction of fault motion and paleomagnitudes of PGFs, and in numerical analyzes to investigate the nature of PGFs. We have developed a methodology for analyzing PGF-geomorphology from LiDAR data using two main software platforms (Ask et al. 2015): (1) Move2015 by Midland Valley has been used for constructing 3D models of the surface traces of the PGFs to determine apparent vertical throw. The apparent hanging- and footwall cut off lines are digitized, and subsequent computation of coordinates is rather time efficient and provide continuous data of fault and soil geomorphology that can be statistically analyzed; and (2) ArcGIS 10.3 by Esri has mostly been used to derive the slope model for the study area. We successfully tested the methodology within a limited area of the Pärvie fault zone, which is the longest known PGF in the world (Ask et al. 2015). Here, we apply the methodology to PGFs in northern Sweden. Additionally, we are planning to analyse PGFs within a virtual reality environment utilizing the GeoVisionary software platform by Virtalis Ltd. in order to increase accuracy and efficiency and to decrease modelling uncertainties. References Ask et al. 2015. Geomorphology of intraplate postglacial faults in Sweden. AGU, Abstract #83167 Lindblom, et al., 2015. Microearthquakes illuminate the deep structure of the endglacial Pärvie fault, northern Sweden. doi: 10.1093/gji/ggv112 Lagerbäck & Sundh, 2008. Early Holocene faulting and paleoseismicity in northern Sweden. http://resource.sgu.se/produkter/c/c836-rapport.pdf Mikko, et al. 2015. LiDAR-derived inventory of post-glacial fault scarps in Sweden. doi:10.1080/11035897.2015.1036360 Smith, et al., 2014. Surficial geology indicates early Holocene faulting and seismicity, central Sweden. doi: 10.1007/s00531-014-1025-6

High resolution digital autoradiographic and dosimetric analysis of heterogeneous radioactivity distribution in xenografted prostate tumors.

PubMed

Timmermand, Oskar V; Nilsson, Jenny; Strand, Sven-Erik; Elgqvist, Jörgen

2016-12-01

The first main aim of this study was to illustrate the absorbed dose rate distribution from 177 Lu in sections of xenografted prostate cancer (PCa) tumors using high resolution digital autoradiography (DAR) and compare it with hypothetical identical radioactivity distributions of 90 Y or 7 MeV alpha-particles. Three dosimetry models based on either dose point kernels or Monte Carlo simulations were used and evaluated. The second and overlapping aim, was to perform DAR imaging and dosimetric analysis of the distribution of radioactivity, and hence the absorbed dose rate, in tumor sections at an early time point after injection during radioimmunotherapy using 177 Lu-h11B6, directed against the human kallikrein 2 antigen. Male immunodeficient BALB/c nude mice, aged 6-8 w, were inoculated by subcutaneous injection of ∼10 7 LNCaP cells in a 200 μl suspension of a 1:1 mixture of medium and Matrigel. The antibody h11B6 was conjugated with the chelator CHX-A″-DTPA after which conjugated h11B6 was mixed with 177 LuCl 3 . The incubation was performed at room temperature for 2 h, after which the labeling was terminated and the solution was purified on a NAP-5 column. About 20 MBq 177 Lu-h11B6 was injected intravenously in the tail vein. At approximately 10 h postinjection (hpi), the mice were sacrificed and one tumor was collected from each of the five animals and cryosectioned into 10 μm thick slices. The tumor slices were measured and imaged using the DAR MicroImager system and the M3Vision software. Then the absorbed dose rate was calculated using a dose point kernel generated with the Monte Carlo code gate v7.0. The DAR system produced high resolution images of the radioactivity distribution, close to the resolution of single PCa cells. The DAR images revealed a pronounced heterogeneous radioactivity distribution, i.e., count rate per area, in the tumors, indicated by the normalized intensity variations along cross sections as mean ± SD: 0.15 ± 0.15, 0.20 ± 0.18, 0.12 ± 0.17, 0.15 ± 0.16, and 0.23 ± 0.22, for each tumor section, respectively. The absorbed dose rate distribution for 177 Lu at the time of dissection 10 hpi showed a maximum value of 2.9 ± 0.4 Gy/h (mean ± SD), compared to 6.0 ± 0.9 and 159 ± 25 Gy/h for the hypothetical 90 Y and 7 MeV alpha-particle cases assuming the same count rate densities. Mean absorbed dose rate values were 0.13, 0.53, and 6.43 Gy/h for 177 Lu, 90 Y, and alpha-particles, respectively. The initial uptake of 177 Lu-h11B6 produces a high absorbed dose rate, which is important for a successful therapeutic outcome. The hypothetical 90 Y case indicates a less heterogeneous absorbed dose rate distribution and a higher mean absorbed dose rate compared to 177 Lu, although with a potentially increased irradiation of surrounding healthy tissue. The hypothetical alpha-particle case indicates the possibility of a higher maximum absorbed dose rate, although with a more heterogeneous absorbed dose rate distribution.

Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

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

Danny L. Anderson

Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates amore » new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed “mDn”, is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mDn method yielded the smallest LRMSE.« less

Integrating LiDAR Data into Earth Science Education

NASA Astrophysics Data System (ADS)

Robinson, S. E.; Arrowsmith, R.; de Groot, R. M.; Crosby, C. J.; Whitesides, A. S.; Colunga, J.

2010-12-01

The use of high-resolution topography derived from Light Detection and Ranging (LiDAR) in the study of active tectonics is widespread and has become an indispensable tool to better understand earthquake hazards. For this reason and the spectacular representation of the phenomena the data provide, it is appropriate to integrate these data into the Earth science education curriculum. A collaboration between Arizona State University, the OpenTopography Facility, and the Southern California Earthquake Center are developing, three earth science education products to inform students and other audiences about LiDAR and its application to active tectonics research. First, a 10-minute introductory video titled LiDAR: Illuminating Earthquakes was produced and is freely available online through the OpenTopography portal and SCEC. The second product is an update and enhancement of the Wallace Creek Interpretive Trail website (www.scec.org/wallacecreek). LiDAR topography data products have been added along with the development of a virtual tour of the offset channels at Wallace Creek using the B4 LiDAR data within the Google Earth environment. The virtual tour to Wallace Creek is designed as a lab activity for introductory undergraduate geology courses to increase understanding of earthquake hazards through exploration of the dramatic offset created by the San Andreas Fault (SAF) at Wallace Creek and Global Positioning System-derived displacements spanning the SAF at Wallace Creek . This activity is currently being tested in courses at Arizona State University. The goal of the assessment is to measure student understanding of plate tectonics and earthquakes after completing the activity. Including high-resolution topography LiDAR data into the earth science education curriculum promotes understanding of plate tectonics, faults, and other topics related to earthquake hazards.

LiDAR data and SAR imagery acquired by an unmanned helicopter for rapid landslide investigation

NASA Astrophysics Data System (ADS)

Kasai, M.; Tanaka, Y.; Yamazaki, T.

2012-12-01

When earthquakes or heavy rainfall hits a landslide prone area, initial actions require estimation of the size of damage to people and infrastructure. This includes identifying the number and size of newly collapsed or expanded landslides, and appraising subsequent risks from remobilization of landslides and debris materials. In inapproachable areas, the UAV (Unmanned Aerial Vehicles) is likely to be of greatest use. In addition, repeat monitoring of sites after the event is a way of utilizing UAVs, particularly in terms of cost and convenience. In this study, LiDAR (SkEyesBox MP-1) data and SAR (Nano SAR) imagery, acquired over 0.5 km2 landslide prone area, are presented to assess the practicability of using unmanned helicopters (in this case a 10 year old YAMAHA RMAX G1) in these situations. LiDAR data was taken in July 2012, when tree foliage covered the ground surface. However, imagery was of sufficient quality to identify and measure landslide features. Nevertheless, LiDAR data obtained by a manned helicopter in the same area in August 2008 was more detailed, reflecting the function of the LiDAR scanner. On the other hand, 2 m resolution Nano SAR imagery produced reasonable results to elucidate hillslope condition. A quick method for data processing without loss of image quality was also investigated. In conclusion, the LiDAR scanner and UAV employed here could be used to plan immediate remedial activity of the area, before LiDAR measurement with a manned helicopter can be organized. SAR imagery from UAV is also available for this initial activity, and can be further applied to long term monitoring.

Estimating stem volume and biomass of Pinus koraiensis using LiDAR data.

