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Sample records for hospital mnh dar

  1. Cervical pre-malignant lesions in HIV infected women attending Care and Treatment Centre in a tertiary hospital, Dar es Salaam, Tanzania.

    PubMed

    Balandya, Belinda S; Pembe, Andrea B; Mwakyoma, Henry A

    2011-09-01

    The aims of this study was to determine proportion of HIV infected women with cervical pre-malignant lesions; and compare the use of Visual Inspection of the cervix after application of Acetic acid (VIA) and Papanicolau (Pap) smear in screening for cervical premalignant lesions in HIV positive women attending Care and Treatment Centre (CTC) at Muhimbili National Hospital (MNH), Dar es Salaam, Tanzania. A total of 316 women aged 18-70 years had a Pap smear taken for cytology, followed by spraying onto the cervix with 4% acetic acid and then inspecting it. Cytology was considered negative when there was no Cervical Intraepithelial Neoplasia (CIN) lesion reported from the Pap smear taken, and positive if CIN lesion 1, 2 or 3 was reported. Detection of a well-defined, opaque acetowhite lesion close to the squamocolumnar junction or close to the external cervical os constituted a positive VIA. Out of 316 women, 132 women had acetowhite lesions on VIA, making the proportion of abnormal cervical lesions to be 42.4%. One hundred and one out of 312 women (32.4%) had CIN lesions detected on Pap smear. The proportion of agreement between these two tests was 0.3. The proportion of agreement was moderate in women with advanced WHO HIV clinical stage of the disease and in women not on ART (Anti Retroviral Therapy). Women with CD-4 count less than 200 cells/mm3 had more abnormal cervical lesions. There is considerable proportion of HIV positive women with premalignant lesions of the cervix. Considering the proportion of HIV women with abnormal lesions and the difficulty in logistics of doing Pap smear in low resource settings, these results supports the recommendation to introduce screening of premalignant lesions of the cervix using VIA to all HIV infected women.

  2. Antibiotic use in urological surgeries: a six years review at Muhimbili National Hospital, Dar es salaam-Tanzania

    PubMed Central

    Nyongole, Obadia; Akoko, Larry; Mwanga, Ally; Mchembe, Mabula; Kamala, Benjamin; Mbembati, Naboth

    2015-01-01

    Introduction Antimicrobial prophylaxis for urologic procedures is a major issue, as potential advantages of antibiotic administration should be carefully weighed against potential side effects, microbial resistance, and health care costs. This study aimed to review a six years trend of antibiotic use in urological surgeries at Muhimbili National Hospital (MNH) being an experience in a typical third world environment. Methods This was a six years hospital based descriptive, retrospective study conducted of which all case notes of urological patients operated on in between January 2007 to December, 2012 were reviewed by using a structured data collecting tool. The data were analyzed using SPSS software. Results Male patients were the majority at 62% (450). The age range was 0 - 90 years, with a mean of 30 ± 22.09. Among the urological surgeries done at MNH 86.5% (628) received prophylactic antibiotics regardless of the type surgery done. Majority 63.7% (463) received antibiotics during induction. Ceftriaxone was the commonly given antibiotic regardless of the type of urological surgery done. Most of patients (86.4%) were given antibiotics for five days regardless whether it was for prophylactic or treatment intention. Conclusion Antibiotic use is still a challenge at our hospital with over use of prophylactic antibiotics without obvious indications. Prolonged use of prophylactic antibiotics beyond five days was the main finding. Ceftriaxone was the most given antibiotic regardless of the urological surgery done and its level of contamination. Antibiotic stewardship needs to be addressed urgently to avoid serious drug resistances leaving alone the cost implication. PMID:26952184

  3. Staphylococcus aureus MnhF Mediates Cholate Efflux and Facilitates Survival under Human Colonic Conditions

    PubMed Central

    Sannasiddappa, Thippeswamy H.; Hood, Graham A.; Hanson, Kevan J.; Costabile, Adele; Gibson, Glenn R.

    2015-01-01

    Resistance to the innate defenses of the intestine is crucial for the survival and carriage of Staphylococcus aureus, a common colonizer of the human gut. Bile salts produced by the liver and secreted into the intestines are one such group of molecules with potent antimicrobial activity. The mechanisms by which S. aureus is able to resist such defenses in order to colonize and survive in the human gut are unknown. Here we show that mnhF confers resistance to bile salts, which can be abrogated by efflux pump inhibitors. MnhF mediates the efflux of radiolabeled cholic acid both in S. aureus and when heterologously expressed in Escherichia coli, rendering them resistant. Deletion of mnhF attenuated the survival of S. aureus in an anaerobic three-stage continuous-culture model of the human colon (gut model), which represents different anatomical areas of the large intestine. PMID:25824834

  4. Electronic structure of the [MNH2]+ (M = Sc-Cu) complexes.

    PubMed

    Hendrickx, Marc F A; Clima, Sergiu

    2006-11-23

    B3LYP geometry optimizations for the [MNH2]+ complexes of the first-row transition metal cations (Sc+-Cu+) were performed. Without any exception the ground states of these unsaturated amide complexes were calculated to possess planar geometries. CASPT2 binding energies that were corrected for zero-point energies and including relativistic effects show a qualitative trend across the series that closely resembles the experimental observations. The electronic structures for the complexes of the early and middle transition metal cations (Sc+-Co+) differ from the electronic structures derived for the complexes of the late transition metal cations (Ni+ and Cu+). For the former complexes the relative higher position of the 3d orbitals above the singly occupied 2p(pi) HOMO of the uncoordinated NH2 induces an electron transfer from the 3d shell to 2p(pi). The stabilization of the 3d orbitals from the left to the right along the first-row transition metal series causes these orbitals to become situated below the HOMO of the NH2 ligand for Ni+ and Cu+, preventing a transfer from occurring in the [MNH2]+ complexes of these metal cations. Analysis of the low-lying states of the amide complexes revealed a rather unique characteristic of their electronic structures that was found across the entire series. Rather exceptionally for the whole of chemistry, pi-type interactions were calculated to be stronger than the corresponding sigma-type interactions. The origin of this extraordinary behavior can be ascribed to the low-lying sp2 lone pair orbital of the NH2 ligand with respect to the 3d level. PMID:17107114

  5. Challenges of caring for children with mental disorders: Experiences and views of caregivers attending the outpatient clinic at Muhimbili National Hospital, Dar es Salaam - Tanzania

    PubMed Central

    2012-01-01

    Background It is estimated that world-wide up to 20 % of children suffer from debilitating mental illness. Mental disorders that pose a significant concern include learning disorders, hyperkinetic disorders (ADHD), depression, psychosis, pervasive development disorders, attachment disorders, anxiety disorders, conduct disorder, substance abuse and eating disorders. Living with such children can be very stressful for caregivers in the family. Therefore, determination of challenges of living with these children is important in the process of finding ways to help or support caregivers to provide proper care for their children. The purpose of this study was to explore the psychological and emotional, social, and economic challenges that parents or guardians experience when caring for mentally ill children and what they do to address or deal with them. Methodology A qualitative study design using in-depth interviews and focus group discussions was applied. The study was conducted at the psychiatric unit of Muhimbili National Hospital in Tanzania. Two focus groups discussions (FGDs) and 8 in-depth interviews were conducted with caregivers who attended the psychiatric clinic with their children. Data analysis was done using content analysis. Results The study revealed psychological and emotional, social, and economic challenges caregivers endure while living with mentally ill children. Psychological and emotional challenges included being stressed by caring tasks and having worries about the present and future life of their children. They had feelings of sadness, and inner pain or bitterness due to the disturbing behaviour of the children. They also experienced some communication problems with their children due to their inability to talk. Social challenges were inadequate social services for their children, stigma, burden of caring task, lack of public awareness of mental illness, lack of social support, and problems with social life. The economic challenges were

  6. Zeeman relaxation of MnH (X{sup 7}{Sigma}{sup +}) in collisions with {sup 3}He: Mechanism and comparison with experiment

    SciTech Connect

    Turpin, F.; Stoecklin, T.; Halvick, Ph.

    2011-03-15

    We present a theoretical study of the Zeeman relaxation of the magnetically trappable lowest field seeking state of MnH ({sup 7{Sigma}}) in collisions with {sup 3}He. We analyze the collisional Zeeman transition mechanism as a function of the final diatomic state and its variation as a function of an applied magnetic field. We show that as a result of this mechanism the levels with {Delta}M{sub j}>2 give negligible contributions to the Zeemam relaxation cross section. We also compare our results to the experimental cross sections obtained from the buffer-gas cooling and magnetic trapping of this molecule and investigate the dependence of the Zeeman relaxation cross section on the accuracy of the three-body interaction at ultralow energies.

  7. The Zeeman effect in the (0,0) band of the A 7Pi-X 7Sigma(+) transition of manganese monohydride, MnH.

    PubMed

    Steimle, Timothy C; Wang, Hailing; Gengler, Jamie J; Stoll, Michael; Meijer, Gerard

    2008-10-28

    The Zeeman tuning of the P(1)(0) line (nu=17 568.35 cm(-1)) of the A (7)Pi-X (7)Sigma(+) (0,0) band of manganese monohydride, MnH, has been investigated. The laser induced fluorescence spectrum of a supersonic molecular beam sample was recorded at a resolution of approximately 40 MHz and with field strengths of up to 362.0 mT. The observed spectrum was successfully fitted using a traditional effective Zeeman Hamiltonian to determine an effective magnetic g-factor for the J=2 level of the F(1)-spin component of the A (7)Pi(v=0) state. Spectral predictions of the P(1)(0) line at field strengths used in magnetic trapping experiments are presented.

  8. Reanalysis and extension of the MnH A7Π- X7Σ + (0, 0) band: Fine structure and hyperfine-induced rotational branches

    NASA Astrophysics Data System (ADS)

    Varberg, Thomas D.; Gray, Jeffrey A.; Field, Robert W.; Merer, Anthony J.

    1992-12-01

    The A7Π- X7Σ + (0, 0) band of MnH at 568 nm has been recorded by laser fluorescence excitation spectroscopy. The original rotational analysis of Nevin [ Proc. R. Irish Acad.48A, 1-45 (1942); 50A, 123-137 (1945)] has been extended with some corrections at low J. Systematic internal hyperfine perturbations in the X7Σ + state, caused by the Δ N = 0, Δ J = ±1 matrix elements of the 55Mn hyperfine term in the Hamiltonian, have been observed in all seven electron spin components over the entire range of N″ studied. These perturbations destroy the "goodness" of J″ as a quantum number, giving rise to hyperfine-induced Δ J = ±2 rotational branches and to observable energy shifts of the most severely affected levels. The A7Π state, with A = 40.5 cm -1 and B = 6.35 cm -1, evolves rapidly from Hund's case ( a) to case ( b) coupling, which produces anomalous branch patterns at low J. A total of 156 rotational branches have been identified and fitted by least squares to an effective Hamiltonian, providing precise values for the rotational and fine structure constants. Values of the principal constants determined in the fit are (1σ errors in units of the last digit are listed in parentheses): The fine structures of the A7Π and X7Σ + states confirm the assignment of the A ← X transition as Mn 4 pπ ← 4 sσ in the presence of a spectator, nonbonding Mn 3 d5 ( 6S) open core.

  9. Casscf/ci Calculations for First Row Transition Metal Hydrides - the TIH(4-PHI), VH(5-DELTA), CRH(6-SIGMA-PLUS), MNH(7-SIGMA-PLUS), FEH(4,6-DELTA) and NIH(2-DELTA) States

    NASA Astrophysics Data System (ADS)

    Walch, S. P.; Bauschlicher, C. W., Jr.

    1983-04-01

    Calculations are performed for the predicted ground states of TiH(4-phi), VH(5-delta), CrH(6-sigma-plus), MnH(7-sigma-plus), Fett(4,6-delta) and NiH(2-delta). For FeH both the 6-delta and 4-delta states are studied, since both are likely candidates for the ground state. The ground state symmetries are predicted based on a combination of atomic coupling arguments and coupling of 4s(2)3d(n) and 4s(1)3d(n+1) terms in the molecular system. Electron correlation is included by a CASSCF/CI (SD) treatment. The CASSCF includes near-degeneracy effects, while correlation of the 3d electrons in included at the CI level.

  10. A pure inorganic 1D chain based on {Mo8O28} clusters and Mn(II) ions: [Mn(H2O)2Mo8O28 ] n 6 n -

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaofen; Yan, Yonghong; Wu, Lizhou; Yu, Chengxin; Dong, Xinbo; Hu, Huaiming; Xue, Ganglin

    2016-01-01

    A new pure inorganic polymer, (NH4)6n[Mn(H2O)2Mo8O28)]n(H2O)2n(1), has been synthesized and characterized by elemental analyses, IR spectrum, UV-vis absorption spectra, TG-DSC and electrochemical studies. In 1, [Mo8O28]8- anions act as tetradentate ligands and are alternately linked by Mn(H2O)2 2 + ions into a one-dimensional chain structure. It is interesting that 1 represents the first example of pure inorganic-inorganic hybrid based on octamolybdate and transition metal ions. Moreover, it was indicated that 1 had definite catalytic activities on the probe reaction of benzyl alcohol oxidation to benzaldehyde with H2O2.

  11. Infrared and Raman studies of manganese dihydrogen phosphate dihydrate, Mn(H 2PO 4) 2·2H 2O. I: Region of the vibrations of the phosphate ions and external modes of the water molecules

    NASA Astrophysics Data System (ADS)

    Koleva, V.; Stefov, V.; Cahil, A.; Najdoski, M.; Šoptrajanov, B.; Engelen, B.; Lutz, H. D.

    2009-01-01

    Infrared and Raman spectra of Mn(H 2PO 4) 2·2H 2O and of series of deuterated analogues recorded at room temperature (RT) and the boiling temperature of liquid nitrogen (LNT) have been presented and analyzed in detail in respect to the internal vibrations of the HPO4- ions and the external modes of the water molecules. Some vibrational couplings of the stretching and bending PO 4 modes have been discussed. The stretching PO 4 modes appear to be coupled with the in-plane δ(OH) and out-of-plane γ(OH) bending POH vibrations, while the bending PO 4 modes are coupled with the water librations. The mutual exclusion rule is obeyed for all vibrations under consideration. The large frequency separation between the γ(OH) modes of the two POH groups evidences for the considerable difference in the strength of the hydrogen bonds which they form. The observed A-B and g-u splittings for the γ(OH) vibrations show that both intra-chain and inter-chain interactions of the HPO4- ions are significant. Three bands of water librations are found in the IR and Raman spectra of Mn(H 2PO 4) 2·2H 2O and the observed g-u correlation splittings are smaller than 10 cm -1. Strong interactions of ν4 and ν2 modes of PO 4 with the librations of H 2O and D 2O molecules have been found.

  12. Characterizing Lava Flows With LiDAR

    NASA Astrophysics Data System (ADS)

    Deligne, N. I.; Cashman, K. V.; Deardorff, N.; Dietterich, H. R.; House, P. K.; Soule, S.

    2009-12-01

    Digital elevation models (DEMs) have been used in volcanology in predictive modeling of lava flow paths, both for assessment of potential hazards and specific predictions of lava flow paths. Topographic analysis of a lava flow is potentially useful for mapping and quantifying flow surface morphologies, which in turn can be used to determine flow emplacement conditions, such as effusion rate, steadiness of flow, and interactions with pre-existing topography and surface water. However, this has been limited in application because of the coarse resolution of most DEMs. In recent years, use of Light Detection and Ranging (LiDAR) airborne laser altimetry, capable of producing high resolution (≤ 1 meter) DEMs, has become increasingly common in the geomorphic and mapping community. However, volcanologists have made little use of airborne LiDAR. Here we compare information obtained using field observations and standard (10 meter) DEMs against LiDAR high resolution DEMs to assess the usefulness, capabilities, and limitations of LiDAR as applicable to lava flows. We compare morphologic characteristics of five lava flows of different compositions, tectonic settings, flow extents, slopes, and eruption duration: (1) 1984 Mauna Loa lava flow, Hawaii; (2) December 1974 Kilauea lava flow, Hawaii; (3) c. 1600 ybp Collier Cone lava flow, central Oregon Cascades; (4) Holocene lava flows from the Sand Mountain volcanic chain, central Oregon Cascades; and (5) Pleistocene lava flows along the Owyhee River, eastern Oregon basin and range. These lava flows range in composition from basalt to andesite, and have eruption durations ranging from 6 hours (observed) to years (inferred). We measure channel width, levee and flow front heights, compression ridge amplitude, wavelength and tumuli dimensions, and surface roughness. For all but the smallest scale features, LiDAR is easily used to quantify these features, which often is impossible or technically challenging to do in the field, while

  13. Using LiDAR to characterize logjams in lowland rivers

    NASA Astrophysics Data System (ADS)

    Abalharth, Mahdi; Hassan, Marwan A.; Klinkenberg, Brian; Leung, Vivian; McCleary, Richard

    2015-10-01

    Logjams significantly influence watershed hydrology, flow regime, channel morphology and stability, and processes in lowland rivers. Consequently, logjams play a major role in the existence and conservation of the riparian and aquatic ecosystems along major waterways. In this paper, we attempt to detect and quantify logjams in river channels using LiDAR technology in conjunction with traditional fieldwork. To the best of our knowledge, LiDAR-based analysis has not been used to characterize logjams in streams. Overall, when applied in a lowland river environment, LiDAR-based analysis demonstrates a comprehensive solution for detecting logjams in relation to the fieldwork, with a low rate of omission. A filtered approach predicted the presence of 95% of fieldwork-reported logjams (a 5% rate of omission), but also identified six logjams not identified in the field (a 10% rate of commission). A nonfiltered approach identified 87% of field-reported logjams, producing a 13% rate of omission and a 6.7% rate of commission. Dimension measurements were more consistent in the filtered LiDAR approach, showing 53%, 34%, and 90% of R2 improvements for the length, width, and height, respectively, over the unfiltered LiDAR values. As vegetation cover hindered accurate delineation of logjam boundaries by LiDAR, field and LiDAR measurements of nonvegetation-obstructed logjams were more highly correlated than the field and LiDAR measurements of partially and completely vegetation-obstructed logjams.