PubMed

Kwak, Doo-Ahn; Lee, Woo-Kyun; Cho, Hyun-Kook; Lee, Seung-Ho; Son, Yowhan; Kafatos, Menas; Kim, So-Ra

2010-07-01

The objective of this study was to estimate the stem volume and biomass of individual trees using the crown geometric volume (CGV), which was extracted from small-footprint light detection and ranging (LiDAR) data. Attempts were made to analyze the stem volume and biomass of Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes of tree density: low (240 N/ha), medium (370 N/ha), and high (1,340 N/ha). To delineate individual trees, extended maxima transformation and watershed segmentation of image processing methods were applied, as in one of our previous studies. As the next step, the crown base height (CBH) of individual trees has to be determined; information for this was found in the LiDAR point cloud data using k-means clustering. The LiDAR-derived CGV and stem volume can be estimated on the basis of the proportional relationship between the CGV and stem volume. As a result, low tree-density plots had the best performance for LiDAR-derived CBH, CGV, and stem volume (R (2) = 0.67, 0.57, and 0.68, respectively) and accuracy was lowest for high tree-density plots (R (2) = 0.48, 0.36, and 0.44, respectively). In the case of medium tree-density plots accuracy was R (2) = 0.51, 0.52, and 0.62, respectively. The LiDAR-derived stem biomass can be predicted from the stem volume using the wood basic density of coniferous trees (0.48 g/cm(3)), and the LiDAR-derived above-ground biomass can then be estimated from the stem volume using the biomass conversion and expansion factors (BCEF, 1.29) proposed by the Korea Forest Research Institute (KFRI).

Modeling Diurnal and Seasonal 3D Light Profiles in Amazon Forests

NASA Astrophysics Data System (ADS)

Morton, D. C.; Rubio, J.; Gastellu-Etchegorry, J.; Cook, B. D.; Hunter, M. O.; Yin, T.; Nagol, J. R.; Keller, M. M.

2013-12-01

The complex horizontal and vertical structure in tropical forests generates a diversity of light environments for canopy and understory trees. These 3D light profiles are dynamic on diurnal and seasonal time scales based on changes in solar illumination and the fraction of diffuse light. Understanding this variability is critical for improving ecosystem models and interpreting optical and LiDAR remote sensing data from tropical forests. Here, we initialized the Discrete Anisotropic Radiative Transfer (DART) model using dense airborne LiDAR data (>20 returns m2) from three forest sites in the central and eastern Amazon. Forest scenes derived from airborne LiDAR data were tested using modeled and observed large-footprint LiDAR data from the ICESat-GLAS sensor. Next, diurnal and seasonal profiles of photosynthetically active radiation (PAR) for each forest site were simulated under clear sky and cloudy conditions using DART. Incident PAR was summarized for canopy, understory, and ground levels. Our study illustrates the importance of realistic canopy models for accurate representation of LiDAR and optical radiative transfer. In particular, canopy rugosity and ground topography information from airborne LiDAR data provided critical 3D information that cannot be recreated using stem maps and allometric relationships for crown dimensions. The spatial arrangement of canopy trees altered PAR availability, even for dominant individuals, compared to downwelling measurements from nearby eddy flux towers. Pseudo-realistic branch and leaf architecture was also essential for recreating multiple scattering within canopies at near-infrared wavelengths commonly used for LiDAR remote sensing and quantifying PAR attenuation from shading within and between canopies. These findings point to the need for more spatial information on forest structure to improve the representation of light availability in models of tropical forest productivity.

DTMs Assessment to the Definition of Shallow Landslides Prone Areas

NASA Astrophysics Data System (ADS)

Martins, Tiago D.; Oka-Fiori, Chisato; Carvalho Vieira, Bianca; Montgomery, David R.

2017-04-01

Predictive methods have been developed, especially since the 1990s, to identify landslide prone areas. One of the examples it is the physically based model SHALSTAB (Shallow Landsliding Stability Model), that calculate the potential instability for shallow landslides based on topography and physical soil properties. Normally, in such applications in Brazil, the Digital Terrain Model (DTM), is obtained mainly from conventional contour lines. However, recently the LiDAR (Light Detection and Ranging) system has been largely used in Brazil. Thus, this study aimed to evaluate different DTM's, generated from conventional data and LiDAR, and their influence in generating susceptibility maps to shallow landslides using SHALSTAB model. For that were analyzed the physical properties of soil, the response of the model when applying conventional topographical data and LiDAR's in the generation of DTM, and the shallow landslides susceptibility maps based on different topographical data. The selected area is in the urban perimeter of the municipality of Antonina (PR), affected by widespread landslides in March 2011. Among the results, it was evaluated different LiDAR data interpolation, using GIS tools, wherein the Triangulation/Natural Neighbor presented the best performance. It was also found that in one of evaluation indexes (Scars Concentration), the LiDAR derived DTM presented the best performance when compared with the one originated from contour lines, however, the Landslide Potential index, has presented a small increase. Consequently, it was possible to assess the DTM's, and the one derived from LiDAR improved very little the certitude percentage. It is also noted a gap in researches carried out in Brazil on the use of products generated from LiDAR data on geomorphological analysis.

Design, construction, and testing of the direct absorption receiver panel research experiment

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

Chavez, J.M.; Rush, E.E.; Matthews, C.W.

1990-01-01

A panel research experiment (PRE) was designed, built, and tested as a scaled-down model of a direct absorption receiver (DAR). The PRE is a 3-MW{sub t}DAR experiment that will allow flow testing with molten nitrate salt and provide a test bed for DAR testing with actual solar heating. In a solar central receiver system DAR, the heat absorbing fluid (a blackened molten nitrate salt) flows in a thin film down a vertical panel (rather than through tubes as in conventional receiver designs) and absorbs the concentrated solar flux directly. The ability of the flowing salt film to absorb flux directly.more » The ability of the flowing salt film to absorb the incident solar flux depends on the panel design, hydraulic and thermal fluid flow characteristics, and fluid blackener properties. Testing of the PRE is being conducted to demonstrate the engineering feasibility of the DAR concept. The DAR concept is being investigated because it offers numerous potential performance and economic advantages for production of electricity when compared to other solar receiver designs. The PRE utilized a 1-m wide by 6-m long absorber panel. The salt flow tests are being used to investigate component performance, panel deformations, and fluid stability. Salt flow testing has demonstrated that all the DAR components work as designed and that there are fluid stability issues that need to be addressed. Future solar testing will include steady-state and transient experiments, thermal loss measurements, responses to severe flux and temperature gradients and determination of peak flux capability, and optimized operation. In this paper, we describe the design, construction, and some preliminary flow test results of the Panel Research Experiment. 11 refs., 8 figs., 2 tabs.« less

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models

PubMed Central

2018-01-01

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the ‘Internet of Things’ (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds. PMID:29748521

Wind turbine wake characterization from temporally disjunct 3-D measurements

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

Doubrawa, Paula; Barthelmie, Rebecca J.; Wang, Hui

Scanning LiDARs can be used to obtain three-dimensional wind measurements in and beyond the atmospheric surface layer. In this work, metrics characterizing wind turbine wakes are derived from LiDAR observations and from large-eddy simulation (LES) data, which are used to recreate the LiDAR scanning geometry. The metrics are calculated for two-dimensional planes in the vertical and cross-stream directions at discrete distances downstream of a turbine under single-wake conditions. The simulation data are used to estimate the uncertainty when mean wake characteristics are quantified from scanning LiDAR measurements, which are temporally disjunct due to the time that the instrument takes tomore » probe a large volume of air. Based on LES output, we determine that wind speeds sampled with the synthetic LiDAR are within 10% of the actual mean values and that the disjunct nature of the scan does not compromise the spatial variation of wind speeds within the planes. We propose scanning geometry density and coverage indices, which quantify the spatial distribution of the sampled points in the area of interest and are valuable to design LiDAR measurement campaigns for wake characterization. Lastly, we find that scanning geometry coverage is important for estimates of the wake center, orientation and length scales, while density is more important when seeking to characterize the velocity deficit distribution.« less

Wind turbine wake characterization from temporally disjunct 3-D measurements

DOE PAGES

Doubrawa, Paula; Barthelmie, Rebecca J.; Wang, Hui; ...

2016-11-10

Scanning LiDARs can be used to obtain three-dimensional wind measurements in and beyond the atmospheric surface layer. In this work, metrics characterizing wind turbine wakes are derived from LiDAR observations and from large-eddy simulation (LES) data, which are used to recreate the LiDAR scanning geometry. The metrics are calculated for two-dimensional planes in the vertical and cross-stream directions at discrete distances downstream of a turbine under single-wake conditions. The simulation data are used to estimate the uncertainty when mean wake characteristics are quantified from scanning LiDAR measurements, which are temporally disjunct due to the time that the instrument takes tomore » probe a large volume of air. Based on LES output, we determine that wind speeds sampled with the synthetic LiDAR are within 10% of the actual mean values and that the disjunct nature of the scan does not compromise the spatial variation of wind speeds within the planes. We propose scanning geometry density and coverage indices, which quantify the spatial distribution of the sampled points in the area of interest and are valuable to design LiDAR measurement campaigns for wake characterization. Lastly, we find that scanning geometry coverage is important for estimates of the wake center, orientation and length scales, while density is more important when seeking to characterize the velocity deficit distribution.« less

Waveform fitting and geometry analysis for full-waveform lidar feature extraction

NASA Astrophysics Data System (ADS)

Tsai, Fuan; Lai, Jhe-Syuan; Cheng, Yi-Hsiu

2016-10-01

This paper presents a systematic approach that integrates spline curve fitting and geometry analysis to extract full-waveform LiDAR features for land-cover classification. The cubic smoothing spline algorithm is used to fit the waveform curve of the received LiDAR signals. After that, the local peak locations of the waveform curve are detected using a second derivative method. According to the detected local peak locations, commonly used full-waveform features such as full width at half maximum (FWHM) and amplitude can then be obtained. In addition, the number of peaks, time difference between the first and last peaks, and the average amplitude are also considered as features of LiDAR waveforms with multiple returns. Based on the waveform geometry, dynamic time-warping (DTW) is applied to measure the waveform similarity. The sum of the absolute amplitude differences that remain after time-warping can be used as a similarity feature in a classification procedure. An airborne full-waveform LiDAR data set was used to test the performance of the developed feature extraction method for land-cover classification. Experimental results indicate that the developed spline curve- fitting algorithm and geometry analysis can extract helpful full-waveform LiDAR features to produce better land-cover classification than conventional LiDAR data and feature extraction methods. In particular, the multiple-return features and the dynamic time-warping index can improve the classification results significantly.

Accuracy Assessment of Lidar-Derived Digital Terrain Model (dtm) with Different Slope and Canopy Cover in Tropical Forest Region

NASA Astrophysics Data System (ADS)

Salleh, M. R. M.; Ismail, Z.; Rahman, M. Z. A.

2015-10-01

Airborne Light Detection and Ranging (LiDAR) technology has been widely used recent years especially in generating high accuracy of Digital Terrain Model (DTM). High density and good quality of airborne LiDAR data promises a high quality of DTM. This study focussing on the analysing the error associated with the density of vegetation cover (canopy cover) and terrain slope in a LiDAR derived-DTM value in a tropical forest environment in Bentong, State of Pahang, Malaysia. Airborne LiDAR data were collected can be consider as low density captured by Reigl system mounted on an aircraft. The ground filtering procedure use adaptive triangulation irregular network (ATIN) algorithm technique in producing ground points. Next, the ground control points (GCPs) used in generating the reference DTM and these DTM was used for slope classification and the point clouds belong to non-ground are then used in determining the relative percentage of canopy cover. The results show that terrain slope has high correlation for both study area (0.993 and 0.870) with the RMSE of the LiDAR-derived DTM. This is similar to canopy cover where high value of correlation (0.989 and 0.924) obtained. This indicates that the accuracy of airborne LiDAR-derived DTM is significantly affected by terrain slope and canopy caver of study area.

Nosql for Storage and Retrieval of Large LIDAR Data Collections

NASA Astrophysics Data System (ADS)

Boehm, J.; Liu, K.

2015-08-01

Developments in LiDAR technology over the past decades have made LiDAR to become a mature and widely accepted source of geospatial information. This in turn has led to an enormous growth in data volume. The central idea for a file-centric storage of LiDAR point clouds is the observation that large collections of LiDAR data are typically delivered as large collections of files, rather than single files of terabyte size. This split of the dataset, commonly referred to as tiling, was usually done to accommodate a specific processing pipeline. It makes therefore sense to preserve this split. A document oriented NoSQL database can easily emulate this data partitioning, by representing each tile (file) in a separate document. The document stores the metadata of the tile. The actual files are stored in a distributed file system emulated by the NoSQL database. We demonstrate the use of MongoDB a highly scalable document oriented NoSQL database for storing large LiDAR files. MongoDB like any NoSQL database allows for queries on the attributes of the document. As a specialty MongoDB also allows spatial queries. Hence we can perform spatial queries on the bounding boxes of the LiDAR tiles. Inserting and retrieving files on a cloud-based database is compared to native file system and cloud storage transfer speed.

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Villalonga, Alberto; Haber, Rodolfo E

2018-05-10

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the 'Internet of Things' (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds.

Shear viscosity for dense plasmas by equilibrium molecular dynamics in asymmetric Yukawa ionic mixtures.

PubMed

Haxhimali, Tomorr; Rudd, Robert E; Cabot, William H; Graziani, Frank R

2015-11-01

We present molecular dynamics (MD) calculations of shear viscosity for asymmetric mixed plasma for thermodynamic conditions relevant to astrophysical and inertial confinement fusion plasmas. Specifically, we consider mixtures of deuterium and argon at temperatures of 100-500 eV and a number density of 10^{25} ions/cc. The motion of 30,000-120,000 ions is simulated in which the ions interact via the Yukawa (screened Coulomb) potential. The electric field of the electrons is included in this effective interaction; the electrons are not simulated explicitly. Shear viscosity is calculated using the Green-Kubo approach with an integral of the shear stress autocorrelation function, a quantity calculated in the equilibrium MD simulations. We systematically study different mixtures through a series of simulations with increasing fraction of the minority high-Z element (Ar) in the D-Ar plasma mixture. In the more weakly coupled plasmas, at 500 eV and low Ar fractions, results from MD compare very well with Chapman-Enskog kinetic results. In the more strongly coupled plasmas, the kinetic theory does not agree well with the MD results. We develop a simple model that interpolates between classical kinetic theories at weak coupling and the Murillo Yukawa viscosity model at higher coupling. This hybrid kinetics-MD viscosity model agrees well with the MD results over the conditions simulated, ranging from moderately weakly coupled to moderately strongly coupled asymmetric plasma mixtures.

Study of shear viscosity for dense plasmas by equilibrium molecular dynamics in asymmetric Yukawa ionic mixtures

NASA Astrophysics Data System (ADS)

Haxhimali, Tomorr; Rudd, Robert; Cabot, William; Graziani, Frank

2015-11-01

We present molecular dynamics (MD) calculations of shear viscosity for asymmetric mixed plasma for thermodynamic conditions relevant to astrophysical and Inertial Confinement Fusion plasmas. Specifically, we consider mixtures of deuterium and argon at temperatures of 100-500 eV and a number density of 1025 ions/cc. The motion of 30000-120000 ions is simulated in which the ions interact via the Yukawa (screened Coulomb) potential. The electric field of the electrons is included in this effective interaction. Shear viscosity is calculated using the Green-Kubo approach with an integral of the shear stress autocorrelation function, a quantity calculated in the equilibrium MD simulations. We study different mixtures with increasing fraction of the minority high-Z element (Ar) in the D-Ar plasma mixture. In the more weakly coupled plasmas, at 500 eV and low Ar fractions, results from MD compare very well with Chapman-Enskog kinetic results. We introduce a model that interpolates between a screened-plasma kinetic theory at weak coupling and the Murillo Yukawa viscosity model at higher coupling. This hybrid kinetics-MD viscosity model agrees well with the MD results over the conditions simulated. This work was performed under the auspices of the US Dept. of Energy by Lawrence Livermore National Security, LLC under Contract DE-AC52-07NA27344.

Shear viscosity for dense plasmas by equilibrium molecular dynamics in asymmetric Yukawa ionic mixtures

NASA Astrophysics Data System (ADS)

Haxhimali, Tomorr; Rudd, Robert E.; Cabot, William H.; Graziani, Frank R.

2015-11-01

We present molecular dynamics (MD) calculations of shear viscosity for asymmetric mixed plasma for thermodynamic conditions relevant to astrophysical and inertial confinement fusion plasmas. Specifically, we consider mixtures of deuterium and argon at temperatures of 100-500 eV and a number density of 1025 ions/cc. The motion of 30 000-120 000 ions is simulated in which the ions interact via the Yukawa (screened Coulomb) potential. The electric field of the electrons is included in this effective interaction; the electrons are not simulated explicitly. Shear viscosity is calculated using the Green-Kubo approach with an integral of the shear stress autocorrelation function, a quantity calculated in the equilibrium MD simulations. We systematically study different mixtures through a series of simulations with increasing fraction of the minority high-Z element (Ar) in the D-Ar plasma mixture. In the more weakly coupled plasmas, at 500 eV and low Ar fractions, results from MD compare very well with Chapman-Enskog kinetic results. In the more strongly coupled plasmas, the kinetic theory does not agree well with the MD results. We develop a simple model that interpolates between classical kinetic theories at weak coupling and the Murillo Yukawa viscosity model at higher coupling. This hybrid kinetics-MD viscosity model agrees well with the MD results over the conditions simulated, ranging from moderately weakly coupled to moderately strongly coupled asymmetric plasma mixtures.

Occurrence of water-borne enteric viruses in two settlements based in Eastern Chad: analysis of hepatitis E virus, hepatitis A virus and human adenovirus in water sources.