  14. Rigorous LiDAR Strip Adjustment with Triangulated Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Y. J.; Xiong, X. D.; Hu, X. Y.

    2013-10-01

    This paper proposes a POS aided LiDAR strip adjustment method. Firstly, aero-triangulation of the simultaneously obtained aerial images is conducted with a few photogrammetry-specific ground control points. Secondly, LiDAR intensity images are generated from the reflectance signals of laser foot points, and conjugate points are automatically matched between the LiDAR intensity image and the aero-triangulated aerial image. Control points used in LiDAR strip adjustment are derived from these conjugate points. Finally, LiDAR strip adjustment of real data is conducted with the POS aided LiDAR strip adjustment method proposed in this paper, and comparison experiment using three-dimensional similarity transformation method is also performed. The results indicate that the POS aided LiDAR strip adjustment method can significantly correct the planimetric and vertical errors of LiDAR strips. The planimetric correction accuracy is higher than average point distance while the vertical correction accuracy is comparable to that of the result of aero-triangulation. Moreover, the proposed method is obliviously superior to the traditional three-dimensional similarity transformation method.

  15. Infrared and Raman studies of manganese dihydrogen phosphate dihydrate, Mn(H 2PO 4) 2·2H 2O. Part II: Region of the internal OH group vibrations

    NASA Astrophysics Data System (ADS)

    Koleva, V.; Stefov, V.; Cahil, A.; Najdoski, M.; Šoptrajanov, B.; Engelen, B.; Lutz, H. D.

    2009-02-01

    Infrared and Raman spectra of Mn(H 2PO 4) 2·2H 2O and of series of deuterated analogues recorded at room temperature (RT) and at the boiling temperature of liquid nitrogen (LNT) have been presented and analyzed with respect to the OH vibrations. In the OH stretching mode region ABC bands behaviour is observed in accordance with the structural data for presence of a short hydrogen bond (2.609 Å). It is presumed that the A band of the ABC trio most probably originates from the stretching OH vibrations of strongly hydrogen bonded POH(1) group, but the contribution of the second POH(2) group and the water molecule should be also considered. The strength of the four hydrogen bonds as deduced from the infrared wavenumbers of the isotopically isolated OD groups has been discussed in terms of the respective O···O distances, the hydrogen bond acceptor capability of the oxygen atoms, the hydrogen bond donor strength of the H 2PO 4 ions and water molecules and the hydrogen bond acceptor angles. The influence of the cooperative effect has been also analyzed.

  16. Two temperature-independent spinomers of the dinuclear Mn(III) compound [{Mn(H(2)O)(phen)}(2)(mu-2-ClC(6)H(4)COO)(2)(mu-O)](ClO(4))(2).

    PubMed

    Gómez, Verónica; Corbella, Montserrat; Aullón, Gabriel

    2010-02-15

    Two spin isomers or spinomers of [{Mn(H(2)O)(phen)}(2)(mu-2-ClC(6)H(4)COO)(2)(mu-O)](ClO(4))(2) have been synthesized, characterized, and theoretically analyzed. The thermodynamically most stable, compound 1, shows a spin ground state S = 4, while the kinetically most favorable, compound 2.H(2)O, shows a spin ground state S = 0. Compound 1 exhibits ferromagnetic behavior, with J = 2.7 cm(-1), |D(Mn)| = 2.06 cm(-1), |E(Mn)| = 0.69 cm(-1), and zJ' = -0.11 cm(-1). Because of the anisotropy of the Mn(III) ions, the ground state S = 4 shows zero-field splitting (ZFS) with |D(4)| = 0.51 cm(-1), appreciably smaller than the D value for the single ion (D(Mn)), due to the relative orientations of the Jahn-Teller axes of both Mn(III) ions, which are quite perpendicular (102 degrees ). Compound 2.H(2)O shows antiferromagnetic coupling, with J = -12.6 cm(-1) (H = -JS(1).S(2) for both compounds). The formation of two spinomers has been explained by density functional theory (DFT) studies, which show that the stability of these compounds and their magnetic interaction are very sensitive to the rotation of the phenyl ring with respect to the carboxylate group of the 2-ClC(6)H(4)COO bridging ligand.

  17. Lava flow texture LiDAR signatures

    NASA Astrophysics Data System (ADS)

    Whelley, P.; Garry, W. B.; Scheidt, S. P.; Irwin, R. P., III; Fox, J.; Bleacher, J. E.; Hamilton, C. W.

    2014-12-01

    High-resolution point clouds and digital elevation models (DEMs) are used to investigate lava textures on the Big Island of Hawaii. An experienced geologist can distinguish fresh or degraded lava textures (e.g., blocky, a'a and pahoehoe) visually in the field. Lava texture depends significantly on eruption conditions, and it is therefore instructive, if accurately determined. In places where field investigations are prohibitive (e.g., Mercury, Venus, the Moon, Mars, Io and remote regions on Earth) lava texture must be assessed from remote sensing data. A reliable method for differentiating lava textures in remote sensing data remains elusive. We present preliminary results comparing properties of lava textures observed in airborne and terrestrial Light Detection and Ranging (LiDAR) data. Airborne data, in this study, were collected in 2011 by Airborne 1 Corporation and have a ~1m point spacing. The authors collected the terrestrial data during a May 2014 field season. The terrestrial scans have a heterogeneous point density. Points close to the scanner are 1 mm apart while 200 m in the distance points are 10 cm apart. Both platforms offer advantages and disadvantages beyond the differences in scale. Terrestrial scans are a quantitative representation of what a geologist sees "on the ground". Airborne scans are a point of view routinely imaged by other remote sensing tools, and can therefore be quickly compared to complimentary data sets (e.g., spectral scans or image data). Preliminary results indicate that LiDAR-derived surface roughness, from both platforms, is useful for differentiating lava textures, but at different spatial scales. As all lava types are quite rough, it is not simply roughness that is the most advantageous parameter; rather patterns in surface roughness can be used to differentiate lava surfaces of varied textures. This work will lead to faster and more reliable volcanic mapping efforts for planetary exploration as well as terrestrial

  18. 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.

  19. Exploring tree species signature using waveform LiDAR data

    NASA Astrophysics Data System (ADS)

    Zhou, T.; Popescu, S. C.; Krause, K.

    2015-12-01

    Successful classification of tree species with waveform LiDAR data would be of considerable value to estimate the biomass stocks and changes in forests. Current approaches emphasize converting the full waveform data into discrete points to get larger amount of parameters and identify tree species using several discrete-points variables. However, ignores intensity values and waveform shapes which convey important structural characteristics. The overall goal of this study was to employ the intensity and waveform shape of individual tree as the waveform signature to detect tree species. The data was acquired by the National Ecological Observatory Network (NEON) within 250*250 m study area located in San Joaquin Experimental Range. Specific objectives were to: (1) segment individual trees using the smoothed canopy height model (CHM) derived from discrete LiDAR points; (2) link waveform LiDAR with above individual tree boundaries to derive sample signatures of three tree species and use these signatures to discriminate tree species in a large area; and (3) compare tree species detection results from discrete LiDAR data and waveform LiDAR data. An overall accuracy of the segmented individual tree of more than 80% was obtained. The preliminary results show that compared with the discrete LiDAR data, the waveform LiDAR signature has a higher potential for accurate tree species classification.

  20. Tensor Modeling Based for Airborne LiDAR Data Classification

    NASA Astrophysics Data System (ADS)

    Li, N.; Liu, C.; Pfeifer, N.; Yin, J. F.; Liao, Z. Y.; Zhou, Y.

    2016-06-01

    Feature selection and description is a key factor in classification of Earth observation data. In this paper a classification method based on tensor decomposition is proposed. First, multiple features are extracted from raw LiDAR point cloud, and raster LiDAR images are derived by accumulating features or the "raw" data attributes. Then, the feature rasters of LiDAR data are stored as a tensor, and tensor decomposition is used to select component features. This tensor representation could keep the initial spatial structure and insure the consideration of the neighborhood. Based on a small number of component features a k nearest neighborhood classification is applied.

  1. Automatic registration method for mobile LiDAR data

    NASA Astrophysics Data System (ADS)

    Wang, Ruisheng; Ferrie, Frank P.

    2015-01-01

    We present an automatic mutual information (MI) registration method for mobile LiDAR and panoramas collected from a driving vehicle. The suitability of MI for registration of aerial LiDAR and aerial oblique images has been demonstrated under an assumption that minimization of joint entropy (JE) is a sufficient approximation of maximization of MI. We show that this assumption is invalid for the ground-level data. The entropy of a LiDAR image cannot be regarded as approximately constant for small perturbations. Instead of minimizing the JE, we directly maximize MI to estimate corrections of camera poses. Our method automatically registers mobile LiDAR with spherical panoramas over an approximate 4-km drive, and is the first example we are aware of that tests MI registration in a large-scale context.

  2. 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

  3. 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.

  4. Georeferenced LiDAR 3D Vine Plantation Map Generation

    PubMed Central

    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. PMID:22163952

  5. 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.

  6. 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. PMID:22163952

  7. Infections associated with severe malnutrition among hospitalised children in East Africa.

    PubMed

    Sunguya, B F P; Koola, J I; Atkinson, S

    2006-09-01

    Severe protein-energy malnutrition (PEM) predisposes affected children to various infections, which either worsens their nutritional status or causes malnutrition, hence complicating their management and outcome. This study was carried out to determine the infections associated with severe malnutrition among children admitted at Kilifi District Hospital (KDH) in Kenya and Muhimbili National Hospital (MNH) in Dar es Salaam, Tanzania. Data was collected from hospital register books and online system database. A total of 1121 children with severe malnutrition were admitted during a period of one year (2004-2005) (MNH = 781; KDH = 340). The proportion of male children with malnutrition was higher than that of female children. Non-oedematous malnutrition was more prevalent at MNH (N = 504; 64%) than KDH (N = 130; 38%). Conversely, oedematous was more prevalence than non-oedematous malnutrition among children admitted at KDH (N = 2 10; 61.7%). More than 75% of all patients with severe PEM were children < 2 years old. Thirty-six per cent of all severe PEM cases had malaria in both hospitals. Forty-five per cent of all admitted patients with severe PEM at KDH had diarrhoea. Two hundred twenty two (28%) and 64 (19%) of the children with severe malnutrition died at MNH and KDH, respectively. Oedematous PEM was associated with a higher case fatality rate than non-oedematous one (P < 0.05). At MNH, 86% of the patients who died with severe malnutrition had other co-morbidities. More (46%) oedematous malnourished patients with co-infections died at MNH than non-oedematous malnourished patients (19%). At KDH, septicaemia was the leading cause of death (55%) among severely malnourished patients. In conclusion, coinfections complicate the management of severe malnutrition and are associated with higher death rate. Management of such infections is of paramount importance to reduce case fatality rates.

  8. Uas Topographic Mapping with Velodyne LiDAR Sensor

    NASA Astrophysics Data System (ADS)

    Jozkow, G.; Toth, C.; Grejner-Brzezinska, D.

    2016-06-01

    Unmanned Aerial System (UAS) technology is nowadays willingly used in small area topographic mapping due to low costs and good quality of derived products. Since cameras typically used with UAS have some limitations, e.g. cannot penetrate the vegetation, LiDAR sensors are increasingly getting attention in UAS mapping. Sensor developments reached the point when their costs and size suit the UAS platform, though, LiDAR UAS is still an emerging technology. One issue related to using LiDAR sensors on UAS is the limited performance of the navigation sensors used on UAS platforms. Therefore, various hardware and software solutions are investigated to increase the quality of UAS LiDAR point clouds. This work analyses several aspects of the UAS LiDAR point cloud generation performance based on UAS flights conducted with the Velodyne laser scanner and cameras. The attention was primarily paid to the trajectory reconstruction performance that is essential for accurate point cloud georeferencing. Since the navigation sensors, especially Inertial Measurement Units (IMUs), may not be of sufficient performance, the estimated camera poses could allow to increase the robustness of the estimated trajectory, and subsequently, the accuracy of the point cloud. The accuracy of the final UAS LiDAR point cloud was evaluated on the basis of the generated DSM, including comparison with point clouds obtained from dense image matching. The results showed the need for more investigation on MEMS IMU sensors used for UAS trajectory reconstruction. The accuracy of the UAS LiDAR point cloud, though lower than for point cloud obtained from images, may be still sufficient for certain mapping applications where the optical imagery is not useful.

  9. Using LiDAR technology in forestry activities.

    PubMed

    Akay, Abdullah Emin; Oğuz, Hakan; Karas, Ismail Rakip; Aruga, Kazuhiro

    2009-04-01

    Managing natural resources in wide-scale areas can be highly time and resource consuming task which requires significant amount of data collection in the field and reduction of the data in the office to provide the necessary information. High performance LiDAR remote sensing technology has recently become an effective tool for use in applications of natural resources. In the field of forestry, the LiDAR measurements of the forested areas can provide high-quality data on three-dimensional characterizations of forest structures. Besides, LiDAR data can be used to provide very high quality and accurate Digital Elevation Model (DEM) for the forested areas. This study presents the progress and opportunities of using LiDAR remote sensing technology in various forestry applications. The results indicate that LiDAR based forest structure data and high-resolution DEMs can be used in wide-scale forestry activities such as stand characterizations, forest inventory and management, fire behaviour modeling, and forest operations. PMID:18365761

  10. Biomass Estimation for Individual Trees using Waveform LiDAR

    NASA Astrophysics Data System (ADS)

    Wang, K.; Kumar, P.; Dutta, D.

    2015-12-01

    Vegetation biomass information is important for many ecological models that include terrestrial vegetation in their simulations. Biomass has strong influences on carbon, water, and nutrient cycles. Traditionally biomass estimation requires intensive, and often destructive, field measurements. However, with advances in technology, airborne LiDAR has become a convenient tool for acquiring such information on a large scale. In this study, we use infrared full waveform LiDAR to estimate biomass information for individual trees in the Sangamon River basin in Illinois, USA. During this process, we also develop automated geolocation calibration algorithms for raw waveform LiDAR data. In the summer of 2014, discrete and waveform LiDAR data were collected over the Sangamon River basin. Field measurements commonly used in biomass equations such as diameter at breast height and total tree height were also taken for four sites across the basin. Using discrete LiDAR data, individual trees are delineated. For each tree, a voxelization methods is applied to all waveforms associated with the tree to result in a pseudo-waveform. By relating biomass extrapolated using field measurements from a training set of trees to waveform metrics for each corresponding tree, we are able to estimate biomass on an individual tree basis. The results can be especially useful as current models increase in resolution.

  11. 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.

  12. Modeling loblolly pine dominant height using airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Maceyka, Andy

    The dominant height of 73 georeferenced field sample plots were modeled from various canopy height metrics derived by means of a small-footprint laser scanning technology, known as light detection and ranging (or just LiDAR), over young and mature forest stands using regression analysis. LiDAR plot metrics were regressed against field measured dominant height using Best Subsets Regression to reduce the number of models. From those models, regression assumptions were evaluated to determine which model was actually the best. The best model included the 1st and 90th height percentiles as predictors and explained 95% of the variance in average dominant height.

  13. 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

  14. Sickle Cell Disease in Pregnancy: Trend and Pregnancy Outcomes at a Tertiary Hospital in Tanzania

    PubMed Central

    Muganyizi, Projestine S.; Kidanto, Hussein

    2013-01-01

    SCD in pregnancy is associated with increased adverse fetal and maternal outcomes. In Tanzania where the frequency of sickle cell trait is 13% there has been scanty data on SCD in pregnancy. With progressive improvement in childhood survival the burden of SCD in pregnancy will increase. We analyzed all deliveries at Muhimbili National Hospital (MNH) from 1999 to 2011. Fetal and maternal outcomes of SCD deliveries were compared with non-SCD. Data were analyzed using IBM SPSS statistics version 19. Chi square and Fisher Exact tests were used to compare proportions and the independent t-test for continuous data. To predict risks of adverse effects, odds ratios were determined using multivariate logistic regression. A p-value<0.05 was considered significant. In total, 157,473 deliveries occurred at MNH during the study period, of which 149 were SCD (incidence of 95 SCD per 100,000 deliveries). The incidence of SCD had increased from 76 per 100,000 deliveries in the 1999–2002 period to over 100 per 100, 000 deliveries in recent years. The mean maternal age at delivery was lower in SCD (24.0±5.5 years) than in non-SCD deliveries (26.2±6.0 years), p<0.001. Compared with non-SCD (2.9±0.7 Kg), SCD deliveries had less mean birth-weight (2.6±0.6 Kg), p<0.001. SCD were more likely than non-SCD to deliver low APGAR score at 5 minutes (34.5% Vs 15.0%, OR = 3.0, 95%CI: 2.1–4.2), stillbirths (25.7% Vs 7.5%, OR = 4.0, 95%CI: 2.8–5.8). There was excessive risk of maternal deaths in SCD compared to non-SCD (11.4% Vs 0.4%, OR = 29, 95%CI: 17.3–48.1). The leading cause of deaths in SCD was infections in wholly 82% in contrast to only 32% in non-SCD. In conclusion SCD in pregnancy is an emerging problem at MNH with increased adverse fetal outcomes and excessive maternal mortality mainly due to infections. PMID:23418582

  15. Audit of clinical-laboratory practices in haematology and blood transfusion at Muhimbili National Hospital in Tanzania.