PubMed

Guerrero-Latorre, Laura; Carratala, Anna; Rodriguez-Manzano, Jesus; Calgua, Byron; Hundesa, Ayalkibet; Girones, Rosina

2011-09-01

Hepatitis E virus (HEV) is a common cause of water-borne acute hepatitis in areas with poor sanitation. In 2004 an outbreak of HEV infection affected around 2,000 people in Eastern Chad (Dar Sila). This paper describes the decrease in the incidence of acute jaundice syndrome (AJS) from 2004 until 2009 when a mean incidence of 0.48 cases/1,000 people/year was recorded in the region. Outbreaks of AJS were identified in some of the camps in 2007 and 2008. Moreover, water samples from drinking water sources were screened for human adenoviruses considered as viral indicators and for hepatitis A virus and HEV. Screening of faecal samples from donkeys for HEV gave negative results. Some of the samples were also analysed for faecal coliforms showing values before disinfection treatment between 3 and >50 colony forming units per 100 mL. All water samples tested were negative for HEV and HAV; however, the presence of low levels of human adenoviruses in 4 out of 16 samples analysed indicates possible human faecal contamination of groundwater. Consequently, breakdowns in the treatment of drinking water and/or increased excretion of hepatitis viruses, which could be related to the arrival of a new population, could spread future outbreaks through drinking water.

Identification of a new fault and associated lineament features in Oregon's Summer Lake Valley using high-resolution LiDAR data

NASA Astrophysics Data System (ADS)

Bennett, L.; Madin, I.

2012-12-01

In 2012, the Oregon Department of Geology and Mineral Industries (DOGAMI) contracted WSI to co-acquire airborne Light Detecting and Ranging (LiDAR) and Thermal Infrared Imagery (TIR) data within the region surrounding Summer Lake, Oregon. The objective of this project was to detect surficial expressions of geothermal activity and associated geologic features. An analysis of the LiDAR data revealed one newly identified fault and several accompanying lineaments that strike northwest, similar to the trend of the Ana River, Brothers, and Eugene-Denio Fault Zones in Central Oregon. The age of the Ana River Fault Zone and Summer Lake bed is known to be within the Holocene epoch. Apparent scarp height observed from the LiDAR is up to 8 meters. While detailed analysis is ongoing, the data illustrated the effectiveness of using high resolution remote sensing data for surficial analysis of geologic displacement. This presentation will focus on direct visual detection of features in the Summer Lake, Oregon landscape using LiDAR data.

Real-time vehicle emissions monitoring using a compact LiDAR system and conventional instruments: first results of an experimental campaign in a suburban area in southern Italy

NASA Astrophysics Data System (ADS)

Parracino, Stefano; Richetta, Maria; Gelfusa, Michela; Malizia, Andrea; Bellecci, Carlo; De Leo, Leonardo; Perrimezzi, Carlo; Fin, Alessandro; Forin, Marco; Giappicucci, Francesca; Grion, Massimo; Marchese, Giuseppe; Gaudio, Pasquale

2016-10-01

Urban air pollution causes deleterious effects on human health and the environment. To meet stringent standards imposed by the European Commission, advanced measurement methods are required. Remote sensing techniques, such as light detection and ranging (LiDAR), can be a valuable option for evaluating particulate matter (PM), emitted by vehicles in urban traffic, with high sensitivity and in shorter time intervals. Since air quality problems persist not only in large urban areas, a measuring campaign was specifically performed in a suburban area of Crotone, Italy, using both a compact LiDAR system and conventional instruments for real-time vehicle emissions monitoring along a congested road. First results reported in this paper show a strong dependence between variations of LiDAR backscattering signals and traffic-related air pollution levels. Moreover, time-resolved LiDAR data averaged in limited regions, directly above conventional monitoring stations at the border of an intersection, were found to be linearly correlated to the PM concentration levels with a correlation coefficient between 0.75 and 0.84.

Optimization of non-linear gradient in hydrophobic interaction chromatography for the analytical characterization of antibody-drug conjugates.

PubMed

Bobály, Balázs; Randazzo, Giuseppe Marco; Rudaz, Serge; Guillarme, Davy; Fekete, Szabolcs

2017-01-20

The goal of this work was to evaluate the potential of non-linear gradients in hydrophobic interaction chromatography (HIC), to improve the separation between the different homologous species (drug-to-antibody, DAR) of commercial antibody-drug conjugates (ADC). The selectivities between Brentuximab Vedotin species were measured using three different gradient profiles, namely linear, power function based and logarithmic ones. The logarithmic gradient provides the most equidistant retention distribution for the DAR species and offers the best overall separation of cysteine linked ADC in HIC. Another important advantage of the logarithmic gradient, is its peak focusing effect for the DAR0 species, which is particularly useful to improve the quantitation limit of DAR0. Finally, the logarithmic behavior of DAR species of ADC in HIC was modelled using two different approaches, based on i) the linear solvent strength theory (LSS) and two scouting linear gradients and ii) a new derived equation and two logarithmic scouting gradients. In both cases, the retention predictions were excellent and systematically below 3% compared to the experimental values. Copyright © 2016 Elsevier B.V. All rights reserved.

Temporal variability and social heterogeneity in disease transmission: the case of SARS in Hong Kong.

PubMed

Cori, Anne; Boëlle, Pierre-Yves; Thomas, Guy; Leung, Gabriel M; Valleron, Alain-Jacques

2009-08-01

The extent to which self-adopted or intervention-related changes in behaviors affect the course of epidemics remains a key issue for outbreak control. This study attempted to quantify the effect of such changes on the risk of infection in different settings, i.e., the community and hospitals. The 2002-2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong, where 27% of cases were healthcare workers, was used as an example. A stochastic compartmental SEIR (susceptible-exposed-infectious-removed) model was used: the population was split into healthcare workers, hospitalized people and general population. Super spreading events (SSEs) were taken into account in the model. The temporal evolutions of the daily effective contact rates in the community and hospitals were modeled with smooth functions. Data augmentation techniques and Markov chain Monte Carlo (MCMC) methods were applied to estimate SARS epidemiological parameters. In particular, estimates of daily reproduction numbers were provided for each subpopulation. The average duration of the SARS infectious period was estimated to be 9.3 days (+/-0.3 days). The model was able to disentangle the impact of the two SSEs from background transmission rates. The effective contact rates, which were estimated on a daily basis, decreased with time, reaching zero inside hospitals. This observation suggests that public health measures and possible changes in individual behaviors effectively reduced transmission, especially in hospitals. The temporal patterns of reproduction numbers were similar for healthcare workers and the general population, indicating that on average, an infectious healthcare worker did not infect more people than any other infectious person. We provide a general method to estimate time dependence of parameters in structured epidemic models, which enables investigation of the impact of control measures and behavioral changes in different settings.

Automatic extraction of building boundaries using aerial LiDAR data

NASA Astrophysics Data System (ADS)

Wang, Ruisheng; Hu, Yong; Wu, Huayi; Wang, Jian

2016-01-01

Building extraction is one of the main research topics of the photogrammetry community. This paper presents automatic algorithms for building boundary extractions from aerial LiDAR data. First, segmenting height information generated from LiDAR data, the outer boundaries of aboveground objects are expressed as closed chains of oriented edge pixels. Then, building boundaries are distinguished from nonbuilding ones by evaluating their shapes. The candidate building boundaries are reconstructed as rectangles or regular polygons by applying new algorithms, following the hypothesis verification paradigm. These algorithms include constrained searching in Hough space, enhanced Hough transformation, and the sequential linking technique. The experimental results show that the proposed algorithms successfully extract building boundaries at rates of 97%, 85%, and 92% for three LiDAR datasets with varying scene complexities.

UV testing of INTELSAT-7, 7A, and 8 solar cells

NASA Technical Reports Server (NTRS)

Meulenberg, A.

1994-01-01

A 4000 hour experiment, conducted in late 1992 through mid 1993, confirmed earlier results on the ultraviolet damage effects in covered solar cells of various types being used, or proposed for use, in INTELSAT programs. Two different UV test systems were used to identify systematic errors and to study the effects of UV source-bulb age on degradation rate. After correction for contamination and UV source-bulb aging, the extrapolated degradation rates for irradiated and unirradiated INTELSAT-5, -6 single AR(SAR) coated cells and INTELSAT-7, -7A, -8 double layer AR(DAR) coated cells in both the 1993 tests confirm the following hypotheses resulting from the 1992 experiment. (a) Irradiated cells display significantly more UV degradation than do the unirradiated cells for tests exceeding 2000 hours. The new data indicates that degradation effects from electron irradiation are proportional to t(exp 2) (the square of the UV hours), at least for times less than or equal to 3000 hours. (b) This difference does not depend upon entire reflective coating, cell resistivity, or manufacturer within the sensitivity and reproducibility of the experiment. (c) There is a clear difference in degradation rate between single AR coated cells (TiO(x)) and double layer AR coated cells (SiO(x) and Al2O3?). At 100,000 hours (11.4 years) the DAR coated cells display more degradation than do the SAR coated cells, even though at 1,000 hours the DAR cells display less degradation. (d) UV degradation rates, to modern covered silicon solar cells, at the beginning of bulb life drop from approximately 2 times the average rate to near zero after 2000 hours (average end-of-life for the xenon short-arc lamps used in the tests). The effects of 1 MeV electron irradiation (10(exp 15) e(-)/sq cm) prior to UV exposure are clearly indicated in the plot of percent change in cell open circuit voltage (Voc) versus percent change in short circuit current (Isc) during the UV test and post-test cleanup of the cells. Clearly, extended UV testing produces a permanent photo-induced redegradation of previously irradiated cells. However, this photo-induced redegradation may be caused by the long-wavelength light, not the UV light.

Airborne laser scanning for forest health status assessment and radiative transfer modelling

NASA Astrophysics Data System (ADS)

Novotny, Jan; Zemek, Frantisek; Pikl, Miroslav; Janoutova, Ruzena

2013-04-01

Structural parameters of forest stands/ecosystems are an important complementary source of information to spectral signatures obtained from airborne imaging spectroscopy when quantitative assessment of forest stands are in the focus, such as estimation of forest biomass, biochemical properties (e.g. chlorophyll /water content), etc. The parameterization of radiative transfer (RT) models used in latter case requires three-dimensional spatial distribution of green foliage and woody biomass. Airborne LiDAR data acquired over forest sites bears these kinds of 3D information. The main objective of the study was to compare the results from several approaches to interpolation of digital elevation model (DEM) and digital surface model (DSM). We worked with airborne LiDAR data with different density (TopEye Mk II 1,064nm instrument, 1-5 points/m2) acquired over the Norway spruce forests situated in the Beskydy Mountains, the Czech Republic. Three different interpolation algorithms with increasing complexity were tested: i/Nearest neighbour approach implemented in the BCAL software package (Idaho Univ.); ii/Averaging and linear interpolation techniques used in the OPALS software (Vienna Univ. of Technology); iii/Active contour technique implemented in the TreeVis software (Univ. of Freiburg). We defined two spatial resolutions for the resulting coupled raster DEMs and DSMs outputs: 0.4 m and 1 m, calculated by each algorithm. The grids correspond to the same spatial resolutions of hyperspectral imagery data for which the DEMs were used in a/geometrical correction and b/building a complex tree models for radiative transfer modelling. We applied two types of analyses when comparing between results from the different interpolations/raster resolution: 1/calculated DEM or DSM between themselves; 2/comparison with field data: DEM with measurements from referential GPS, DSM - field tree alometric measurements, where tree height was calculated as DSM-DEM. The results of the analyses show that: 1/averaging techniques tend to underestimate the tree height and the generated surface does not follow the first LiDAR echoes both for 1 m and 0.4 m pixel size; 2/we did not find any significant difference between tree heights calculated by nearest neighbour algorithm and the active contour technique for 1 m pixel output but the difference increased with finer resolution (0.4 m); 3/the accuracy of the DEMs calculated by tested algorithms is similar.

LiDAR monitoring of retrogressive processes on the steep rockslope of a large landslide in the Japanese Alps

NASA Astrophysics Data System (ADS)

Nishii, R.; Imaizumi, F.; Murakami, W.; Daimaru, H.; Miyamae, T.; Ogawa, Y.

2012-04-01

Akakuzure landslide in Japanese Alps is located in a steep mountain slope experienced deep-seated gravitational slope deformation. The landslide is 700 m high (1200-1900 m a.s.l.), 700 m wide and 400000 m2 in area with post-collapsed sediment ca 27 million m3 in volume. The steep rockslope (>40°) in the landslide shows anaclinal structure consisting of sandstone interbedding with shale. Large volume of sediment produced from the landslide has actively formed an alluvial fan on the outlet of the landslide. The volume and processes of the sediment production in the upper part (ca.40000 m^2) of the landslide were evaluated by geodetic surveys using techniques of airborne and ground-based LiDAR (Light Detection and Ranging). The airborne and ground-based LiDAR surveys were performed twice (2003 and 2007) and 3 times (2010-2011), respectively. Ground surface temperatures were monitored at 3 locations within the landslide from 2010 to 2011. Precipitation and air temperature have been also observed on a meteorological station near the study site. The average erosion depths in the observed rockslope reached 0.89 m (0.22 m/yr) during the first 4 years (2003-2007) and 0.55 m (0.18 m/yr) during the later 3 years (2007-2010). The erosion mainly occurred within the landslide rather than on the edge of the landslide (i.e. no significant retreat of the main scarp). Such large sediment production can be divided into three processes based on the depth of detachment. Deep detachment (>5 m in depth), significantly contributing to the retreat of the rockslope, happened to large blocks had located just above knick lines. During the observation period, at least five large blocks fell down, which appears to originate from sliding along the detachment zone steeper than 30°. Second, anaclinal bedding-parallel blocks (1-2 m in depth) fell down, which mainly occurred around sandstone layers. Finally, thin detachment (<1 m in depth) widely occurred on the rockslope. On one part of shale layers, the erosion depth reached 0.35 m from 2010 to 2011. In Akakuzure landside, numerous fractures of the bedrock, probably produced by gravitational deformation, play an important role to promote the rapid erosion, in addition to external triggers such as heavy rainfalls and frost actions.

Prevalence of Cryptosporidium parvum/hominis, Entamoeba histolytica and Giardia lamblia among Young Children with and without Diarrhea in Dar es Salaam, Tanzania.

PubMed

Tellevik, Marit G; Moyo, Sabrina J; Blomberg, Bjørn; Hjøllo, Torunn; Maselle, Samuel Y; Langeland, Nina; Hanevik, Kurt

2015-01-01

Although enteroparasites are common causes of diarrheal illness, few studies have been performed among children in Tanzania. This study aimed to investigate the prevalence of Cryptosporidium parvum/hominis, Entamoeba histolytica and Giardia lamblia among young children in Dar es Salaam, Tanzania, and identify risk factors for infection. We performed an unmatched case-control study among children < 2 years of age in Dar es Salaam, recruited from August 2010 to July 2011. Detection and identification of protozoans were done by PCR techniques on DNA from stool specimens from 701 cases of children admitted due to diarrhea at the three study hospitals, and 558 controls of children with no history of diarrhea during the last month prior to enrollment. The prevalence of C. parvum/hominis was 10.4% (84.7% C. hominis), and that of G. lamblia 4.6%. E. histolytica was not detected. The prevalence of Cryptosporidium was significantly higher in cases (16.3%) than in controls (3.1%; P < 0.001; OR = 6.2; 95% CI: 3.7-10.4). G. lamblia was significantly more prevalent in controls (6.1%) than in cases (3.4%; P = 0.027; OR = 1.8; 95% CI: 1.1-3.1). Cryptosporidium infection was found more often in HIV-positive (24.2%) than in HIV-negative children (3.9%; P < 0.001; OR = 7.9; 95% CI: 3.1-20.5), and was also associated with rainfall (P < 0.001; OR = 2.41; 95% CI: 1.5-3.8). Among cases, stunted children had significantly higher risk of being infected with Cryptosporidium (P = 0.011; OR = 2.12; 95% CI: 1.2-3.8). G. lamblia infection was more prevalent in the cool season (P = 0.004; OR = 2.2; 95% CI: 1.3-3.8), and more frequent among cases aged > 12 months (P = 0.003; OR = 3.5; 95% CI: 1.5-7.8). Among children aged 7-12 months, those who were breastfed had lower prevalence of G. lamblia infection than those who had been weaned (P = 0.012). Cryptosporidium infection is common among young Tanzanian children with diarrhea, particularly those living with HIV, and infection is more frequent during the rainy season. G. lamblia is frequently implicated in asymptomatic infections, but rarely causes overt diarrheal illness, and its prevalence increases with age.

Designated Airworthiness Representatives

DOT National Transportation Integrated Search

1985-10-01

This advisory circular (AC) contains information and guidance concerning the : selection and appointment of Designated Airworthiness Representatives (DAR's) and identifies the specific functions which may be delegated to DAR's as authorized by the Fe...

Preliminary Results of Double-Sample Forest Inventory of Pine and Mixed Stands with High- and Low-Density LiDAR

Treesearch

Robert C. Parker; Patrick A. Glass

2004-01-01

LiDAR data (0.5 and 1 m postings) were used in a double-sample forest inventory on the Lee Experimental Forest, Louisiana. Phase 2 plots were established with DGPS. Tree d.b.h. (> 4.5 inches) and two sample heights were measured on every 10 th plot of the Phase 1 sample. Volume was computed for natural and planted pine and mixed hardwood species. LiDAR trees were...

Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast‑growing Eucalyptus forest plantation using airborne LiDAR data

Treesearch

Carlos Alberto Silva; Andrew Thomas Hudak; Carine Klauberg; Lee Alexandre Vierling; Carlos Gonzalez‑Benecke; Samuel de Padua Chaves Carvalho; Luiz Carlos Estraviz Rodriguez; Adrian Cardil

2017-01-01

LiDAR measurements can be used to predict and map AGC across variable-age Eucalyptus plantations with adequate levels of precision and accuracy using 5 pulses m− 2 and a grid cell size of 5 m. The promising results for AGC modeling in this study will allow for greater confidence in comparing AGC estimates with varying LiDAR sampling densities for Eucalyptus plantations...