    PubMed

    Makubi, Abel N; Meda, Collins; Magesa, Alex; Minja, Peter; Mlalasi, Juliana; Salum, Zubeda; Kweka, Rumisha E; Rwehabura, James; Quaresh, Amrana; Magesa, Pius M; Robert, David; Makani, Julie; Kaaya, Ephata

    2012-10-01

    In Tanzania, there is paucity of data for monitoring laboratory medicine including haematology. This therefore calls for audits of practices in haematology and blood transfusion in order to provide appraise practice and devise strategies that would result in improved quality of health care services. This descriptive cross-sectional study which audited laboratory practice in haematology and blood transfusion at Muhimbili National Hospital (MNH) aimed at assessing the pre-analytical stage of laboratory investigations including laboratory request forms and handling specimen processing in the haematology laboratory and assessing the chain from donor selection, blood component processing to administration of blood during transfusion. A national standard checklist was used to audit the laboratory request forms (LRF), phlebotomists' practices on handling and assessing the from donor selection to administration 6f blood during transfusion. Both interview and observations were used. A total of 195 LRF were audited and 100% of had incomplete information such as patients' identification numbers, time sample ordered, reason for request, summary of clinical assessment and differential diagnoses. The labelling of specimens was poorly done by phlebotomists/clinicians in 82% of the specimens. Also 65% (132/202) of the blood samples delivered in the haematology laboratory did not contain the recommended volume of blood. There was no laboratory request form specific for ordering blood and there were no guidelines for indication of blood transfusion in the wards/ clinics. The blood transfusion laboratory section was not participating in external quality assessment and the hospital transfusion committee was not in operation. It is recommended that a referral hospital like MNH should have a transfusion committee to provide an active forum to facilitate communication between those involved with transfusion, monitor, coordinate and audit blood transfusion practices as per national

  16. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 47 Telecommunication 2 2014-10-01 2014-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  17. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 47 Telecommunication 2 2013-10-01 2013-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  18. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 2 2012-10-01 2012-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  19. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  20. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 2 2011-10-01 2011-10-01 false Satellite DARS applications subject to...) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401 Satellite DARS applications subject to competitive bidding. Mutually exclusive initial applications for...

  1. 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

  2. High-intensity cyclotron for the IsoDAR experiment

    NASA Astrophysics Data System (ADS)

    Campo, D.; IsoDAR Collaboration

    2015-03-01

    The IsoDAR experiment is the MIT proposal to investigate about several neutrino properties, in order to explain some anomalies experimentally observed. It requires 10mA of proton beam at the energy of 60MeV to produce a high-intensity electron antineutrino flux from the production and the decay of 8Li: it is an ambitious goal for the accelerator design, due also to the fact that the machine has to be placed near a neutrino detector, like KAMLAND or WATCHMAN, located in underground sites. A compact cyclotron able to accelerate H2+ molecule beam up to energy of 60MeV/amu is under study. The critical issues of this machine concern the beam injection due to the effects of space charge, the efficiency of the beam extraction and the technical solutions needed to the machine assembly. Here, the innovative solutions and the preliminary results achieved by the IsoDAR team are discussed.

  3. Volume component analysis for classification of LiDAR data

    NASA Astrophysics Data System (ADS)

    Varney, Nina M.; Asari, Vijayan K.

    2015-03-01

    One of the most difficult challenges of working with LiDAR data is the large amount of data points that are produced. Analysing these large data sets is an extremely time consuming process. For this reason, automatic perception of LiDAR scenes is a growing area of research. Currently, most LiDAR feature extraction relies on geometrical features specific to the point cloud of interest. These geometrical features are scene-specific, and often rely on the scale and orientation of the object for classification. This paper proposes a robust method for reduced dimensionality feature extraction of 3D objects using a volume component analysis (VCA) approach.1 This VCA approach is based on principal component analysis (PCA). PCA is a method of reduced feature extraction that computes a covariance matrix from the original input vector. The eigenvectors corresponding to the largest eigenvalues of the covariance matrix are used to describe an image. Block-based PCA is an adapted method for feature extraction in facial images because PCA, when performed in local areas of the image, can extract more significant features than can be extracted when the entire image is considered. The image space is split into several of these blocks, and PCA is computed individually for each block. This VCA proposes that a LiDAR point cloud can be represented as a series of voxels whose values correspond to the point density within that relative location. From this voxelized space, block-based PCA is used to analyze sections of the space where the sections, when combined, will represent features of the entire 3-D object. These features are then used as the input to a support vector machine which is trained to identify four classes of objects, vegetation, vehicles, buildings and barriers with an overall accuracy of 93.8%

  4. Compact Adaptable Mobile LiDAR System Deployment

    NASA Astrophysics Data System (ADS)

    Glennie, C. L.; Brooks, B. A.; Ericksen, T. L.; Hudnut, K. W.; Foster, J. H.; Hauser, D.; Avery, J.

    2012-12-01

    Airborne LiDAR (LIght Detection And Ranging) systems have become a standard mechanism for acquiring dense high-precision topography, making it possible to perform large scale documentation (100's of km2) per day at spatial scales as fine as a few decimeters horizontally and a few centimeters vertically. However, current airborne and terrestrial LiDAR systems suffer from a number of drawbacks. They are expensive, bulky, require significant power supplies, and are often optimized for use in only one type of mobility platform. It would therefore be advantageous to design a lightweight, compact and relatively inexpensive multipurpose LiDAR and imagery system that could be used from a variety of mobility platforms - both terrestrial and airborne. The system should be quick and easy to deploy, and require a minimum amount of existing infrastructure for operational support. With these goals in mind, our research teams have developed a prototype field deployable compact dynamic laser scanning system that is configured for use on a variety of mobility platforms, including backpack wearable, as well as unmanned aerial vehicles (e.g. balloons & helicopters) and small off-road vehicles such as ATV's. The system is small, self-contained, relatively inexpensive, and easy to deploy. The first version of this multipurpose LiDAR system has been successfully tested in both backpack configuration and on a tethered flight attached to a helium balloon. We will present system design and development details, along with field experiences and a detailed accuracy analysis of the acquired point clouds which show that accuracy of 3-5 cm (1 sigma) vertical can be achieved in both backpack and balloon modalities.

  5. Syntheses, Spectroscopic Data, and X-ray Diffraction Structures of the Heterometallic RuRe Face-shared Bioctahedral (eta(6)-cymene)Ru(mu-Cl)(3)Re(CO)(3) and MnRu2 Edge-shared Trioctahedral [fac-ClRu(CO)(3)](2)(mu-Cl)(4)Mn(H2O)(2) Complexes

    SciTech Connect

    Wang, Xiaoping; Hunt, Sean W; Richmond, Michael G.

    2009-01-01

    Thermolysis of the diruthenium compound [(eta(6)-cymene)RuCl2](2) (1) with ClRe(CO)(5) (2) leads to the formation of the new confacial bioctahedral compound (eta(6)-cymene) Ru(mu-Cl)(3)Re(CO)(3) (3) in good yields; the same product has also been isolated when a mixture of 1 and 2 is irradiated with near UV-vis light for an extended period of time. Heating 1 and ClMn(CO)(5) (4) does not furnish the corresponding manganese analogue of 3 but rather the trioctahedral halide-bridged product [fac-ClRu(CO)(3)](2)(mu-Cl)(4)Mn(H2O)(2) (5). 3 and 5 have been fully characterized in solution and their molecular structures established by X-ray crystallography.

  6. CASSCF/CI calculations for first row transition metal hydrides - The TiH(4-phi), VH(5-delta), CrH(6-sigma-plus), MnH(7-sigma-plus), FeH(4,6-delta) and NiH(2-delta) states

    NASA Technical Reports Server (NTRS)

    Walch, S. P.; Bauschlicher, C. W., Jr.

    1983-01-01

    Calculations are performed for the predicted ground states of TiH(4-phi), VH(5-delta), CrH(6-sigma-plus), MnH(7-sigma-plus), Fett(4,6-delta) and NiH(2-delta). For FeH both the 6-delta and 4-delta states are studied, since both are likely candidates for the ground state. The ground state symmetries are predicted based on a combination of atomic coupling arguments and coupling of 4s(2)3d(n) and 4s(1)3d(n+1) terms in the molecular system. Electron correlation is included by a CASSCF/CI (SD) treatment. The CASSCF includes near-degeneracy effects, while correlation of the 3d electrons in included at the CI level.

  7. Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories

    NASA Astrophysics Data System (ADS)

    Tao, Shengli; Wu, Fangfang; Guo, Qinghua; Wang, Yongcai; Li, Wenkai; Xue, Baolin; Hu, Xueyang; Li, Peng; Tian, Di; Li, Chao; Yao, Hui; Li, Yumei; Xu, Guangcai; Fang, Jingyun

    2015-12-01

    The rapid development of light detection and ranging (LiDAR) techniques is advancing ecological and forest research. During the last decade, numerous single tree segmentation techniques have been developed using airborne LiDAR data. However, accurate crown segmentation using terrestrial or mobile LiDAR data, which is an essential prerequisite for extracting branch level forest characteristics, is still challenging mainly because of the difficulties posed by tree crown intersection and irregular crown shape. In the current work, we developed a comparative shortest-path algorithm (CSP) for segmenting tree crowns scanned using terrestrial (T)-LiDAR and mobile LiDAR. The algorithm consists of two steps, namely trunk detection and subsequent crown segmentation, with the latter inspired by the well-proved metabolic ecology theory and the ecological fact that vascular plants tend to minimize the transferring distance to the root. We tested the algorithm on mobile-LiDAR-scanned roadside trees and T-LiDAR-scanned broadleaved and coniferous forests in China. Point-level quantitative assessments of the segmentation results showed that for mobile-LiDAR-scanned roadside trees, all the points were classified to their corresponding trees correctly, and for T-LiDAR-scanned broadleaved and coniferous forests, kappa coefficients ranging from 0.83 to 0.93 were obtained. We believe that our algorithm will make a contribution to solving the problem of crown segmentation in T-LiDAR scanned-forests, and might be of interest to researchers in LiDAR data processing and to forest ecologists. In addition, our research highlights the advantages of using ecological theories as guidelines for processing LiDAR data.

  8. Synergy Between LiDAR and Image Data in Context of Building Extraction

    NASA Astrophysics Data System (ADS)

    Dal Poz, A. P.

    2014-11-01

    This paper compares the paradigms of LiDAR and aerophotogrammetry in the context of building extraction and briefly discusses a photogrammetric strategy for refining building roof polyhedrons previously extracted from LiDAR data. In general, empirical and theoretical studies have confirmed that LiDAR-based methodologies are more suitable in extracting planar roof faces and ridges of the roof, whereas the aerophotogrammetry are more suitable in extracting building roof outlines. In order to exemplify how to explore these properties, it is presented a photogrammetric method for refining 3D building roof contours extracted from airborne LiDAR data. Examples of application are provided for this refining approach.

  9. Norovirus - hospital

    MedlinePlus

    Gastroenteritis - norovirus; Colitis - norovirus; Hospital acquired infection - norovirus ... Symptoms start within 24 to 48 hours of infection, and can last for 1 ... norovirus. Hospital patients who are very old, very young, or ...

  10. The Daily Activity Report (DAR) a Novel Measure of Functional Outcome for Serious Mental Illness

    PubMed Central

    Velligan, Dawn I.; Mintz, Jim; Sierra, Cynthia; Martin, Mona L.; Fredrick, Megan; Maglinte, Gregory A.; Corey-Lisle, Patricia K.

    2016-01-01

    The assessment of real-world functional outcomes in clinical trials for medications targeting negative symptoms and cognitive impairment is extremely important. We tested the psychometric properties of the Daily Activity Report (DAR), a novel assessment of productive daily activity. We administered the DAR and additional assessments of functional outcome, functional capacity, cognition and symptomatology to 50 individuals with schizophrenia at 2 time points, 1 month apart and to 25 healthy controls. The DAR records a person’s daily activity for 7 consecutive days based upon phone calls made 3 times a day. A total score and scores in 3 domains; instrumental activities (ie, independent living), social and work or school related activities are generated for the DAR. Inter-item consistency was high 0.89–0.94 for each domain and 0.88 overall. Test–retest reliability across 1 month for the total DAR score was 0.67, P < .0001. The total DAR score as well as scores for social activity and nondomestic work/school differed significantly between control and patient participants (P < .0001). DAR domain scores were associated with negative symptoms and functional outcomes, but the primary score related to these measures was the work/school dimension of the DAR. DAR scores were only weakly and nonsignificantly related to positive symptoms. This study provides preliminary support for the reliability and validity of the DAR using interviewer administration. The development of a patient reported version of the DAR using smart phone technology with automatic scoring is the next step. PMID:26712856

  11. Identifying Colluvial Slopes by Airborne LiDAR Analysis

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Colluvial slopes are one of major sources of landslides. Identifying the locations of the slopes will help reduce the risk of disasters, by avoiding building infrastructure and properties nearby, or if they are already there, by applying appropriate counter measures before it suddenly moves. In this study, airborne LiDAR data was analyzed to find their geomorphic characteristics to use for extracting their locations. The study site was set in the suburb of Sapporo City, Hokkaido in Japan. The area is underlain by Andesite and Tuff and prone to landslides. Slope angle and surface roughness were calculated from 5 m resolution DEM. These filters were chosen because colluvial materials deposit at around the angle of repose and accumulation of loose materials was considered to form a peculiar surface texture differentiable from other slope types. Field survey conducted together suggested that colluvial slopes could be identified by the filters with a probability of 80 percent. Repeat LiDAR monitoring of the site by an unmanned helicopter indicated that those slopes detected as colluviums appeared to be moving at a slow rate. In comparison with a similar study from the crushed zone in Japan, the range of slope angle indicative of colluviums agreed with the Sapporo site, while the texture was rougher due to larger debris composing the slopes.

  12. Performance testing of LiDAR exploitation software

    NASA Astrophysics Data System (ADS)

    Varela-González, M.; González-Jorge, H.; Riveiro, B.; Arias, P.

    2013-04-01

    Mobile LiDAR systems are being used widely in recent years for many applications in the field of geoscience. One of most important limitations of this technology is the large computational requirements involved in data processing. Several software solutions for data processing are available in the market, but users are often unknown about the methodologies to verify their performance accurately. In this work a methodology for LiDAR software performance testing is presented and six different suites are studied: QT Modeler, AutoCAD Civil 3D, Mars 7, Fledermaus, Carlson and TopoDOT (all of them in x64). Results depict as QTModeler, TopoDOT and AutoCAD Civil 3D allow the loading of large datasets, while Fledermaus, Mars7 and Carlson do not achieve these powerful performance. AutoCAD Civil 3D needs large loading time in comparison with the most powerful softwares such as QTModeler and TopoDOT. Carlson suite depicts the poorest results among all the softwares under study, where point clouds larger than 5 million points cannot be loaded and loading time is very large in comparison with the other suites even for the smaller datasets. AutoCAD Civil 3D, Carlson and TopoDOT show more threads than other softwares like QTModeler, Mars7 and Fledermaus.

  13. Applying the Moment Distance Framework to LiDAR Waveforms

    NASA Astrophysics Data System (ADS)

    Salas, E. L.; Aguilar-Amuchastegui, N.; Henebry, G. M.

    2010-12-01

    In the past decade or so, there have only been limited approaches formulated for the analysis of waveform LiDAR data. We illustrate how the Moment Distance (MD) framework can characterize the shape of the LiDAR waveforms using simple, computationally fast, geometric operations. We assess the relationship of the MD metrics to some key waveform landmarks - such as locations of peaks, power of returns, and pseudo-heights - using LVIS datasets acquired over a tropical forest in La Selva, Costa Rica in 1998 and 2005. We also apply the MD framework to 2003 LVIS data from Howland Forest, Maine. We also explore the effects of noise on the MD Index (MDI). Our results reveal that the MDI can capture important dynamics in canopy structure. Movement in the location of the peaks is detected by shifts in the MDI. Because this new approach responds to waveform shape, it is more sensitive to changes of location of peak returns than to the power of the return. Results also suggest a positive relationship between the MDI and the canopy pseudo-height.

  14. IsoDAR - A Definitive Search for Sterile Neutrinos

    NASA Astrophysics Data System (ADS)

    Barletta, William

    2013-04-01

    The steady development of high power cyclotrons, mostly in industry, is making possible a definitive, highly cost effective approach to the search for sterile neutrinos. In the proposed IsoDAR experiment a 600 kW beam of protons from a 60 MeV, H2+ cyclotron will impinge on a lithium target to generate copious Li-8. The Li-8 then decays at rest to yield a powerful source of anti-neutrinos that can be located ˜20 m from a hydrogenous detector. In particular our collaboration has been designing the accelerator / target system to be consistent with installation in the Kamioka mine to use the Kamland detector to record inverse beta decay events. We show that this source / detector combination can reveal or exclude the global-fit allowed region at 5 sigma in four months and differentiate between 1 and 2 sterile neutrinos with a few years of continued running. Our studies also show that high power cyclotrons will provide the most cost effective source for such an experiment. In addition, the 60 MeV IsoDAR cyclotron would be an ideal injector for DAEdALUS, our approach to measuring CP violation in the neutrino sector with decay-at-rest experiment.

  15. 4D Terrestrial LiDAR Data Collection: Geomorphic and Hydraulic Applications (Invited)

    NASA Astrophysics Data System (ADS)

    Minear, J. T.; Wright, S. A.; Kinzel, P. J.; Draut, A. E.; Logan, J.

    2013-12-01

    Terrestrial LiDAR, also known as T-LiDAR, ground-based LiDAR, or Terrestrial Laser Scanning, can provide great insights into some types of geomorphic and hydraulic studies, particularly when collected repeatedly over time. Because T-LiDAR collects a large amount of data on a set grid, oftentimes processes are inadvertently captured that are not part of the initial research question but can be important factors in their own right. In addition, though T-LiDAR is most often used at relatively small sites for high-precision scanning, it also can be used for relatively rapid meso-scale site measurements, albeit typically with less precision. Using examples from the Elwha River dam removals, WA, a canal experiment in NE, and several small river restoration sites in CA, we highlight several important and innovative uses of T-LiDAR measurements, including quick temporal scale changes in water surface features and larger temporal- and spatial-scale changes in reservoir deltaic deposits and longitudinal profile features. Also discussed will be some considerations for improving T-LiDAR error estimation and a comparison to other data collection techniques, including aerial LiDAR, structure-from-motion photogrammetry, and UAV- and plane-captured photogrammetry.

  16. Wetland inundation mapping and change monitoring using landsat and airborne LiDAR data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper presents a new approach for mapping wetland inundation change using Landsat and LiDAR intensity data. In this approach, LiDAR data were used to derive highly accurate reference subpixel inundation percentage (SIP) maps at the 30-m resolution. The reference SIP maps were then used to est...

  17. Dia de Dar Gracias. Modulo Nivel Primario. (Day to Give Thanks. Module Primary Level.)

    ERIC Educational Resources Information Center

    Espinoza, Delia; Lopez, Santiago, III

    Dia de Dar Gracias (Thanksgiving) is the subject of this primary level unit. The unit objectives are to: (1) know about El Dia de Dar Gracias as it is celebrated in the United States; (2) know how the Mayas celebrated it; (3) understand the context of the stories in the unit; (4) know about the main food used, the turkey; (5) distinguish other…

  18. Nacelle LiDAR online wind field reconstruction applied to feedforward pitch control

    NASA Astrophysics Data System (ADS)

    GUILLEMIN, F.; DOMENICO, D. DI; NGUYEN, N.; SABIRON, G.; BOQUET, M.; GIRARD, N.; COUPIAC, O.

    2016-09-01

    This paper presents innovative filtering and reconstruction techniques of nacelle LiDAR data, and exploitation of obtained wind anticipation capabilities for wind turbine control strategy. The implemented algorithms are applied under industrial constraints, on a MAIA EOLIS wind turbine, equipped with a LEOSPHERE 5-beams pulsed LiDAR, during experimental campaigns of SMARTEOLE collaborative project.

  19. 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.

  20. 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

  1. Multipath Estimation in Urban Environments from Joint GNSS Receivers and LiDAR Sensors

    PubMed Central

    Ali, Khurram; Chen, Xin; Dovis, Fabio; De Castro, David; Fernández, Antonio J.

    2012-01-01

    In this paper, multipath error on Global Navigation Satellite System (GNSS) signals in urban environments is characterized with the help of Light Detection and Ranging (LiDAR) measurements. For this purpose, LiDAR equipment and Global Positioning System (GPS) receiver implementing a multipath estimating architecture were used to collect data in an urban environment. This paper demonstrates how GPS and LiDAR measurements can be jointly used to model the environment and obtain robust receivers. Multipath amplitude and delay are estimated by means of LiDAR feature extraction and multipath mitigation architecture. The results show the feasibility of integrating the information provided by LiDAR sensors and GNSS receivers for multipath mitigation. PMID:23202177

  2. Multipath estimation in urban environments from joint GNSS receivers and LiDAR sensors.

    PubMed

    Ali, Khurram; Chen, Xin; Dovis, Fabio; De Castro, David; Fernández, Antonio J

    2012-10-30

    In this paper, multipath error on Global Navigation Satellite System (GNSS) signals in urban environments is characterized with the help of Light Detection and Ranging (LiDAR) measurements. For this purpose, LiDAR equipment and Global Positioning System (GPS) receiver implementing a multipath estimating architecture were used to collect data in an urban environment. This paper demonstrates how GPS and LiDAR measurements can be jointly used to model the environment and obtain robust receivers. Multipath amplitude and delay are estimated by means of LiDAR feature extraction and multipath mitigation architecture. The results show the feasibility of integrating the information provided by LiDAR sensors and GNSS receivers for multipath mitigation.

  3. Using a multiwavelength LiDAR for improved remote sensing of natural waters.

    PubMed

    Gray, Deric J; Anderson, John; Nelson, Jean; Edwards, Jarrod

    2015-11-01

    This paper describes research to characterize the benefits of a multiwavelength oceanographic LiDAR for various water types. Field measurements were conducted to establish endmembers representative of both typical and extremely challenging natural conditions. Laboratory tests were performed using a prototype multiwavelength LiDAR in water tanks with optical conditions simulating both sediment-laden and biologically rich water types. LiDAR models were used to simulate the LiDAR signal from both field and laboratory experiments. Our measurements and models show that using a laser wavelength of 470-490 nm in the open ocean leads to an improvement factor of 1.50-1.75 compared to a 532 nm system. In more turbid areas using a laser wavelength of 560-580 nm leads to an improvement factor of 1.25. We conclude by demonstrating how using multiple LiDAR wavelengths can help detect and characterize constituents in the water column.

  4. Towards a LiDAR based geomorphological database of Sweden

    NASA Astrophysics Data System (ADS)

    Peterson, Gustaf; Smith, Colby A.

    2013-04-01

    Geomorphological maps can be important for both societal development and scientific research especially with the use of new technology and consideration for the end user's needs. Since 2009, the Swedish mapping agency (Lantmäteriet) has been using airborne light detection and ranging (LiDAR) to create a detailed "bare earth" digital elevation model (DEM) of Sweden. Presently, a LiDAR derived DEM with 2 m horizontal and 0.25 m vertical resolution exist for about half of the country. This data set enables viewing of the landscape in a new more detailed way; landforms never before seen can now be delineated easily in a desktop environment. We are using this DEM to map the geomorphology, bringing into existence a highly detailed, digitial, geomorphologic database and map. While prior geomorphological maps exist for Sweden, the new map being compiled by the Geological Survey of Sweden (SGU) will be the first one to be derived from and presented in an entirely digital format. With the use of GIS technology, it is possible to present a map with different layers and symbology depending on the scale of the area of interest. For example, when looking at a map at a small scale, every moraine within a moraine complex is visible, but when viewed at a larger scale the moraine complex is presented as a single object. The digital presentation allows users to select scale-appropriate geomorphological data to their needs. By coupling other SGU or external databases with the geomorphological database it is possible to produce a wide range of products suitable for a wide range of uses. For example, by adding bedrock or geochemical data to landforms indicative of ice flow direction, a product useful for mineral prospecting is created. Other derivative applications may include groundwater studies or evaluation of geoheritage areas. Regarding scientific applications, the new LiDAR data have enabled mapping of geomorphic landforms in greater detail than previous Swedish maps. In addition

  5. 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

  6. Blood culture contamination in Tanzania, Malawi, and the United States: a microbiological tale of three cities.

    PubMed

    Archibald, Lennox K; Pallangyo, Kisali; Kazembe, Peter; Reller, L Barth

    2006-12-01

    We conducted retrospective, comparative analyses of contamination rates for cultures of blood obtained in the emergency rooms of Muhimbili National Hospital (MNH) in Dar es Salaam, Tanzania; Lilongwe Central Hospital (LCH) in central Malawi; and the Duke University Medical Center (DUMC) in the United States. None of the emergency room patients had indwelling intravascular devices at the time that the blood samples for cultures were obtained. In addition, we reviewed the contamination rates for a cohort of patients already hospitalized in the DUMC inpatient medical service, most of whom had indwelling intravascular devices. The bloodstream infection rates among the patients at MNH (n=513) and LCH (n=486) were similar (approximately 28%); the contamination rates at the two hospitals were 1.3% (7/513) and 0.8% (4/486), respectively. Of 54 microorganisms isolated from cultures of blood collected in the DUMC emergency room, 26 (48%) were identified as skin contaminants. Cultures of blood collected in the DUMC emergency room were significantly more likely to yield growth of contaminants than the cultures of blood collected in the emergency rooms at MNH and LCH combined (26/332 versus 11/1,003; P<0.0001) or collected in the DUMC inpatient medical service (26/332 versus 7/283; P<0.01). For the MNH and LCH blood cultures, lower contamination rates were observed when skin was disinfected with isopropyl alcohol plus tincture of iodine rather than isopropyl alcohol plus povidone-iodine. In conclusion, blood culture contamination was minimized in sub-Saharan African hospitals with substantially limited resources through scrupulous attention to aseptic skin cleansing and improved venipuncture techniques. Application of these principles when blood samples for culture are obtained in U.S. hospital emergency rooms should help mitigate blood culture contamination rates and the unnecessary microbiology workup of skin contaminants.

  7. Full waveform hyperspectral LiDAR for terrestrial laser scanning.

    PubMed

    Hakala, Teemu; Suomalainen, Juha; Kaasalainen, Sanna; Chen, Yuwei

    2012-03-26

    We present the design of a full waveform hyperspectral light detection and ranging (LiDAR) and the first demonstrations of its applications in remote sensing. The novel instrument produces a 3D point cloud with spectral backscattered reflectance data. This concept has a significant impact on remote sensing and other fields where target 3D detection and identification is crucial, such as civil engineering, cultural heritage, material processing, or geomorphological studies. As both the geometry and spectral information on the target are available from a single measurement, this technology will extend the scope of imaging spectroscopy into spectral 3D sensing. To demonstrate the potential of the instrument in the remote sensing of vegetation, 3D point clouds with backscattered reflectance and spectral indices are presented for a specimen of Norway spruce.

  8. Full waveform hyperspectral LiDAR for terrestrial laser scanning.

    PubMed

    Hakala, Teemu; Suomalainen, Juha; Kaasalainen, Sanna; Chen, Yuwei

    2012-03-26

    We present the design of a full waveform hyperspectral light detection and ranging (LiDAR) and the first demonstrations of its applications in remote sensing. The novel instrument produces a 3D point cloud with spectral backscattered reflectance data. This concept has a significant impact on remote sensing and other fields where target 3D detection and identification is crucial, such as civil engineering, cultural heritage, material processing, or geomorphological studies. As both the geometry and spectral information on the target are available from a single measurement, this technology will extend the scope of imaging spectroscopy into spectral 3D sensing. To demonstrate the potential of the instrument in the remote sensing of vegetation, 3D point clouds with backscattered reflectance and spectral indices are presented for a specimen of Norway spruce. PMID:22453394

  9. Dynamic LiDAR-NDVI classification of fluvial landscape units

    NASA Astrophysics Data System (ADS)

    Ramírez-Núñez, Carolina; Parrot, Jean-François

    2015-04-01

    The lower basin of the Coatzacoalcos River is a wide floodplain in which, during the wet season, local and major flooding are distinguished. Both types of floods, intermittent and regional, are important in terms of resources; the regional flood sediments enrich the soils of the plains and intermittent floods allow obtaining aquatic resources for subsistence during the heatwave. In the floodplain different abandoned meanders and intermittent streams are quickly colonized by aquatic vegetation. However, from the 1990s, the Coatzacoalcos River floodplain has important topographic changes due to mining, road and bridges construction; erosion and sedimentation requires continuous parcel boundaries along with the increasing demand of channel reparation, embankments, levees and bridges associated to tributaries. NDVI data, LiDAR point cloud and various types of flood simulations taking into account the DTM are used to classify the dynamic landscape units. These units are associated to floods in relation with water resources, agriculture and livestock. In the study area, the first returns of the point cloud allow extracting vegetation strata. The last returns correspond to the bare earth surface, especially in this area with few human settlements. The surface that is not covered by trees or by aquatic vegetation, correspond to crops, pastures and bare soils. The classification is obtained by using the NDVI index coupled with vegetation strata and water bodies. The result shows that 47.96% of the area does not present active vegetation and it includes 31.53% of bare soils. Concerning the active vegetation, pastures, bushes and trees represent respectively 25.59%, 11.14% and 13.25%. The remaining 1.25% is distributed between water bodies with aquatic vegetation, trees and shrubs. Dynamic landscape units' classification represents a tool for monitoring water resources in a fluvial plain. This approach can be also applied to forest management, environmental services and

  10. S-DARS broadcast from inclined, elliptical orbits

    NASA Astrophysics Data System (ADS)

    Briskman, Robert D.; Prevaux, Robert J.

    2004-04-01

    The first Sirius spacecraft was launched on July 1, 2000. Exactly 5 months later, on December 1, the third spacecraft was launched, completing the three satellite S-DARS (Satellite Digital Audio Radio Service) constellation. The three satellites are deployed in inclined, elliptical, geosynchronous orbits, which allow seamless broadcast coverage to mobile users in the contiguous US. Terrestrial broadcast repeaters provide service in urban cores. The system is in operation, providing the first ever S-DARS service. The constellation design results in satellite ground tracks over North America with two satellites always above the equator. High elevation look angles from the mobile ground terminals to the satellites minimize performance degradation due to blockage, foliage attenuation and multi-path. The spacecraft were built by Space Systems/Loral using the 1300 bus modified for operation in high inclination orbits. Each spacecraft was launched using a dedicated Russian Proton booster. The satellite payload is a bent pipe repeater using 7.1 GHz for the uplink and 2.3 GHz for the broadcast transmission. The repeater high-power amplification stage consists of 32 Traveling Wave Tube Amplifiers phase combined to yield a total radio frequency output power of nearly 4 kW at saturated operation. The satellite antennas are mechanically steered to maintain the transmit beam centered on the Contiguous United States and the receive beam centered on the uplink earth station located in Vernon Valley, New Jersey. The satellite payload design and performance are described. The principal spacecraft bus systems are described with emphasis on improvements made for operation in the inclined, elliptical geosynchronous orbits.

  11. Urban agriculture and Anopheles habitats in Dar es Salaam, Tanzania.

    PubMed

    Dongus, Stefan; Nyika, Dickson; Kannady, Khadija; Mtasiwa, Deo; Mshinda, Hassan; Gosoniu, Laura; Drescher, Axel W; Fillinger, Ulrike; Tanner, Marcel; Killeen, Gerry F; Castro, Marcia C

    2009-05-01

    A cross-sectional survey of agricultural areas, combined with routinely monitored mosquito larval information, was conducted in urban Dar es Salaam, Tanzania, to investigate how agricultural and geographical features may influence the presence of Anopheles larvae. Data were integrated into a geographical information systems framework, and predictors of the presence of Anopheles larvae in farming areas were assessed using multivariate logistic regression with independent random effects. It was found that more than 5% of the study area (total size 16.8 km2) was used for farming in backyard gardens and larger open spaces. The proportion of habitats containing Anopheles larvae was 1.7 times higher in agricultural areas compared to other areas (95% confidence interval = 1.56-1.92). Significant geographic predictors of the presence of Anopheles larvae in gardens included location in lowland areas, proximity to river, and relatively impermeable soils. Agriculture-related predictors comprised specific seedbed types, mid-sized gardens, irrigation by wells, as well as cultivation of sugar cane or leafy vegetables. Negative predictors included small garden size, irrigation by tap water, rainfed production and cultivation of leguminous crops or fruit trees. Although there was an increased chance of finding Anopheles larvae in agricultural sites, it was found that breeding sites originated by urban agriculture account for less than a fifth of all breeding sites of malaria vectors in Dar es Salaam. It is suggested that strategies comprising an integrated malaria control effort in malaria-endemic African cities include participatory involvement of farmers by planting shade trees near larval habitats.

  12. 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.