Synergy of VSWIR and LiDAR for Ecosystem Structure, Biomass, and Canopy Diversity

NASA Technical Reports Server (NTRS)

Cook, Bruce D.; Asner, Gregory P.

2010-01-01

This slide presentation reviews the use of Visible ShortWave InfraRed (VSWIR) Imaging Spectrometer and LiDAR to study ecosystem structure, biomass and canopy diversity. It is shown that the biophysical data from LiDAR and biochemical information from hyperspectral remote sensing provides complementary data for: (1) describing spatial patterns of vegetation and biodiversity, (2) characterizing relationships between ecosystem form and function, and (3) detecting natural and human induced change that affects the biogeochemical cycles.

Lidar - ND Halo Scanning Doppler, Boardman - Reviewed Data

DOE Data Explorer

Otarola, Sebastian

2017-10-23

The University of Notre Dame (ND) scanning LiDAR dataset used for the WFIP2 Campaign is provided. The LiDAR is a Halo Photonics Stream Line Scanning Doppler LiDAR. **It is highly recommended to discuss any planned use of these data with University of Notre Dame scientists**. For more information refer to Section 4.c) in the updated version of the "WFIP2 Project (lidar.z07)" Readme file, where the lidar.z07.b0 dataset is fully explained.

Geophysical Assessment of Groundwater Potential: A Case Study from Mian Channu Area, Pakistan.

PubMed

Hasan, Muhammad; Shang, Yanjun; Akhter, Gulraiz; Jin, Weijun

2017-11-17

An integrated study using geophysical method in combination with pumping tests and geochemical method was carried out to delineate groundwater potential zones in Mian Channu area of Pakistan. Vertical electrical soundings (VES) using Schlumberger configuration with maximum current electrode spacing (AB/2 = 200 m) were conducted at 50 stations and 10 pumping tests at borehole sites were performed in close proximity to 10 of the VES stations. The aim of this study is to establish a correlation between the hydraulic parameters obtained from geophysical method and pumping tests so that the aquifer potential can be estimated from the geoelectrical surface measurements where no pumping tests exist. The aquifer parameters, namely, transmissivity and hydraulic conductivity were estimated from Dar Zarrouyk parameters by interpreting the layer parameters such as true resistivities and thicknesses. Geoelectrical succession of five-layer strata (i.e., topsoil, clay, clay sand, sand, and sand gravel) with sand as a dominant lithology was found in the study area. Physicochemical parameters interpreted by World Health Organization and Food and Agriculture Organization were well correlated with the aquifer parameters obtained by geoelectrical method and pumping tests. The aquifer potential zones identified by modeled resistivity, Dar Zarrouk parameters, pumped aquifer parameters, and physicochemical parameters reveal that sand and gravel sand with high values of transmissivity and hydraulic conductivity are highly promising water bearing layers in northwest of the study area. Strong correlation between estimated and pumped aquifer parameters suggest that, in case of sparse well data, geophysical technique is useful to estimate the hydraulic potential of the aquifer with varying lithology. © 2017, National Ground Water Association.

Multi-Resolution Analysis of LiDAR data for Characterizing a Stabilized Aeolian Landscape in South Texas

NASA Astrophysics Data System (ADS)

Barrineau, C. P.; Dobreva, I. D.; Bishop, M. P.; Houser, C.

2014-12-01

Aeolian systems are ideal natural laboratories for examining self-organization in patterned landscapes, as certain wind regimes generate certain morphologies. Topographic information and scale dependent analysis offer the opportunity to study such systems and characterize process-form relationships. A statistically based methodology for differentiating aeolian features would enable the quantitative association of certain surface characteristics with certain morphodynamic regimes. We conducted a multi-resolution analysis of LiDAR elevation data to assess scale-dependent morphometric variations in an aeolian landscape in South Texas. For each pixel, mean elevation values are calculated along concentric circles moving outward at 100-meter intervals (i.e. 500 m, 600 m, 700 m from pixel). The calculated average elevation values plotted against distance from the pixel of interest as curves are used to differentiate multi-scalar variations in elevation across the landscape. In this case, it is hypothesized these curves may be used to quantitatively differentiate certain morphometries from others like a spectral signature may be used to classify paved surfaces from natural vegetation, for example. After generating multi-resolution curves for all the pixels in a selected area of interest (AOI), a Principal Components Analysis is used to highlight commonalities and singularities between generated curves from pixels across the AOI. Our findings suggest that the resulting components could be used for identification of discrete aeolian features like open sands, trailing ridges and active dune crests, and, in particular, zones of deflation. This new approach to landscape characterization not only works to mitigate bias introduced when researchers must select training pixels for morphometric investigations, but can also reveal patterning in aeolian landscapes that would not be as obvious without quantitative characterization.

Maternal Dietary L-Arginine and Adverse Birth Outcomes in Dar es Salaam, Tanzania.

PubMed

Darling, Anne Marie; McDonald, Chloe R; Urassa, Willy S; Kain, Kevin C; Mwiru, Ramadhani S; Fawzi, Wafaie W

2017-09-01

The amino acid arginine is a physiological precursor to nitric oxide, which is a key mediator of embryonic survival, fetal growth, and pregnancy maintenance. We evaluated the association between consumption of the amino acid arginine and the rate of adverse birth outcomes using data from a double-blind, randomized, placebo-controlled micronutrient supplementation trial among pregnant women in Dar es Salaam, Tanzania (2001-2004). Dietary intakes of arginine were assessed using repeated 24-hour recalls that were administered throughout pregnancy. Participants (n = 7,591) were monitored by research midwives throughout follow-up to assess pregnancy outcomes. Cubic-restricted splines and multivariable log-Poisson regression with empirical standard errors were used to estimate the continuous and categorical associations between arginine intake and adverse birth outcomes. Compared with women within the lowest quintile of arginine intake, those within the highest quintile had 0.79 times the risk of preterm birth before 37 weeks (95% confidence interval: 0.63, 1.00; P = 0.03). The continuous associations of arginine intake with preterm birth before 37 weeks and with preterm birth before 34 weeks were characterized by an initial rapid decrease in risk with increasing intake (P for nonlinearity < 0.01). Arginine intake was not associated with fetal loss or giving birth to infants who were born small for their gestational ages. This data suggest that the association between dietary arginine intake and preterm birth warrants further investigation. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Extended-Spectrum beta (β)-Lactamases and Antibiogram in Enterobacteriaceae from Clinical and Drinking Water Sources from Bahir Dar City, Ethiopia.

PubMed

Abera, Bayeh; Kibret, Mulugeta; Mulu, Wondemagegn

2016-01-01

The spread of Extended-Spectrum beta (β)-Lactamases (ESBL)-producing Enterobacteriaceae has become a serious global problem. ESBL-producing Enterobacteriaceae vary based on differences in antibiotic use, nature of patients and hospital settings. This study was aimed at determining ESBL and antibiogram in Enterobacteriaceae isolates from clinical and drinking water sources in Bahir Dar City, Northwest Ethiopia. Enterobacteriaceae species were isolated from clinical materials and tap water using standard culturing procedures from September 2013 to March 2015. ESBL-producing-Enterobacteriaceae were detected using double-disk method by E-test Cefotaxim/cefotaxim+ clavulanic acid and Ceftazidime/ceftazidime+ clavulanic acid (BioMerieux SA, France) on Mueller Hinton agar (Oxoid, UK). Overall, 274 Enterobacteriaceae were isolated. Of these, 210 (44%) were from patients and 64 (17.1%) were from drinking water. The median age of the patients was 28 years. Urinary tract infection and blood stream infection accounted for 60% and 21.9% of Enterobacteriaceae isolates, respectively. Klebsiella pneumoniae was isolated from 9 (75%) of neonatal sepsis. The overall prevalence of ESBL-producing Enterobacteriaceae in clinical and drinking water samples were 57.6% and 9.4%, respectively. The predominant ESBL-producers were K. pneumoniae 34 (69.4%) and Escherichia coli 71 (58.2%). Statistically significant associations were noted between ESBL-producing and non- producing Enterobacteriaceae with regard to age of patients, infected body sites and patient settings (P = 0.001). ESBL-producing Enterobacteriaceae showed higher levels of resistance against chloramphenicol, ciprofloxacin and cotrimoxazole than non-ESBL producers (P = 0.001). ESBL-producing Enterobacteriaceae coupled with high levels of other antimicrobials become a major concern for treatment of patients with invasive infections such as blood stream infections, neonatal sepsis and urinary tract infections. ESBL-producing Enterobacteriaceae were also detected in drinking water sources.

3-D visualisation of palaeoseismic trench stratigraphy and trench logging using terrestrial remote sensing and GPR - combining techniques towards an objective multiparametric interpretation

NASA Astrophysics Data System (ADS)

Schneiderwind, S.; Mason, J.; Wiatr, T.; Papanikolaou, I.; Reicherter, K.