  13. Automatic registration of UAV-borne sequent images and LiDAR data

    NASA Astrophysics Data System (ADS)

    Yang, Bisheng; Chen, Chi

    2015-03-01

    Use of direct geo-referencing data leads to registration failure between sequent images and LiDAR data captured by mini-UAV platforms because of low-cost sensors. This paper therefore proposes a novel automatic registration method for sequent images and LiDAR data captured by mini-UAVs. First, the proposed method extracts building outlines from LiDAR data and images and estimates the exterior orientation parameters (EoPs) of the images with building objects in the LiDAR data coordinate framework based on corresponding corner points derived indirectly by using linear features. Second, the EoPs of the sequent images in the image coordinate framework are recovered using a structure from motion (SfM) technique, and the transformation matrices between the LiDAR coordinate and image coordinate frameworks are calculated using corresponding EoPs, resulting in a coarse registration between the images and the LiDAR data. Finally, 3D points are generated from sequent images by multi-view stereo (MVS) algorithms. Then the EoPs of the sequent images are further refined by registering the LiDAR data and the 3D points using an iterative closest-point (ICP) algorithm with the initial results from coarse registration, resulting in a fine registration between sequent images and LiDAR data. Experiments were performed to check the validity and effectiveness of the proposed method. The results show that the proposed method achieves high-precision robust co-registration of sequent images and LiDAR data captured by mini-UAVs.

  14. 4D Near Real-Time Environmental Monitoring Using Highly Temporal LiDAR

    NASA Astrophysics Data System (ADS)

    Höfle, Bernhard; Canli, Ekrem; Schmitz, Evelyn; Crommelinck, Sophie; Hoffmeister, Dirk; Glade, Thomas

    2016-04-01

    The last decade has witnessed extensive applications of 3D environmental monitoring with the LiDAR technology, also referred to as laser scanning. Although several automatic methods were developed to extract environmental parameters from LiDAR point clouds, only little research has focused on highly multitemporal near real-time LiDAR (4D-LiDAR) for environmental monitoring. Large potential of applying 4D-LiDAR is given for landscape objects with high and varying rates of change (e.g. plant growth) and also for phenomena with sudden unpredictable changes (e.g. geomorphological processes). In this presentation we will report on the most recent findings of the research projects 4DEMON (http://uni-heidelberg.de/4demon) and NoeSLIDE (https://geomorph.univie.ac.at/forschung/projekte/aktuell/noeslide/). The method development in both projects is based on two real-world use cases: i) Surface parameter derivation of agricultural crops (e.g. crop height) and ii) change detection of landslides. Both projects exploit the "full history" contained in the LiDAR point cloud time series. One crucial initial step of 4D-LiDAR analysis is the co-registration over time, 3D-georeferencing and time-dependent quality assessment of the LiDAR point cloud time series. Due to the high amount of datasets (e.g. one full LiDAR scan per day), the procedure needs to be performed fully automatically. Furthermore, the online near real-time 4D monitoring system requires to set triggers that can detect removal or moving of tie reflectors (used for co-registration) or the scanner itself. This guarantees long-term data acquisition with high quality. We will present results from a georeferencing experiment for 4D-LiDAR monitoring, which performs benchmarking of co-registration, 3D-georeferencing and also fully automatic detection of events (e.g. removal/moving of reflectors or scanner). Secondly, we will show our empirical findings of an ongoing permanent LiDAR observation of a landslide (Gresten

  15. Frontiers in Using LiDAR to Analyze Urban Landscape Heterogeneity

    NASA Astrophysics Data System (ADS)

    Singh, Kunwar Krishna Veer

    Light Detection and Ranging (LiDAR) technology has facilitated extraordinary advances in our ability to remotely sense precise details of both built and natural environments. The inherent complexity of urban landscapes and the massive data volumes produced by LiDAR require unique methodological considerations for big data remote sensing over large metropolitan regions. The heterogeneous landscapes of the rapidly urbanizing Charlotte Metropolitan Region of North Carolina provided an ideal testing ground for developing methods of analysis for urban ecosystems over large regional extents, including: (1) fusion of LiDAR digital surface models (DSMs) with Landsat TM imagery to balance spatial resolution, data volume, and mapping accuracy of urban land covers, (2) comparison of LiDAR-derived metrics to fine grain optical imagery -- and their integration -- for detecting forest understory plant invaders, and (3) data reduction techniques for computationally efficient estimation of aboveground woody biomass in urban forests. In Chapter 1, I examined tradeoffs between potential gains in mapping accuracy and computational costs by integrating DSMs (structural and intensity) extracted from LiDAR with TM imagery and evaluating the degree to which TM, LiDAR, and LiDAR-TM fusion data discriminated land covers. I used Maximum Likelihood and Classification Tree algorithms to classify TM data, LiDAR data, and LiDAR-TM fusions. I assessed the relative contributions of LiDAR DSMs to map classification accuracy and identified an optimal spatial resolution of LiDAR DSMs for large area assessments of urban land cover. In Chapter 2, I analyzed combinations of datasets developed from categorized LiDAR-derived variables (Overstory, Understory, Topography, and Overall Vegetation Characteristics) and IKONOS imagery ( Optical) to detect and map the understory plant invader, Ligustrum sinense, using Random Forest (RF) and logistic regression (LR) algorithms, and I assessed the relative

  16. Hospital fundamentals.

    PubMed

    Althausen, Peter L; Hill, Austin D; Mead, Lisa

    2014-07-01

    Under the current system, orthopaedic trauma surgeons must work in some form of hospital setting as our primary service involves treatment of the trauma patient. We must not forget that just as a trauma center cannot exist without our services, we cannot function without their support. As a result, a clear understanding of the balance between physicians and hospitals is paramount. Historical perspective enables physicians and hospital personnel alike to understand the evolution of hospital-physician relationship. This process should be understood upon completion of this chapter. The relationship between physicians and hospitals is becoming increasingly complex and multiple forms of integration exist such as joint ventures, gain sharing, and co-management agreements. For the surgeon to negotiate well, an understanding of hospital governance and the role of the orthopaedic traumatologist is vital to success. An understanding of the value provided by the traumatologist includes all aspects of care including efficiency, availability, cost effectiveness, and research activities. To create effective and sustainable healthcare institutions, physicians and hospitals must be aligned over a sustained period of time. Unfortunately, external forces have eroded the historical basis for the working relationship between physicians and hospitals. Increased competition and reimbursement cuts, coupled with the increasing demands for quality, efficiency, and coordination and the payment changes outlined in healthcare reform, have left many organizations wondering how to best rebuild the relationship. The principal goal for the physician when partnering with a hospital or healthcare entity is to establish a sustainable model of service line management that protects or advances the physician's ability to make impactful improvements in quality of patient care, decreases in healthcare costs, and improvements in process efficiency through evidence-based practices and protocols. PMID

  17. Hospital fundamentals.

    PubMed

    Althausen, Peter L; Hill, Austin D; Mead, Lisa

    2014-07-01

    Under the current system, orthopaedic trauma surgeons must work in some form of hospital setting as our primary service involves treatment of the trauma patient. We must not forget that just as a trauma center cannot exist without our services, we cannot function without their support. As a result, a clear understanding of the balance between physicians and hospitals is paramount. Historical perspective enables physicians and hospital personnel alike to understand the evolution of hospital-physician relationship. This process should be understood upon completion of this chapter. The relationship between physicians and hospitals is becoming increasingly complex and multiple forms of integration exist such as joint ventures, gain sharing, and co-management agreements. For the surgeon to negotiate well, an understanding of hospital governance and the role of the orthopaedic traumatologist is vital to success. An understanding of the value provided by the traumatologist includes all aspects of care including efficiency, availability, cost effectiveness, and research activities. To create effective and sustainable healthcare institutions, physicians and hospitals must be aligned over a sustained period of time. Unfortunately, external forces have eroded the historical basis for the working relationship between physicians and hospitals. Increased competition and reimbursement cuts, coupled with the increasing demands for quality, efficiency, and coordination and the payment changes outlined in healthcare reform, have left many organizations wondering how to best rebuild the relationship. The principal goal for the physician when partnering with a hospital or healthcare entity is to establish a sustainable model of service line management that protects or advances the physician's ability to make impactful improvements in quality of patient care, decreases in healthcare costs, and improvements in process efficiency through evidence-based practices and protocols.

  18. LiDAR improves fire behaviour predictions using a biophysical, mechanistic model

    NASA Astrophysics Data System (ADS)

    Zylstra, Philip; Horsey, Bronwyn; Yebra, Marta; Marselis, Suzanne

    2016-04-01

    Numerous studies have attempted to address the utility of LiDAR as a tool for measuring fuel inputs to fire behaviour models, however the direct effect of this approach on fire behaviour prediction requires quantification. We used a biophysical, mechanistic model validated for eucalypt forest in SE Australia to assess the improvement in prediction accuracy afforded using LiDAR-derived inputs. The accuracy of modelling with these inputs was compared to modelling using detailed site-specific field surveys of a dry sclerophyll forest to represent the highest standard of inputs, and values derived from desktop-available community-wide descriptors to represent baseline inputs. Use of LiDAR significantly improved on baseline predictions and enabled site-specific decision making across the study area. When used with an appropriate model, LiDAR can facilitate improved decision-making in regard to forest fire behaviour.

  19. 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.

  20. Hospital marketing.

    PubMed

    Carter, Tony

    2003-01-01

    This article looks at a prescribed academic framework for various criteria that serve as a checklist for marketing performance that can be applied to hospital marketing organizations. These guidelines are drawn from some of Dr. Noel Capon of Columbia University's book Marketing Management in the 21st Century and applied to actual practices of hospital marketing organizations. In many ways this checklist can act as a "marketing" balanced scorecard to verify performance effectiveness and develop opportunities for innovation.

  1. Hospital philanthropy.

    PubMed

    Smith, Dean G; Clement, Jan P

    2013-01-01

    It remains an open question whether hospital spending on fundraising efforts to garner philanthropy is a good use of funds. Research and industry reports provide conflicting results. We describe the accounting and data challenges in analysis of hospital philanthropy, which include measurement of donations, measurement of fundraising expenses, and finding the relationships among organizations where these cash flows occur. With these challenges, finding conflicting results is not a surprise. PMID:23614267

  2. Hospital marketing.

    PubMed

    Carter, Tony

    2003-01-01

    This article looks at a prescribed academic framework for various criteria that serve as a checklist for marketing performance that can be applied to hospital marketing organizations. These guidelines are drawn from some of Dr. Noel Capon of Columbia University's book Marketing Management in the 21st Century and applied to actual practices of hospital marketing organizations. In many ways this checklist can act as a "marketing" balanced scorecard to verify performance effectiveness and develop opportunities for innovation. PMID:14753323

  3. 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.

  4. 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.

  5. Aboveground Biomass Modeling from Field and LiDAR Data in Brazilian Amazon Tropical Rain Forest

    NASA Astrophysics Data System (ADS)

    Silva, C. A.; Hudak, A. T.; Vierling, L. A.; Keller, M. M.; Klauberg Silva, C. K.

    2015-12-01

    Tropical forests are an important component of global carbon stocks, but tropical forest responses to climate change are not sufficiently studied or understood. Among remote sensing technologies, airborne LiDAR (Light Detection and Ranging) may be best suited for quantifying tropical forest carbon stocks. Our objective was to estimate aboveground biomass (AGB) using airborne LiDAR and field plot data in Brazilian tropical rain forest. Forest attributes such as tree density, diameter at breast height, and heights were measured at a combination of square plots and linear transects (n=82) distributed across six different geographic zones in the Amazon. Using previously published allometric equations, tree AGB was computed and then summed to calculate total AGB at each sample plot. LiDAR-derived canopy structure metrics were also computed at each sample plot, and random forest regression modelling was applied to predict AGB from selected LiDAR metrics. The LiDAR-derived AGB model was assessed using the random forest explained variation, adjusted coefficient of determination (Adj. R²), root mean square error (RMSE, both absolute and relative) and BIAS (both absolute and relative). Our findings showed that the 99th percentile of height and height skewness were the best LiDAR metrics for AGB prediction. The AGB model using these two best predictors explained 59.59% of AGB variation, with an Adj. R² of 0.92, RMSE of 33.37 Mg/ha (20.28%), and bias of -0.69 (-0.42%). This study showed that LiDAR canopy structure metrics can be used to predict AGC stocks in Tropical Forest with acceptable precision and accuracy. Therefore, we conclude that there is good potential to monitor carbon sequestration in Brazilian Tropical Rain Forest using airborne LiDAR data, large field plots, and the random forest algorithm.

  6. Change Detection from differential airborne LiDAR using a weighted Anisotropic Iterative Closest Point Algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Kusari, A.; Glennie, C. L.; Oskin, M. E.; Hinojosa-Corona, A.; Borsa, A. A.; Arrowsmith, R.

    2013-12-01

    Differential LiDAR (Light Detection and Ranging) from repeated surveys has recently emerged as an effective tool to measure three-dimensional (3D) change for applications such as quantifying slip and spatially distributed warping associated with earthquake ruptures, and examining the spatial distribution of beach erosion after hurricane impact. Currently, the primary method for determining 3D change is through the use of the iterative closest point (ICP) algorithm and its variants. However, all current studies using ICP have assumed that all LiDAR points in the compared point clouds have uniform accuracy. This assumption is simplistic given that the error for each LiDAR point is variable, and dependent upon highly variable factors such as target range, angle of incidence, and aircraft trajectory accuracy. Therefore, to rigorously determine spatial change, it would be ideal to model the random error for every LiDAR observation in the differential point cloud, and use these error estimates as apriori weights in the ICP algorithm. To test this approach, we implemented a rigorous LiDAR observation error propagation method to generate estimated random error for each point in a LiDAR point cloud, and then determine 3D displacements between two point clouds using an anistropic weighted ICP algorithm. The algorithm was evaluated by qualitatively and quantitatively comparing post earthquake slip estimates from the 2010 El Mayor-Cucapah Earthquake between a uniform weight and anistropically weighted ICP algorithm, using pre-event LiDAR collected in 2006 by Instituto Nacional de Estadística y Geografía (INEGI), and post-event LiDAR collected by The National Center for Airborne Laser Mapping (NCALM).

  7. 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.

  8. 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.

  9. 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.

  10. Classification of LiDAR Data with Point Based Classification Methods

    NASA Astrophysics Data System (ADS)

    Yastikli, N.; Cetin, Z.

    2016-06-01

    LiDAR is one of the most effective systems for 3 dimensional (3D) data collection in wide areas. Nowadays, airborne LiDAR data is used frequently in various applications such as object extraction, 3D modelling, change detection and revision of maps with increasing point density and accuracy. The classification of the LiDAR points is the first step of LiDAR data processing chain and should be handled in proper way since the 3D city modelling, building extraction, DEM generation, etc. applications directly use the classified point clouds. The different classification methods can be seen in recent researches and most of researches work with the gridded LiDAR point cloud. In grid based data processing of the LiDAR data, the characteristic point loss in the LiDAR point cloud especially vegetation and buildings or losing height accuracy during the interpolation stage are inevitable. In this case, the possible solution is the use of the raw point cloud data for classification to avoid data and accuracy loss in gridding process. In this study, the point based classification possibilities of the LiDAR point cloud is investigated to obtain more accurate classes. The automatic point based approaches, which are based on hierarchical rules, have been proposed to achieve ground, building and vegetation classes using the raw LiDAR point cloud data. In proposed approaches, every single LiDAR point is analyzed according to their features such as height, multi-return, etc. then automatically assigned to the class which they belong to. The use of un-gridded point cloud in proposed point based classification process helped the determination of more realistic rule sets. The detailed parameter analyses have been performed to obtain the most appropriate parameters in the rule sets to achieve accurate classes. The hierarchical rule sets were created for proposed Approach 1 (using selected spatial-based and echo-based features) and Approach 2 (using only selected spatial-based features

  11. Potential and limit of LiDAR data for earthquake recurrence characterization

    NASA Astrophysics Data System (ADS)

    Zielke, Olaf

    2013-04-01

    The characterization of earthquake (EQ) recurrence --assessing timing and size of past EQs along a given fault (section)-- has proven difficult, largely due the relatively short time span that is covered by instrumental seismic observations. While major EQs along a given fault are inferred to occur roughly on centennial to millennial time scales, seismographs to record them emerged little more than 100 years ago. Thus, recurrence of major EQs has essentially not yet been observed instrumentally. Stratigraphic and geomorphic evidence is used instead to describe and constrain recurrence of surface rupturing EQs. In the 1980s, analysis of such data sets culminated in the formulation of now classical EQ recurrence models. The debate about the correctness and thus applicability of these in part contradicting models is still ongoing. Over the last 10 years or so Light Detection and Ranging (LiDAR) technology became available to paleoseismic and tectono-geomorphic investigations. High spatial resolution, precision, and accuracy --the key features of LiDAR data-- revealed details in the tectono-geomorphic record that could not be resolved previously by field investigation or air photo analysis. As a result LiDAR data sets contributed and continues to contribute to improvements in the recurrence characterization of (surface rupturing) EQs. Here, I will present an overview on LiDAR data implementation in paleoseismic and tectono-geomorphic studies, including trench-based LiDAR, terrestrial LiDAR, and airborne LiDAR and I will discuss the impact of LiDAR data on constraining EQ recurrence characteristics as well as their relation to the classical EQ recurrence models. Additionally, I will discuss the intrinsic limits (that even LiDAR data cannot overcome) that arise when investigating geomorphic and stratigraphic evidence for EQ recurrence characterization. The natural complexity of the rupture process itself and its imprint on the analyzed data sets puts an unavoidable limit

  12. Quantifying Forest Carbon and Structure with Terrestrial LiDAR

    NASA Astrophysics Data System (ADS)

    Stovall, A. E.; Shugart, H. H., Jr.

    2014-12-01

    Current rising atmospheric CO2 concentrations are a major concern with significant global ramifications, however, of the carbon (C) fluxes that are known to occur on Earth, the terrestrial sink has the greatest amount of uncertainty. Improved monitoring of forest cover and change is required for reducing emissions from deforestation and forest degradation (REDD). We determine C storage from volume measurements with a high-precision Terrestrial Laser Scanner (TLS), substantially improving current standard ground validation techniques. This technology is utilized on several 30 m x 30 m plots in a Virginia temperate forest. Aboveground C is calculated on each of the study sites with commonly used allometric equations to offer a realistic comparison of field-based estimations to TLS-derived methods. The TLS and aerial LiDAR point cloud data are compared via the development of canopy height models at the plot scale. The novel method of point cloud voxelization is applied to our TLS data in order to produce detailed volumetric calculations in these complex forest ecosystems. Statistical output from the TLS data allows us to resolve and compare forest structure on scales from the individual plot to the entire forest landscape. The estimates produced from this research will be used to inform more widely available remote sensing datasets provided by NASA's Landsat satellites, significantly reducing the uncertainty of the terrestrial C cycle in temperate forests. Preliminary findings corroborate previous research, suggesting the potential for highly detailed monitoring of forest C storage as defined by the REDD initiative and analysis of complex ecosystem structure.

  13. Homicide of children in Dar es Salaam, Tanzania, 2005

    PubMed Central

    Outwater, Anne; Mgaya, Edward; Campbell, Jacquelyn C.; Becker, Stan; Kinabo, Linna; Menick, Daniel Mbassa

    2014-01-01

    Background Although data are sparse, it has been estimated that the highest rates of homicide death amongst children are in Africa. Little information is available on ages 0 -< 15 years. No reliable quantitative surveillance analysis of neonaticide (killed at less than one week) has been done. Methods A Violent Death Survey following WHO/CDC Guidelines was completed in Dar es Salaam region, Tanzania (DSM) (population 2.845 million) in 2005. Qualitative and quantitative data were gathered and analyzed using mixed methods techniques. Results The overall age adjusted rate of discarded and killed children in DSM was 2.05. The rate of neonaticide was 27.7 per 100,000) while the rate of homicide incidence for children > one day was Discussion The overall estimated homicide rate for Africa of children under age 15 was 4.53 per 100,000, whereas. The estimated global rate is 1.7 per 100,000 closer to DSM‘s rate. The results in DSM show that broad age groupings such as ” <1 year” or “0–4 years” or “0 – <15 years” may mask a high incidence of neonaticide and an otherwise low incidence of murdered children. The print media provided good in-depth coverage for a few cases but it is not known if the reported cases are representative. Conclusion Eighty percent of homicides of children in DSM are neonaticides. Since it is believed that the forces behind neonaticide are fundamentally different than homicides of older children, it is suggested that data of future surveys be parsed to include neonates, until the phenomenon is more clearly understood and addressed. Further understanding of the mother and father of the deceased is needed. Continued surveillance data collection is important to expand the sample size. PMID:22066333

  14. Improved estimates of forest vegetation structure and biomass with a LiDAR-optimized sampling design

    NASA Astrophysics Data System (ADS)

    Hawbaker, Todd J.; Keuler, Nicholas S.; Lesak, Adrian A.; Gobakken, Terje; Contrucci, Kirk; Radeloff, Volker C.

    2009-06-01

    LiDAR data are increasingly available from both airborne and spaceborne missions to map elevation and vegetation structure. Additionally, global coverage may soon become available with NASA's planned DESDynI sensor. However, substantial challenges remain to using the growing body of LiDAR data. First, the large volumes of data generated by LiDAR sensors require efficient processing methods. Second, efficient sampling methods are needed to collect the field data used to relate LiDAR data with vegetation structure. In this paper, we used low-density LiDAR data, summarized within pixels of a regular grid, to estimate forest structure and biomass across a 53,600 ha study area in northeastern Wisconsin. Additionally, we compared the predictive ability of models constructed from a random sample to a sample stratified using mean and standard deviation of LiDAR heights. Our models explained between 65 to 88% of the variability in DBH, basal area, tree height, and biomass. Prediction errors from models constructed using a random sample were up to 68% larger than those from the models built with a stratified sample. The stratified sample included a greater range of variability than the random sample. Thus, applying the random sample model to the entire population violated a tenet of regression analysis; namely, that models should not be used to extrapolate beyond the range of data from which they were constructed. Our results highlight that LiDAR data integrated with field data sampling designs can provide broad-scale assessments of vegetation structure and biomass, i.e., information crucial for carbon and biodiversity science.

  15. Estimating FPAR of maize canopy using airborne discrete-return LiDAR data.

    PubMed

    Luo, Shezhou; Wang, Cheng; Xi, Xiaohuan; Pan, Feifei

    2014-03-10

    The fraction of absorbed photosynthetically active radiation (FPAR) is a key parameter for ecosystem modeling, crop growth monitoring and yield prediction. Ground-based FPAR measurements are time consuming and labor intensive. Remote sensing provides an alternative method to obtain repeated, rapid and inexpensive estimates of FPAR over large areas. LiDAR is an active remote sensing technology and can be used to extract accurate canopy structure parameters. A method to estimating FPAR of maize from airborne discrete-return LiDAR data was developed and tested in this study. The raw LiDAR point clouds were processed to separate ground returns from vegetation returns using a filter method over a maize field in the Heihe River Basin, northwest China. The fractional cover (fCover) of maize canopy was computed using the ratio of canopy return counts or intensity sums to the total of returns or intensities. FPAR estimation models were established based on linear regression analysis between the LiDAR-derived fCover and the field-measured FPAR (R(2) = 0.90, RMSE = 0.032, p < 0.001). The reliability of the constructed regression model was assessed using the leave-one-out cross-validation procedure and results show that the regression model is not overfitting the data and has a good generalization capability. Finally, 15 independent field-measured FPARs were used to evaluate accuracy of the LiDAR-predicted FPARs and results show that the LiDAR-predicted FPAR has a high accuracy (R(2) = 0.89, RMSE = 0.034). In summary, this study suggests that the airborne discrete-return LiDAR data could be adopted to accurately estimate FPAR of maize.

  16. 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.

  17. Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale.

    PubMed

    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

  18. Estimation of effective plant area index for South Korean forests using LiDAR system.

    PubMed

    Kwak, Doo-Ahn; Lee, Woo-Kyun; Kafatos, Menas; Son, Yowhan; Cho, Hyun-Kook; Lee, Seung-Ho

    2010-07-01

    Light Detection and Ranging (LiDAR) systems can be used to estimate both vertical and horizontal forest structure. Woody components, the leaves of trees and the understory can be described with high precision, using geo-registered 3D-points. Based on this concept, the Effective Plant Area Indices (PAI(e)) for areas of Korean Pine (Pinus koraiensis), Japanese Larch (Larix leptolepis) and Oak (Quercus spp.) were estimated by calculating the ratio of intercepted and incident LIDAR laser rays for the canopies of the three forest types. Initially, the canopy gap fraction (G ( LiDAR )) was generated by extracting the LiDAR data reflected from the canopy surface, or inner canopy area, using k-means statistics. The LiDAR-derived PAI(e) was then estimated by using G ( LIDAR ) with the Beer-Lambert law. A comparison of the LiDAR-derived and field-derived PAI(e) revealed the coefficients of determination for Korean Pine, Japanese Larch and Oak to be 0.82, 0.64 and 0.59, respectively. These differences between field-based and LIDAR-based PAI(e) for the different forest types were attributed to the amount of leaves and branches in the forest stands. The absence of leaves, in the case of both Larch and Oak, meant that the LiDAR pulses were only reflected from branches. The probability that the LiDAR pulses are reflected from bare branches is low as compared to the reflection from branches with a high leaf density. This is because the size of the branch is smaller than the resolution across and along the 1 meter LIDAR laser track. Therefore, a better predictive accuracy would be expected for the model if the study would be repeated in late spring when the shoots and leaves of the deciduous trees begin to appear.

  19. Diversity arrays technology (DArT) for high-throughput profiling of the hexaploid wheat genome.

    PubMed

    Akbari, Mona; Wenzl, Peter; Caig, Vanessa; Carling, Jason; Xia, Ling; Yang, Shiying; Uszynski, Grzegorz; Mohler, Volker; Lehmensiek, Anke; Kuchel, Haydn; Hayden, Mathew J; Howes, Neil; Sharp, Peter; Vaughan, Peter; Rathmell, Bill; Huttner, Eric; Kilian, Andrzej

    2006-11-01

    Despite a substantial investment in the development of panels of single nucleotide polymorphism (SNP) markers, the simple sequence repeat (SSR) technology with a limited multiplexing capability remains a standard, even for applications requiring whole-genome information. Diversity arrays technology (DArT) types hundreds to thousands of genomic loci in parallel, as previously demonstrated in a number diploid plant species. Here we show that DArT performs similarly well for the hexaploid genome of bread wheat (Triticum aestivum L.). The methodology previously used to generate DArT fingerprints of barley also generated a large number of high-quality markers in wheat (99.8% allele-calling concordance and approximately 95% call rate). The genetic relationships among bread wheat cultivars revealed by DArT coincided with knowledge generated with other methods, and even closely related cultivars could be distinguished. To verify the Mendelian behaviour of DArT markers, we typed a set of 90 Cranbrook x Halberd doubled haploid lines for which a framework (FW) map comprising a total of 339 SSR, restriction fragment length polymorphism (RFLP) and amplified fragment length polymorphism (AFLP) markers was available. We added an equal number of DArT markers to this data set and also incorporated 71 sequence tagged microsatellite (STM) markers. A comparison of logarithm of the odds (LOD) scores, call rates and the degree of genome coverage indicated that the quality and information content of the DArT data set was comparable to that of the combined SSR/RFLP/AFLP data set of the FW map. PMID:17033786

  20. Hospitality Management.

    ERIC Educational Resources Information Center

    College of the Canyons, Valencia, CA.

    A project was conducted at College of the Canyons (Valencia, California) to initiate a new 2-year hospitality program with career options in hotel or restaurant management. A mail and telephone survey of area employers in the restaurant and hotel field demonstrated a need for, interest in, and willingness to provide internships for such a program.…

  1. Academic Hospitality

    ERIC Educational Resources Information Center

    Phipps, Alison; Barnett, Ronald

    2007-01-01

    Academic hospitality is a feature of academic life. It takes many forms. It takes material form in the hosting of academics giving papers. It takes epistemological form in the welcome of new ideas. It takes linguistic form in the translation of academic work into other languages, and it takes touristic form through the welcome and generosity with…

  2. Spinning a laser web: predicting spider distributions using LiDAR.

    PubMed

    Vierling, K T; Bässler, C; Brandl, R; Vierling, L A; Weiss, I; Müller, J

    2011-03-01

    LiDAR remote sensing has been used to examine relationships between vertebrate diversity and environmental characteristics, but its application to invertebrates has been limited. Our objectives were to determine whether LiDAR-derived variables could be used to accurately describe single-species distributions and community characteristics of spiders in remote forested and mountainous terrain. We collected over 5300 spiders across multiple transects in the Bavarian National Park (Germany) using pitfall traps. We examined spider community characteristics (species richness, the Shannon index, the Simpson index, community composition, mean body size, and abundance) and single-species distribution and abundance with LiDAR variables and ground-based measurements. We used the R2 and partial R2 provided by variance partitioning to evaluate the predictive power of LiDAR-derived variables compared to ground measurements for each of the community characteristics. The total adjusted R2 for species richness, the Shannon index, community species composition, and body size had a range of 25-57%. LiDAR variables and ground measurements both contributed >80% to the total predictive power. For species composition, the explained variance was approximately 32%, which was significantly greater than expected by chance. The predictive power of LiDAR-derived variables was comparable or superior to that of the ground-based variables for examinations of single-species distributions, and it explained up to 55% of the variance. The predictability of species distributions was higher for species that had strong associations with shade in open-forest habitats, and this niche position has been well documented across the European continent for spider species. The similar statistical performance between LiDAR and ground-based measures at our field sites indicated that deriving spider community and species distribution information using LiDAR data can provide not only high predictive power at

  3. 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

  4. Spinning a laser web: predicting spider distributions using LiDAR.

    PubMed

    Vierling, K T; Bässler, C; Brandl, R; Vierling, L A; Weiss, I; Müller, J

    2011-03-01

    LiDAR remote sensing has been used to examine relationships between vertebrate diversity and environmental characteristics, but its application to invertebrates has been limited. Our objectives were to determine whether LiDAR-derived variables could be used to accurately describe single-species distributions and community characteristics of spiders in remote forested and mountainous terrain. We collected over 5300 spiders across multiple transects in the Bavarian National Park (Germany) using pitfall traps. We examined spider community characteristics (species richness, the Shannon index, the Simpson index, community composition, mean body size, and abundance) and single-species distribution and abundance with LiDAR variables and ground-based measurements. We used the R2 and partial R2 provided by variance partitioning to evaluate the predictive power of LiDAR-derived variables compared to ground measurements for each of the community characteristics. The total adjusted R2 for species richness, the Shannon index, community species composition, and body size had a range of 25-57%. LiDAR variables and ground measurements both contributed >80% to the total predictive power. For species composition, the explained variance was approximately 32%, which was significantly greater than expected by chance. The predictive power of LiDAR-derived variables was comparable or superior to that of the ground-based variables for examinations of single-species distributions, and it explained up to 55% of the variance. The predictability of species distributions was higher for species that had strong associations with shade in open-forest habitats, and this niche position has been well documented across the European continent for spider species. The similar statistical performance between LiDAR and ground-based measures at our field sites indicated that deriving spider community and species distribution information using LiDAR data can provide not only high predictive power at

  5. Specular and diffuse object extraction from a LiDAR derived Digital Surface Model (DSM)

    NASA Astrophysics Data System (ADS)

    Saraf, N. M.; Hamid, J. R. A.; Kamaruddin, M. H.

    2014-02-01

    This paper intents to investigate the indifferent behaviour quantitatively of target objects of interest due to specular and diffuse reflectivity based on generated LiDAR DSM of the study site in Ampang, Kuala Lumpur. The LiDAR data to be used was initially checked for its reliability and accuracy. The point cloud LiDAR data was converted to raster to allow grid analysis of the next process of generating the DSM and DTM. Filtering and masking were made removing the features of interest (i.e. building and tree) and other unwanted above surface features. A normalised DSM and object segmentation approach were conducted on the trees and buildings separately. Error assessment and findings attained were highlighted and documented. The result of LiDAR verification certified that the data is reliable and useable. The RMSE obtained is within the tolerance value of horizontal and vertical accuracy (x, y, z) i.e. 0.159 m, 0.211 m 0.091 m respectively. Building extraction inclusive of roof top based on slope and contour analysis undertaken indicate the capability of the approach while single tree extraction through aspect analysis appears to preserve the accuracy of the extraction accordingly. The paper has evaluated the suitable methods of extracting non-ground features and the effective segmentation of the LiDAR data.

  6. Detection of fault structures with airborne LiDAR point-cloud data

    NASA Astrophysics Data System (ADS)

    Chen, Jie; Du, Lei

    2015-08-01

    The airborne LiDAR (Light Detection And Ranging) technology is a new type of aerial earth observation method which can be used to produce high-precision DEM (Digital Elevation Model) quickly and reflect ground surface information directly. Fault structure is one of the key forms of crustal movement, and its quantitative description is the key to the research of crustal movement. The airborne LiDAR point-cloud data is used to detect and extract fault structures automatically based on linear extension, elevation mutation and slope abnormal characteristics. Firstly, the LiDAR point-cloud data is processed to filter out buildings, vegetation and other non-surface information with the TIN (Triangulated Irregular Network) filtering method and Burman model calibration method. TIN and DEM are made from the processed data sequentially. Secondly, linear fault structures are extracted based on dual-threshold method. Finally, high-precision DOM (Digital Orthophoto Map) and other geological knowledge are used to check the accuracy of fault structure extraction. An experiment is carried out in Beiya Village of Yunnan Province, China. With LiDAR technology, results reveal that: the airborne LiDAR point-cloud data can be utilized to extract linear fault structures accurately and automatically, measure information such as height, width and slope of fault structures with high precision, and detect faults in areas with vegetation coverage effectively.

  7. Flow Characteristics of Tidewater Glaciers in Greenland and Alaska using Ground-Based LiDAR

    NASA Astrophysics Data System (ADS)

    Finnegan, D. C.; Stearns, L. A.; Hamilton, G. S.; O'Neel, S.

    2010-12-01

    LiDAR scanning systems have been employed to characterize and quantify multi-temporal glacier and ice sheet changes for nearly three decades. Until recently, LiDAR scanning systems were limited to airborne and space-based platforms which come at a significant cost to deploy and are limited in spatial and temporal sampling capabilities necessary to compare with in-situ field measurements. Portable ground-based LiDAR scanning systems are now being used as a glaciological tool. We discuss research efforts to employ ground-based near-infrared LiDAR systems at two differing tidewater glacier systems in the spring of 2009; Helheim Glacier in southeast Greenland and Columbia Glacier in southeast Alaska. Preliminary results allow us to characterize short term displacement rates and detailed observations of calving processes. These results highlight the operational limitations and capabilities of commercially available LiDAR systems, and allow us to identify optimal operating characteristics for monitoring small to large-scale tidewater glaciers in near real-time. Furthermore, by identifying the operational limitations of these sensors it allows for optimal design characteristics of new sensors necessary to meet ground-based calibration and validation requirements of ongoing scientific missions.