2015-09-01

Two normal faults on the Island of Crete and mainland Greece were studied to create and test an innovative workflow to make palaeoseismic trench logging more objective, and visualise the sedimentary architecture within the trench wall in 3-D. This is achieved by combining classical palaeoseismic trenching techniques with multispectral approaches. A conventional trench log was firstly compared to results of iso cluster analysis of a true colour photomosaic representing the spectrum of visible light. Passive data collection disadvantages (e.g. illumination) were addressed by complementing the dataset with active near-infrared backscatter signal image from t-LiDAR measurements. The multispectral analysis shows that distinct layers can be identified and it compares well with the conventional trench log. According to this, a distinction of adjacent stratigraphic units was enabled by their particular multispectral composition signature. Based on the trench log, a 3-D-interpretation of GPR data collected on the vertical trench wall was then possible. This is highly beneficial for measuring representative layer thicknesses, displacements and geometries at depth within the trench wall. Thus, misinterpretation due to cutting effects is minimised. Sedimentary feature geometries related to earthquake magnitude can be used to improve the accuracy of seismic hazard assessments. Therefore, this manuscript combines multiparametric approaches and shows: (i) how a 3-D visualisation of palaeoseismic trench stratigraphy and logging can be accomplished by combining t-LiDAR and GRP techniques, and (ii) how a multispectral digital analysis can offer additional advantages and a higher objectivity in the interpretation of palaeoseismic and stratigraphic information. The multispectral datasets are stored allowing unbiased input for future (re-)investigations.

Detection of CTX-M-15 beta-lactamases in Enterobacteriaceae causing hospital- and community-acquired urinary tract infections as early as 2004, in Dar es Salaam, Tanzania.

PubMed

Manyahi, Joel; Moyo, Sabrina J; Tellevik, Marit Gjerde; Ndugulile, Faustine; Urassa, Willy; Blomberg, Bjørn; Langeland, Nina

2017-04-17

The spread of Extended Spectrum β-lactamases (ESBLs) among Enterobacteriaceae and other Gram-Negative pathogens in the community and hospitals represents a major challenge to combat infections. We conducted a study to assess the prevalence and genetic makeup of ESBL-type resistance in bacterial isolates causing community- and hospital-acquired urinary tract infections. A total of 172 isolates of Enterobacteriaceae were collected in Dar es Salaam, Tanzania, from patients who met criteria of community and hospital-acquired urinary tract infections. We used E-test ESBL strips to test for ESBL-phenotype and PCR and sequencing for detection of ESBL genes. Overall 23.8% (41/172) of all isolates were ESBL-producers. ESBL-producers were more frequently isolated from hospital-acquired infections (32%, 27/84 than from community-acquired infections (16%, 14/88, p < 0.05). ESBL-producers showed high rate of resistance to ciprofloxacin (85.5%), doxycycline (90.2%), gentamicin (80.5%), nalidixic acid (84.5%), and trimethoprim-sulfamethoxazole (85.4%). Furthermore, 95% of ESBL-producers were multi-drug resistant compared to 69% of non-ESBL-producers (p < 0.05). The distribution of ESBL genes were as follows: 29/32 (90.6%) bla CTX-M-15 , two bla SHV-12 , and one had both bla CTX-M-15 and bla SHV-12 . Of 29 isolates carrying bla CTX-M-15 , 69% (20/29) and 31% (9/29) were hospital and community, respectively. Bla SHV-12 genotypes were only detected in hospital-acquired infections. bla CTX-M-15 is a predominant gene conferring ESBL-production in Enterobacteriaceae causing both hospital- and community-acquired infections in Tanzania.

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.

Effects of LiDAR point density and landscape context on the retrieval of urban forest biomass

NASA Astrophysics Data System (ADS)

Singh, K. K.; Chen, G.; McCarter, J. B.; Meentemeyer, R. K.

2014-12-01

Light Detection and Ranging (LiDAR), as an alternative to conventional optical remote sensing, is being increasingly used to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and better data accuracies, which however pose challenges to the procurement and processing of LiDAR data for large-area assessments. Reducing point density cuts data acquisition costs and overcome computational challenges for broad-scale forest management. However, how does that impact the accuracy of biomass estimation in an urban environment containing a great level of anthropogenic disturbances? The main goal of this study is to evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing regions of Charlotte, North Carolina, USA. We used multiple linear regression to establish the statistical relationship between field-measured biomass and predictor variables (PVs) derived from LiDAR point clouds with varying densities. We compared the estimation accuracies between the general Urban Forest models (no discrimination of forest type) and the Forest Type models (evergreen, deciduous, and mixed), which was followed by quantifying the degree to which landscape context influenced biomass estimation. The explained biomass variance of Urban Forest models, adjusted R2, was fairly consistent across the reduced point densities with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models using two representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, signifying the distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest biomass assessment without compromising the accuracy of estimation, which may further be improved using development density.

LiDAR as an Exploration Tool

DOE Data Explorer

Boschmann, D.; Diles, J.; Clarno, J.; Meigs, A.; Walsh, P.

2011-01-01

Using LiDAR to identify structural and volcanic evolution of a Miocene-Pleistocene age bimodal volcanic complex and implications for geothermal potential. The file includes an updated geologic map, methods, and preliminary results.

Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

PubMed Central

2011-01-01

Background The spread of infectious diseases crucially depends on the pattern of contacts between individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. However, there are few empirical studies available that provide estimates of the number and duration of contacts between social groups. Moreover, their space and time resolutions are limited, so that data are not explicit at the person-to-person level, and the dynamic nature of the contacts is disregarded. In this study, we aimed to assess the role of data-driven dynamic contact patterns between individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population. Methods We considered high-resolution data about face-to-face interactions between the attendees at a conference, obtained from the deployment of an infrastructure based on radiofrequency identification (RFID) devices that assessed mutual face-to-face proximity. The spread of epidemics along these interactions was simulated using an SEIR (Susceptible, Exposed, Infectious, Recovered) model, using both the dynamic network of contacts defined by the collected data, and two aggregated versions of such networks, to assess the role of the data temporal aspects. Results We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation that retains only the topology of the contact network fails to reproduce the size of the epidemic. Conclusions These results have important implications for understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics. Please see related article BMC Medicine, 2011, 9:88 PMID:21771290

Early rigorous control interventions can largely reduce dengue outbreak magnitude: experience from Chaozhou, China.

PubMed

Liu, Tao; Zhu, Guanghu; He, Jianfeng; Song, Tie; Zhang, Meng; Lin, Hualiang; Xiao, Jianpeng; Zeng, Weilin; Li, Xing; Li, Zhihao; Xie, Runsheng; Zhong, Haojie; Wu, Xiaocheng; Hu, Wenbiao; Zhang, Yonghui; Ma, Wenjun

2017-08-02

Dengue fever is a severe public heath challenge in south China. A dengue outbreak was reported in Chaozhou city, China in 2015. Intensified interventions were implemented by the government to control the epidemic. However, it is still unknown the degree to which intensified control measures reduced the size of the epidemics, and when should such measures be initiated to reduce the risk of large dengue outbreaks developing? We selected Xiangqiao district as study setting because the majority of the indigenous cases (90.6%) in Chaozhou city were from this district. The numbers of daily indigenous dengue cases in 2015 were collected through the national infectious diseases and vectors surveillance system, and daily Breteau Index (BI) data were reported by local public health department. We used a compartmental dynamic SEIR (Susceptible, Exposed, Infected and Removed) model to assess the effectiveness of control interventions, and evaluate the control effect of intervention timing on dengue epidemic. A total of 1250 indigenous dengue cases was reported from Xiangqiao district. The results of SEIR modeling using BI as an indicator of actual control interventions showed a total of 1255 dengue cases, which is close to the reported number (n = 1250). The size and duration of the outbreak were highly sensitive to the intensity and timing of interventions. The more rigorous and earlier the control interventions implemented, the more effective it yielded. Even if the interventions were initiated several weeks after the onset of the dengue outbreak, the interventions were shown to greatly impact the prevalence and duration of dengue outbreak. This study suggests that early implementation of rigorous dengue interventions can effectively reduce the epidemic size and shorten the epidemic duration.

Efficient Vaccine Distribution Based on a Hybrid Compartmental Model.

PubMed

Yu, Zhiwen; Liu, Jiming; Wang, Xiaowei; Zhu, Xianjun; Wang, Daxing; Han, Guoqiang

2016-01-01

To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible-exposed-infectious šC recovered) model, named the hybrid SEIR-V model (HSEIR-V), which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk) for controlling the spread of viral infections. Based on data from the 2009-2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics.

Efficient Vaccine Distribution Based on a Hybrid Compartmental Model

PubMed Central

Yu, Zhiwen; Liu, Jiming; Wang, Xiaowei; Zhu, Xianjun; Wang, Daxing; Han, Guoqiang

2016-01-01

To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible—exposed—infectious šC recovered) model, named the hybrid SEIR-V model (HSEIR-V), which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk) for controlling the spread of viral infections. Based on data from the 2009–2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics. PMID:27233015

LiDAR error estimation with WAsP engineering

NASA Astrophysics Data System (ADS)

Bingöl, F.; Mann, J.; Foussekis, D.