  8. Octree-based segmentation for terrestrial LiDAR point cloud data in industrial applications

    NASA Astrophysics Data System (ADS)

    Su, Yun-Ting; Bethel, James; Hu, Shuowen

    2016-03-01

    Automated and efficient algorithms to perform segmentation of terrestrial LiDAR data is critical for exploitation of 3D point clouds, where the ultimate goal is CAD modeling of the segmented data. In this work, a novel segmentation technique is proposed, starting with octree decomposition to recursively divide the scene into octants or voxels, followed by a novel split and merge framework that uses graph theory and a series of connectivity analyses to intelligently merge components into larger connected components. The connectivity analysis, based on a combination of proximity, orientation, and curvature connectivity criteria, is designed for the segmentation of pipes, vessels, and walls from terrestrial LiDAR data of piping systems at industrial sites, such as oil refineries, chemical plants, and steel mills. The proposed segmentation method is exercised on two terrestrial LiDAR datasets of a steel mill and a chemical plant, demonstrating its ability to correctly reassemble and segregate features of interest.

  9. 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.

  10. Using 3D visual tools with LiDAR for environmental outreach

    NASA Astrophysics Data System (ADS)

    Glenn, N. F.; Mannel, S.; Ehinger, S.; Moore, C.

    2009-12-01

    The project objective is to develop visualizations using light detection and ranging (LiDAR) data and other data sources to increase community understanding of remote sensing data for earth science. These data are visualized using Google Earth and other visualization methods. Final products are delivered to K-12, state, and federal agencies to share with their students and community constituents. Once our partner agencies were identified, we utilized a survey method to better understand their technological abilities and use of visualization products. The final multimedia products include a visualization of LiDAR and well data for water quality mapping in a southeastern Idaho watershed; a tour of hydrologic points of interest in southeastern Idaho visited by thousands of people each year, and post-earthquake features near Borah Peak, Idaho. In addition to the customized multimedia materials, we developed tutorials to encourage our partners to utilize these tools with their own LiDAR and other scientific data.

  11. [Analysis of an Air Pollution Process Using LiDAR in Nanjing, Spring of 2014].

    PubMed

    Bao, Qing; He, Jun-liang; Zha, Yong; Cheng, Feng; Li, Qian-nan

    2015-04-01

    Based on environmental monitoring data, meteorological data and the results of numerical simulation, a typical air pollution process in Nanjing, from 26th May to 1st June, 2014 was deeply analyzed combining aerosol extinction coefficient derived from LiDAR system. Experimental results showed that the entire pollution process was affected by both local pollution and exogenous inputs including dust and smoke. Meteorological factors played a significant role in the generation and elimination of pollutants. Low pressure and temperature inversion also hindered the diffusion of pollutants, while strong rainfall terminated the pollution process. During the pollution, the height of atmospheric boundary layer was lower than normal situation and changed little during the pollution period, which provided a poor diffusion condition for pollutants. LiDAR could accurately detect aerosol vertical structure which was able to capture the temporal and spatial variation of pollutant distributions. Therefore, LiDAR can be of great significance for the atmospheric pollution monitoring. PMID:26164889

  12. Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

    SciTech Connect

    Danny L. Anderson

    2012-05-01

    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 a 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.

  13. 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). PMID:20182905

  14. Reconstruction and analysis of a deciduous sapling using digital photographs or terrestrial-LiDAR technology

    PubMed Central

    Delagrange, Sylvain; Rochon, Pascal

    2011-01-01

    Background and Aims To meet the increasing need for rapid and non-destructive extraction of canopy traits, two methods were used and compared with regard to their accuracy in estimatating 2-D and 3-D parameters of a hybrid poplar sapling. Methods The first method consisted of the analysis of high definition photographs in Tree Analyser (TA) software (PIAF-INRA/Kasetsart University). TA allowed the extraction of individual traits using a space carving approach. The second method utilized 3-D point clouds acquired from terrestrial light detection and ranging (T-LiDAR) scans. T-LiDAR scans were performed on trees without leaves to reconstruct the lignified structure of the sapling. From this skeleton, foliage was added using simple modelling rules extrapolated from field measurements. Validation of the estimated dimension and the accuracy of reconstruction was then achieved by comparison with an empirical data set. Key Results TA was found to be slightly less precise than T-LiDAR for estimating tree height, canopy height and mean canopy diameter, but for 2-D traits both methods were, however, fully satisfactory. TA tended to over-estimate total leaf area (error up to 50 %), but better estimates were obtained by reducing the size of the voxels used for calculations. In contrast, T-LiDAR estimated total leaf area with an error of <6 %. Finally, both methods led to an over-estimation of canopy volume. With respect to this trait, T-LiDAR (14·5 % deviation) greatly surpassed the accuracy of TA (up to 50 % deviation), even if the voxels used were reduced in size. Conclusions Taking into account their magnitude of data acquisition and analysis and their accuracy in trait estimations, both methods showed contrasting potential future uses. Specifically, T-LiDAR is a particularly promising tool for investigating the development of large perennial plants, by itself or in association with plant modelling. PMID:21515607

  15. LiDAR remote sensing observations for forest assessment and recovery responses following disturbance

    NASA Astrophysics Data System (ADS)

    Rosette, J.; Suárez, J.; Fonweben, J.; North, P.

    2013-12-01

    LiDAR data covering 400 km2 in the Cowal and Trossacs Forest District, Scotland, U.K., were used to provide a low cost solution to update the database of public forests and to produce multi-scale cartographic products for supporting management decisions in the event of forest disturbance such as infestation or wind damage. All parameter estimates were directly obtained from the LiDAR data without the necessity of field calibration. This was achieved using a hybrid approach integrating current stand models for Sitka spruce (Picea sitchensis bong. Carr) and LiDAR analysis. More conventional field methods offer percentage sampling, permitting only a proportion of stands to be surveyed each year and aiming to represent stand-level conditions. The use of LiDAR is advantageous in allowing a complete observation-based assessment throughout the forest and greatly-improved spatial representation of important forest parameters. Time-series analysis was performed using LiDAR data collected in the past 10 years. This analysis allowed us to establish growth trajectories in the forest stands, automatically discriminating areas of growth, those whose growth had been affected by disease and the occurrence of windthrow gaps. The results were compared to the cartography produced by the Forest District after a severe wind storm that affected the area in 2012. This analysis showed the ability of LiDAR to create a more precise location and extent of catastrophic damage and windthrow gaps. In addition, once windthrow has occurred, progression of further damage in existing canopy gaps can be observed. This approach additionally allows the impact of disease on forest growth and subsequent recovery response to be monitored.

  16. 'Dar Kenn Ghal Sahhtek'--an eating disorder and obesity service in Malta.

    PubMed

    Aquilina, Francesca Falzon; Grech, Anton; Zerafa, Darleen; Agius, Mark; Voon, Valerie

    2015-09-01

    This paper will describe the incidence of eating disorders, with particular focus on obesity and binge eating, within the Island of Malta. The development of and 'Dar Kenn Ghal Sahhtek', the first centre for eating disorders in Malta will then be recounted, and the effective therapeutic interventions provided in it will be described. One important function of this unit is the treatment of excessive obesity. Some epidemiological data on the Obese Patients in DKS, relating to the incidence of Binge Eating Disorder in the DKS patient group will be given. This data was collected during a collaboritive research project between the Psychiatry Department of Cambridge University and 'Dar Kenn Ghal Sahhtek'.

  17. Direct injection into the IsoDAR Cyclotron using a RFQ

    NASA Astrophysics Data System (ADS)

    Axani, Spencer; IsoDAR Collaboration

    2015-04-01

    Beginning in the 1970s, the use of Radio Frequency Quadrupoles (RFQs) has been pervasive in linear accelerators in order to accelerate, bunch, and separate ion species. Current research suggests this may be an ideal way to inject a low energy H2+ beam axially into a cyclotron. The IsoDAR (Isotope Decay At Rest) experiment aims to implement this injection system in order to achieve higher Low Energy Beam Transport (LEBT) efficiencies and ultimately construct a novel compact neutrino factory to test the hypothesis of sterile neutrinos. This talk will focus on the research and development needed to implement a RFQ into the IsoDAR experiment.

  18. DArT markers: diversity analyses and mapping in Sorghum bicolor

    PubMed Central

    Mace, Emma S; Xia, Ling; Jordan, David R; Halloran, Kirsten; Parh, Dipal K; Huttner, Eric; Wenzl, Peter; Kilian, Andrzej

    2008-01-01

    Background The sequential nature of gel-based marker systems entails low throughput and high costs per assay. Commonly used marker systems such as SSR and SNP are also dependent on sequence information. These limitations result in high cost per data point and significantly limit the capacity of breeding programs to obtain sufficient return on investment to justify the routine use of marker-assisted breeding for many traits and particularly quantitative traits. Diversity Arrays Technology (DArT™) is a cost effective hybridisation-based marker technology that offers a high multiplexing level while being independent of sequence information. This technology offers sorghum breeding programs an alternative approach to whole-genome profiling. We report on the development, application, mapping and utility of DArT™ markers for sorghum germplasm. Results A genotyping array was developed representing approximately 12,000 genomic clones using PstI+BanII complexity with a subset of clones obtained through the suppression subtractive hybridisation (SSH) method. The genotyping array was used to analyse a diverse set of sorghum genotypes and screening a Recombinant Inbred Lines (RIL) mapping population. Over 500 markers detected variation among 90 accessions used in a diversity analysis. Cluster analysis discriminated well between all 90 genotypes. To confirm that the sorghum DArT markers behave in a Mendelian manner, we constructed a genetic linkage map for a cross between R931945-2-2 and IS 8525 integrating DArT and other marker types. In total, 596 markers could be placed on the integrated linkage map, which spanned 1431.6 cM. The genetic linkage map had an average marker density of 1/2.39 cM, with an average DArT marker density of 1/3.9 cM. Conclusion We have successfully developed DArT markers for Sorghum bicolor and have demonstrated that DArT provides high quality markers that can be used for diversity analyses and to construct medium-density genetic linkage maps. The

  19. 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

  20. 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

  1. Airborne hyperspectral and LiDAR data integration for weed detection

    NASA Astrophysics Data System (ADS)

    Tamás, János; Lehoczky, Éva; Fehér, János; Fórián, Tünde; Nagy, Attila; Bozsik, Éva; Gálya, Bernadett; Riczu, Péter

    2014-05-01

    Agriculture uses 70% of global available fresh water. However, ca. 50-70% of water used by cultivated plants, the rest of water transpirated by the weeds. Thus, to define the distribution of weeds is very important in precision agriculture and horticulture as well. To survey weeds on larger fields by traditional methods is often time consuming. Remote sensing instruments are useful to detect weeds in larger area. In our investigation a 3D airborne laser scanner (RIEGL LMS-Q680i) was used in agricultural field near Sopron to scouting weeds. Beside the airborne LiDAR, hyperspectral imaging system (AISA DUAL) and air photos helped to investigate weed coverage. The LiDAR survey was carried out at early April, 2012, before sprouting of cultivated plants. Thus, there could be detected emerging of weeds and direction of cultivation. However airborne LiDAR system was ideal to detect weeds, identification of weeds at species level was infeasible. Higher point density LiDAR - Terrestrial laser scanning - systems are appropriate to distinguish weed species. Based on the results, laser scanner is an effective tool to scouting of weeds. Appropriate weed detection and mapping systems could contribute to elaborate water and herbicide saving management technique. This publication was supported by the OTKA project K 105789.

  2. Hyperspectral and LiDAR remote sensing of fire fuels in Hawaii Volcanoes National Park.

    PubMed

    Varga, Timothy A; Asner, Gregory P

    2008-04-01

    Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub-montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non-photosynthetic vegetation, and bare substrate and shade. Small-footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three-dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three-dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three-dimensional properties of ecosystems, their flammability, and the potential for fire spread.

  3. Geospatial revolution and remote sensing LiDAR in Mesoamerican archaeology

    PubMed Central

    Chase, Arlen F.; Fisher, Christopher T.; Leisz, Stephen J.; Weishampel, John F.

    2012-01-01

    The application of light detection and ranging (LiDAR), a laser-based remote-sensing technology that is capable of penetrating overlying vegetation and forest canopies, is generating a fundamental shift in Mesoamerican archaeology and has the potential to transform research in forested areas world-wide. Much as radiocarbon dating that half a century ago moved archaeology forward by grounding archaeological remains in time, LiDAR is proving to be a catalyst for an improved spatial understanding of the past. With LiDAR, ancient societies can be contextualized within a fully defined landscape. Interpretations about the scale and organization of densely forested sites no longer are constrained by sample size, as they were when mapping required laborious on-ground survey. The ability to articulate ancient landscapes fully permits a better understanding of the complexity of ancient Mesoamerican urbanism and also aids in modern conservation efforts. The importance of this geospatial innovation is demonstrated with newly acquired LiDAR data from the archaeological sites of Caracol, Cayo, Belize and Angamuco, Michoacán, Mexico. These data illustrate the potential of technology to act as a catalytic enabler of rapid transformational change in archaeological research and interpretation and also underscore the value of on-the-ground archaeological investigation in validating and contextualizing results. PMID:22802623

  4. Geospatial revolution and remote sensing LiDAR in Mesoamerican archaeology.

    PubMed

    Chase, Arlen F; Chase, Diane Z; Fisher, Christopher T; Leisz, Stephen J; Weishampel, John F

    2012-08-01

    The application of light detection and ranging (LiDAR), a laser-based remote-sensing technology that is capable of penetrating overlying vegetation and forest canopies, is generating a fundamental shift in Mesoamerican archaeology and has the potential to transform research in forested areas world-wide. Much as radiocarbon dating that half a century ago moved archaeology forward by grounding archaeological remains in time, LiDAR is proving to be a catalyst for an improved spatial understanding of the past. With LiDAR, ancient societies can be contextualized within a fully defined landscape. Interpretations about the scale and organization of densely forested sites no longer are constrained by sample size, as they were when mapping required laborious on-ground survey. The ability to articulate ancient landscapes fully permits a better understanding of the complexity of ancient Mesoamerican urbanism and also aids in modern conservation efforts. The importance of this geospatial innovation is demonstrated with newly acquired LiDAR data from the archaeological sites of Caracol, Cayo, Belize and Angamuco, Michoacán, Mexico. These data illustrate the potential of technology to act as a catalytic enabler of rapid transformational change in archaeological research and interpretation and also underscore the value of on-the-ground archaeological investigation in validating and contextualizing results.

  5. How Children Living in Poor Areas of Dar Es Salaam, Tanzania Perceive Their Own Multiple Intelligences

    ERIC Educational Resources Information Center

    Dixon, Pauline; Humble, Steve; Chan, David W.

    2016-01-01

    This study was carried out with 1,857 poor children from 17 schools, living in low-income areas of Dar Es Salaam, Tanzania. All children took the "Student Multiple Intelligences Profile" (SMIP) questionnaire as part of a bigger project that gathered data around concepts and beliefs of talent. This paper sets out two aims, first to…

  6. Child Labour in Urban Agriculture: The Case of Dar es Salaam, Tanzania.

    ERIC Educational Resources Information Center

    Mlozi, Malongo R. S.

    1995-01-01

    Urban agriculture in Dar es Salaam was found to use child labor of both children with parents of higher and lower socioeconomic status (SES). Discusses policy implications and calls for the education of parents of lower SES not to expect an economic contribution from their children's labor, and the education of children about their rights. (LZ)

  7. Registration of optical imagery and LiDAR data using an inherent geometrical constraint.

    PubMed

    Zhang, Wuming; Zhao, Jing; Chen, Mei; Chen, Yiming; Yan, Kai; Li, Linyuan; Qi, Jianbo; Wang, Xiaoyan; Luo, Jinghui; Chu, Qing

    2015-03-23

    A novel method for registering imagery with Light Detection And Ranging (LiDAR) data is proposed. It is based on the phenomenon that the back-projection of LiDAR point cloud of an object should be located within the object boundary in the image. Using this inherent geometrical constraint, the registration parameters computation of both data sets only requires LiDAR point clouds of several objects and their corresponding boundaries in the image. The proposed registration method comprises of four steps: point clouds extraction, boundary extraction, back-projection computation and registration parameters computation. There are not any limitations on the geometrical and spectral properties of the object. So it is suitable not only for structured scenes with man-made objects but also for natural scenes. Moreover, the proposed method based on the inherent geometrical constraint can register two data sets derived from different parts of an object. It can be used to co-register TLS (Terrestrial Laser Scanning) LiDAR point cloud and UAV (Unmanned aerial vehicle) image, which are obtaining more attention in the forest survey application. Using initial registration parameters comparable to POS (position and orientation system) accuracy, the performed experiments validated the feasibility of the proposed registration method.