2008-05-01

The LiDAR measurements, vertical wind profile in any height between 10 to 150m, are based on assumption that the measured wind is a product of a homogenous wind. In reality there are many factors affecting the wind on each measurement point which the terrain plays the main role. To model LiDAR measurements and predict possible error in different wind directions for a certain terrain we have analyzed two experiment data sets from Greece. In both sites LiDAR and met, mast data have been collected and the same conditions are simulated with RisØ/DTU software, WAsP Engineering 2.0. Finally measurement data is compared with the model results. The model results are acceptable and very close for one site while the more complex one is returning higher errors at higher positions and in some wind directions.

Development and mapping of DArT markers within the Festuca - Lolium complex

PubMed Central

Kopecký, David; Bartoš, Jan; Lukaszewski, Adam J; Baird, James H; Černoch, Vladimír; Kölliker, Roland; Rognli, Odd Arne; Blois, Helene; Caig, Vanessa; Lübberstedt, Thomas; Studer, Bruno; Shaw, Paul; Doležel, Jaroslav; Kilian, Andrzej

2009-01-01

Background Grasses are among the most important and widely cultivated plants on Earth. They provide high quality fodder for livestock, are used for turf and amenity purposes, and play a fundamental role in environment protection. Among cultivated grasses, species within the Festuca-Lolium complex predominate, especially in temperate regions. To facilitate high-throughput genome profiling and genetic mapping within the complex, we have developed a Diversity Arrays Technology (DArT) array for five grass species: F. pratensis, F. arundinacea, F. glaucescens, L. perenne and L. multiflorum. Results The DArTFest array contains 7680 probes derived from methyl-filtered genomic representations. In a first marker discovery experiment performed on 40 genotypes from each species (with the exception of F. glaucescens for which only 7 genotypes were used), we identified 3884 polymorphic markers. The number of DArT markers identified in every single genotype varied from 821 to 1852. To test the usefulness of DArTFest array for physical mapping, DArT markers were assigned to each of the seven chromosomes of F. pratensis using single chromosome substitution lines while recombinants of F. pratensis chromosome 3 were used to allocate the markers to seven chromosome bins. Conclusion The resources developed in this project will facilitate the development of genetic maps in Festuca and Lolium, the analysis on genetic diversity, and the monitoring of the genomic constitution of the Festuca × Lolium hybrids. They will also enable marker-assisted selection for multiple traits or for specific genome regions. PMID:19832973

The use of LiDAR-derived high-resolution DSM and intensity data to support modelling of urban flooding

NASA Astrophysics Data System (ADS)

Aktaruzzaman, Md.; Schmitt, Theo G.

2011-11-01

This paper addresses the issue of a detailed representation of an urban catchment in terms of hydraulic and hydrologic attributes. Modelling of urban flooding requires a detailed knowledge of urban surface characteristics. The advancement in spatial data acquisition technology such as airborne LiDAR (Light Detection and Ranging) has greatly facilitated the collection of high-resolution topographic information. While the use of the LiDAR-derived Digital Surface Model (DSM) has gained popularity over the last few years as input data for a flood simulation model, the use of LiDAR intensity data has remained largely unexplored in this regard. LiDAR intensity data are acquired along with elevation data during the data collection mission by an aircraft. The practice of using of just aerial images with RGB (Red, Green and Blue) wavebands is often incapable of identifying types of surface under the shadow. On the other hand, LiDAR intensity data can provide surface information independent of sunlight conditions. The focus of this study is the use of intensity data in combination with aerial images to accurately map pervious and impervious urban areas. This study presents an Object-Based Image Analysis (OBIA) framework for detecting urban land cover types, mainly pervious and impervious surfaces in order to improve the rainfall-runoff modelling. Finally, this study shows the application of highresolution DSM and land cover maps to flood simulation software in order to visualize the depth and extent of urban flooding phenomena.

Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation.

PubMed

Silva, Carlos Alberto; Klauberg, Carine; Hudak, Andrew T; Vierling, Lee A; Liesenberg, Veraldo; Bernett, Luiz G; Scheraiber, Clewerson F; Schoeninger, Emerson R

2018-01-01

Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM) and tree density (TD) of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR) data and the non- k-nearest neighbor (k-NN) imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more effective for retrieving height than tree density. The model coefficients of determination (adj.R2) and a root mean squared difference (RMSD) for HD, HM and TD were 0.90, 0.94, 0.38m and 6.99, 5.70, 12.92%, respectively. Our results show that LiDAR and k-NN imputation can be used to predict stand heights with high accuracy in Pinus taeda. However, furthers studies need to be realized to improve the accuracy prediction of TD and to evaluate and compare the cost of acquisition and processing of LiDAR data against the conventional inventory procedures.

Localized Segment Based Processing for Automatic Building Extraction from LiDAR Data

NASA Astrophysics Data System (ADS)

Parida, G.; Rajan, K. S.

2017-05-01

The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

Registration of Panoramic/Fish-Eye Image Sequence and LiDAR Points Using Skyline Features

PubMed Central

Zhu, Ningning; Jia, Yonghong; Ji, Shunping

2018-01-01

We propose utilizing a rigorous registration model and a skyline-based method for automatic registration of LiDAR points and a sequence of panoramic/fish-eye images in a mobile mapping system (MMS). This method can automatically optimize original registration parameters and avoid the use of manual interventions in control point-based registration methods. First, the rigorous registration model between the LiDAR points and the panoramic/fish-eye image was built. Second, skyline pixels from panoramic/fish-eye images and skyline points from the MMS’s LiDAR points were extracted, relying on the difference in the pixel values and the registration model, respectively. Third, a brute force optimization method was used to search for optimal matching parameters between skyline pixels and skyline points. In the experiments, the original registration method and the control point registration method were used to compare the accuracy of our method with a sequence of panoramic/fish-eye images. The result showed: (1) the panoramic/fish-eye image registration model is effective and can achieve high-precision registration of the image and the MMS’s LiDAR points; (2) the skyline-based registration method can automatically optimize the initial attitude parameters, realizing a high-precision registration of a panoramic/fish-eye image and the MMS’s LiDAR points; and (3) the attitude correction values of the sequences of panoramic/fish-eye images are different, and the values must be solved one by one. PMID:29883431

Mapping Arctic plant functional type distributions in the Barrow Environmental Observatory using WorldView-2 and LiDAR datasets

DOE PAGES

Langford, Zachary; Kumar, Jitendra; Hoffman, Forrest; ...

2016-09-06

Multi-scale modeling of Arctic tundra vegetation requires characterization of the heterogeneous tundra landscape, which includes representation of distinct plant functional types (PFTs). We combined high-resolution multi-spectral remote sensing imagery from the WorldView-2 satellite with light detecting and ranging (LiDAR)-derived digital elevation models (DEM) to characterize the tundra landscape in and around the Barrow Environmental Observatory (BEO), a 3021-hectare research reserve located at the northern edge of the Alaskan Arctic Coastal Plain. Vegetation surveys were conducted during the growing season (June August) of 2012 from 48 1 m 1 m plots in the study region for estimating the percent cover ofmore » PFTs (i.e., sedges, grasses, forbs, shrubs, lichens and mosses). Statistical relationships were developed between spectral and topographic remote sensing characteristics and PFT fractions at the vegetation plots from field surveys. These derived relationships were employed to statistically upscale PFT fractions for our study region of 586 hectares at 0.25-m resolution around the sampling areas within the BEO, which was bounded by the LiDAR footprint. We employed an unsupervised clustering for stratification of this polygonal tundra landscape and used the clusters for segregating the field data for our upscaling algorithm over our study region, which was an inverse distance weighted (IDW) interpolation. We describe two versions of PFT distribution maps upscaled by IDW from WorldView-2 imagery and LiDAR: (1) a version computed from a single image in the middle of the growing season; and (2) a version computed from multiple images through the growing season. This approach allowed us to quantify the value of phenology for improving PFT distribution estimates. We also evaluated the representativeness of the field surveys by measuring the Euclidean distance between every pixel. This guided the ground-truthing campaign in late July of 2014 for addressing uncertainty based on representativeness analysis by selecting 24 1 m 1 m plots that were well and poorly represented. Ground-truthing indicated that including phenology had a better accuracy (R 2=0.75, RMSE=9.94) than the single image upscaling (R 2=0.63 , RMSE=12.05) predicted from IDW. We also updated our upscaling approach to include the 24 ground-truthing plots, and a second ground-truthing campaign in late August of 2014 indicated a better accuracy for the phenology model (R 2=0.61 , RMSE=13.78 ) than only using the original 48 plots for the phenology model (R 2=0.23 , RMSE=17.49). After all, we believe that the cluster-based IDW upscaling approach and the representativeness analysis offer new insights for upscaling high-resolution data in fragmented landscapes. This analysis and approach provides PFT maps needed to inform land surface models in Arctic ecosystems.« less