  8. Integrating ICT into Teaching and Learning at the University of Dar es Salaam

    ERIC Educational Resources Information Center

    Mtebe, Joel S.; Dachi, Hilary; Raphael, Christina

    2011-01-01

    Since 1985, Tanzania has been undergoing significant political and economic changes from a centralized to a more market-oriented and globally connected economy. The University of Dar es Salaam (UDSM) has responded to these changes by reviewing its legal status, vision, and functions, particularly those related to research, teaching, and public…

  9. a Data Driven Method for Building Reconstruction from LiDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Sajadian, M.; Arefi, H.

    2014-10-01

    Airborne laser scanning, commonly referred to as LiDAR, is a superior technology for three-dimensional data acquisition from Earth's surface with high speed and density. Building reconstruction is one of the main applications of LiDAR system which is considered in this study. For a 3D reconstruction of the buildings, the buildings points should be first separated from the other points such as; ground and vegetation. In this paper, a multi-agent strategy has been proposed for simultaneous extraction and segmentation of buildings from LiDAR point clouds. Height values, number of returned pulse, length of triangles, direction of normal vectors, and area are five criteria which have been utilized in this step. Next, the building edge points are detected using a new method named "Grid Erosion". A RANSAC based technique has been employed for edge line extraction. Regularization constraints are performed to achieve the final lines. Finally, by modelling of the roofs and walls, 3D building model is reconstructed. The results indicate that the proposed method could successfully extract the building from LiDAR data and generate the building models automatically. A qualitative and quantitative assessment of the proposed method is then provided.

  10. Genetics and Human Agency: Comment on Dar-Nimrod and Heine (2011)

    ERIC Educational Resources Information Center

    Turkheimer, Eric

    2011-01-01

    Dar-Nimrod and Heine (2011) decried genetic essentialism without denying the importance of genetics in the genesis of human behavior, and although I agree on both counts, a deeper issue remains unaddressed: how should we adjust our cognitions about our own behavior in light of genetic influence, or is it perhaps not necessary to take genetics into…

  11. Genetic Essentialism, Neuroessentialism, and Stigma: Commentary on Dar-Nimrod and Heine (2011)

    ERIC Educational Resources Information Center

    Haslam, Nick

    2011-01-01

    Dar-Nimrod and Heine (2011) presented a masterfully broad review of the implications of genetic essentialism for understandings of human diversity. This commentary clarifies the reasons that essentialist thinking has problematic social consequences and links genetic forms of essentialism to those invoking neural essences. The mounting evidence…

  12. The Effect of Lava Texture on LiDAR Attributes and Full Waveform

    NASA Astrophysics Data System (ADS)

    Anderson, S. W.; Finnegan, D. C.; LeWinter, A.

    2013-12-01

    The distribution of glassy, vesicular, and crystalline textures on lava flow and dome surfaces provides insights regarding the physical and chemical processes occurring during emplacement. For silicic flows, these textures may reflect variations in the volatile content of lava upon eruption. To assess the efficacy of texture detection with our terrestrial full waveform LiDAR system capable of measuring ~125,000 topographic points/second, we analyzed attribute and full waveform data from a variety of lava textures displayed on recent rhyolitic obsidian flows of the Inyo Dome chain (California) and pahoehoe and aa flows at Kilauea volcano (Hawaii). We find that attributes such as intensity, amplitude and deviation of the returned 1550nm laser pulse fall into discrete ranges associated with glassy, pumiceous and crystalline textures on both the rhyolitic and basaltic surfaces. This enables detection of vesicularity at ranges in excess of 500 m, making LiDAR a useful tool for remotely determining lava texture. Scan times using our Riegl VZ1000 and VZ400 systems require only minutes, allowing for repeated scans over a short time period, and processing times are <1 hour. We have also analyzed the full digitized waveforms of LiDAR pulses returned from these surfaces, and find that they also have unique signatures related to texture. We therefore suggest that LiDAR can provide reliable information on lava texture during eruption, aiding in the interpretation of eruption hazards from increasing volatile contents.

  13. Pit latrine emptying behavior and demand for sanitation services in Dar Es Salaam, Tanzania.

    PubMed

    Jenkins, Marion W; Cumming, Oliver; Cairncross, Sandy

    2015-02-27

    Pit latrines are the main form of sanitation in unplanned areas in many rapidly growing developing cities. Understanding demand for pit latrine fecal sludge management (FSM) services in these communities is important for designing demand-responsive sanitation services and policies to improve public health. We examine latrine emptying knowledge, attitudes, behavior, trends and rates of safe/unsafe emptying, and measure demand for a new hygienic latrine emptying service in unplanned communities in Dar Es Salaam (Dar), Tanzania, using data from a cross-sectional survey at 662 residential properties in 35 unplanned sub-wards across Dar, where 97% had pit latrines. A picture emerges of expensive and poor FSM service options for latrine owners, resulting in widespread fecal sludge exposure that is likely to increase unless addressed. Households delay emptying as long as possible, use full pits beyond what is safe, face high costs even for unhygienic emptying, and resort to unsafe practices like 'flooding out'. We measured strong interest in and willingness to pay (WTP) for the new pit emptying service at 96% of residences; 57% were WTP≥U.S. $17 to remove ≥200 L of sludge. Emerging policy recommendations for safe FSM in unplanned urban communities in Dar and elsewhere are discussed.

  14. Spatial Patterns of Trees from Airborne LiDAR Using a Simple Tree Segmentation Algorithm

    NASA Astrophysics Data System (ADS)

    Jeronimo, S.; Kane, V. R.; McGaughey, R. J.; Franklin, J. F.

    2015-12-01

    Objectives for management of forest ecosystems on public land incorporate a focus on maintenance and restoration of ecological functions through silvicultural manipulation of forest structure. The spatial pattern of residual trees - the horizontal element of structure - is a key component of ecological restoration prescriptions. We tested the ability of a simple LiDAR individual tree segmentation method - the watershed transform - to generate spatial pattern metrics similar to those obtained by the traditional method - ground-based stem mapping - on forested plots representing the structural diversity of a large wilderness area (Yosemite NP) and a large managed area (Sierra NF) in the Sierra Nevada, Calif. Most understory and intermediate-canopy trees were not detected by the LiDAR segmentation; however, LiDAR- and field-based assessments of spatial pattern in terms of tree clump size distributions largely agreed. This suggests that (1) even when individual tree segmentation is not effective for tree density estimates, it can provide a good measurement of tree spatial pattern, and (2) a simple segmentation method is adequate to measure spatial pattern of large areas with a diversity of structural characteristics. These results lay the groundwork for a LiDAR tool to assess clumping patterns across forest landscapes in support of restoration silviculture. This tool could describe spatial patterns of functionally intact reference ecosystems, measure departure from reference targets in treatment areas, and, with successive acquisitions, monitor treatment efficacy.

  15. High-throughput genotyping of hop (Humulus lupulus L.) utilising diversity arrays technology (DArT).

    PubMed

    Howard, E L; Whittock, S P; Jakše, J; Carling, J; Matthews, P D; Probasco, G; Henning, J A; Darby, P; Cerenak, A; Javornik, B; Kilian, A; Koutoulis, A

    2011-05-01

    Implementation of molecular methods in hop (Humulus lupulus L.) breeding is dependent on the availability of sizeable numbers of polymorphic markers and a comprehensive understanding of genetic variation. However, use of molecular marker technology is limited due to expense, time inefficiency, laborious methodology and dependence on DNA sequence information. Diversity arrays technology (DArT) is a high-throughput cost-effective method for the discovery of large numbers of quality polymorphic markers without reliance on DNA sequence information. This study is the first to utilise DArT for hop genotyping, identifying 730 polymorphic markers from 92 hop accessions. The marker quality was high and similar to the quality of DArT markers previously generated for other species; although percentage polymorphism and polymorphism information content (PIC) were lower than in previous studies deploying other marker systems in hop. Genetic relationships in hop illustrated by DArT in this study coincide with knowledge generated using alternate methods. Several statistical analyses separated the hop accessions into genetically differentiated North American and European groupings, with hybrids between the two groups clearly distinguishable. Levels of genetic diversity were similar in the North American and European groups, but higher in the hybrid group. The markers produced from this time and cost-efficient genotyping tool will be a valuable resource for numerous applications in hop breeding and genetics studies, such as mapping, marker-assisted selection, genetic identity testing, guidance in the maintenance of genetic diversity and the directed breeding of superior cultivars. PMID:21243330

  16. High-throughput genotyping of hop (Humulus lupulus L.) utilising diversity arrays technology (DArT)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Implementation of molecular methods in hop breeding is dependent on the availability of sizeable numbers of polymorphic markers and a comprehensive understanding of genetic variation. Diversity Arrays Technology (DArT) is a high-throughput cost-effective method for the discovery of large numbers of...

  17. Hyperspectral and LiDAR remote sensing of fire fuels in Hawaii Volcanoes National Park.

    PubMed

    Varga, Timothy A; Asner, Gregory P

    2008-04-01

    Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub-montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non-photosynthetic vegetation, and bare substrate and shade. Small-footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three-dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three-dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three-dimensional properties of ecosystems, their flammability, and the potential for fire spread. PMID:18488621

  18. Biomass estimation of Douglas fir stands using airborne LiDAR data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Biomass is an important parameter not only for carbon cycle modeling, but also for supporting land management operations (e.g. land use policy, forest fire management). Various remote sensing data have been utilized for biomass estimation, especially in forested areas. LiDAR (Light Detection And Ran...

  19. 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…

  20. Pit Latrine Emptying Behavior and Demand for Sanitation Services in Dar Es Salaam, Tanzania

    PubMed Central

    Jenkins, Marion W.; Cumming, Oliver; Cairncross, Sandy

    2015-01-01

    Pit latrines are the main form of sanitation in unplanned areas in many rapidly growing developing cities. Understanding demand for pit latrine fecal sludge management (FSM) services in these communities is important for designing demand-responsive sanitation services and policies to improve public health. We examine latrine emptying knowledge, attitudes, behavior, trends and rates of safe/unsafe emptying, and measure demand for a new hygienic latrine emptying service in unplanned communities in Dar Es Salaam (Dar), Tanzania, using data from a cross-sectional survey at 662 residential properties in 35 unplanned sub-wards across Dar, where 97% had pit latrines. A picture emerges of expensive and poor FSM service options for latrine owners, resulting in widespread fecal sludge exposure that is likely to increase unless addressed. Households delay emptying as long as possible, use full pits beyond what is safe, face high costs even for unhygienic emptying, and resort to unsafe practices like ‘flooding out’. We measured strong interest in and willingness to pay (WTP) for the new pit emptying service at 96% of residences; 57% were WTP ≥U.S. $17 to remove ≥200 L of sludge. Emerging policy recommendations for safe FSM in unplanned urban communities in Dar and elsewhere are discussed. PMID:25734790

  1. Mapping of post-event earthquake induced landslides in Sg. Mesilou using LiDAR

    NASA Astrophysics Data System (ADS)

    Hanan Mat Yusoff, Habibah; Azahari Razak, Khamarrul; Yuen, Florence; Harun, Afifi; Talib, Jasmi; Mohamad, Zakaria; Ramli, Zamri; Abd Razab, Razain

    2016-06-01

    Earthquake is a common natural disaster in active tectonic regions. The disaster can induce cascading disasters such as debris flow, mudflow and reactivated old landslides. M 6.0 Ranau earthquake dated on June 05, 2015 coupling with intense and prolonged rainfall caused several mass movements such as debris flow, deep-seated and shallow landslides in Mesilou, Sabah. This study aims at providing a better insight into the use of advanced LiDAR mapping technology for recognizing landslide induced by earthquakes particularly in a vegetated terrain, assessing post event hazard and analyzing its distribution for hazard zonation. We developed the landslide inventory using LiDAR-derived visual analysis method and validated in the field. A landslide inventory map improved with the support of LiDAR derivative data. Finally, landslide inventory was analysed by emphasizing its distribution and density in such a way that it provides clues of risky zone as a result of debris flow. We recommend that mitigation action and risk reduction should be taken place at a transport zone of the channel compared to other zones. This study indicates that modern airborne LiDAR can be a good complementary tool for improving landslide inventory in a complex environment, and an effective tool for rapid regional hazard and risk assessment in the tropics.

  2. Registration of optical imagery and LiDAR data using an inherent geometrical constraint.

    PubMed

    Zhang, Wuming; Zhao, Jing; Chen, Mei; Chen, Yiming; Yan, Kai; Li, Linyuan; Qi, Jianbo; Wang, Xiaoyan; Luo, Jinghui; Chu, Qing

    2015-03-23

    A novel method for registering imagery with Light Detection And Ranging (LiDAR) data is proposed. It is based on the phenomenon that the back-projection of LiDAR point cloud of an object should be located within the object boundary in the image. Using this inherent geometrical constraint, the registration parameters computation of both data sets only requires LiDAR point clouds of several objects and their corresponding boundaries in the image. The proposed registration method comprises of four steps: point clouds extraction, boundary extraction, back-projection computation and registration parameters computation. There are not any limitations on the geometrical and spectral properties of the object. So it is suitable not only for structured scenes with man-made objects but also for natural scenes. Moreover, the proposed method based on the inherent geometrical constraint can register two data sets derived from different parts of an object. It can be used to co-register TLS (Terrestrial Laser Scanning) LiDAR point cloud and UAV (Unmanned aerial vehicle) image, which are obtaining more attention in the forest survey application. Using initial registration parameters comparable to POS (position and orientation system) accuracy, the performed experiments validated the feasibility of the proposed registration method. PMID:25837107

  3. Clinical, Virologic, and Epidemiologic Characteristics of Dengue Outbreak, Dar es Salaam, Tanzania, 2014

    PubMed Central

    Mboera, Leonard E.G.; De Nardo, Pasquale; Oriyo, Ndekya M.; Meschi, Silvia; Rumisha, Susan F.; Colavita, Francesca; Mhina, Athanas; Carletti, Fabrizio; Mwakapeje, Elibariki; Capobianchi, Maria Rosaria; Castilletti, Concetta; Di Caro, Antonino; Nicastri, Emanuele; Malecela, Mwelecele N.; Ippolito, Giuseppe

    2016-01-01

    We investigated a dengue outbreak in Dar es Salaam, Tanzania, in 2014, that was caused by dengue virus (DENV) serotype 2. DENV infection was present in 101 (20.9%) of 483 patients. Patient age and location of residence were associated with infection. Seven (4.0%) of 176 patients were co-infected with malaria and DENV. PMID:27088845

  4. Development of DArT-based PCR markers for selecting drought-tolerant spring barley.

    PubMed

    Fiust, Anna; Rapacz, Marcin; Wójcik-Jagła, Magdalena; Tyrka, Mirosław

    2015-08-01

    The tolerance of spring barley (Hordeum vulgare L.) cultivars to spring drought is an important agronomic trait affecting crop yield and quality in Poland. Therefore, breeders require new molecular markers to select plants with lower spring drought susceptibility. With the advent of genomic selection technology, simple molecular tools may still be applicable to screen material for markers of the most important traits and in-depth genome scanning. In previous studies, diversity arrays technology (DArT)-based genetic maps were constructed for F2 populations of Polish fodder and malt barley elite breeding lines, and 15 and 18 quantitative trait loci (QTLs) related to spring drought tolerance were identified, respectively. In this paper, we show the results of a conversion of 30 DArT markers corresponding to 11 QTLs into simple sequence repeat (SSR) and sequence tagged site (STS) markers. Twenty-two polymorphic markers were obtained, including 13 DArT-based SSRs. Additionally, 31 SSR markers, located in close proximity to the DArT markers, were selected from the GrainGenes database and tested. Further analyses of 24 advanced breeding lines with different drought tolerances confirmed that five out of the 30 converted markers, as well as three out of the 31 additional SSR markers, were effective in marker-assisted selection for drought tolerance. The possible function of clones related to these markers in drought tolerance is discussed. PMID:25716655

  5. Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale.

    PubMed

    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

  6. 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

  7. Field and LiDAR observations of the Hector Mine California 1999 surface rupture

    NASA Astrophysics Data System (ADS)

    Sousa, F.; Akciz, S. O.; Harvey, J. C.; Hudnut, K. W.; Lynch, D. K.; Scharer, K. M.; Stock, J. M.; Witkosky, R.; Kendrick, K. J.; Wespestad, C.

    2014-12-01

    We report new field- and computer-based investigations of the surface rupture of the October 16, 1999 Hector Mine Earthquake. Since May 2012, in cooperation with the United States Marine Corps Air Ground Combat Center (MCAGCC) at Twentynine Palms, CA, our team has been allowed ground and aerial access to the entire surface rupture. We have focused our new field-based research and imagery analysis along the ~10 kilometer-long maximum slip zone (MSZ) which roughly corresponds to the zone of >4 meter dextral horizontal offset. New data include: 1) a 1 km wide aerial LiDAR survey along the entire surface rupture (@ 10 shots/m2, May 2012, www.opentopography.org); 2) terrestrial LiDAR surveys at 5 sites within the MSZ (@ >1000 shots/m2, April 2014); 3) low altitude aerial photography and ground based photography of the entire MSZ; 4) a ground-truthed database of 87 out of the 94 imagery-based offset measurements made within the MSZ; and 5) a database of 50 new field-based offset measurements made within the MSZ by our team on the ground, 31 of which have also been made on the computer (Ladicaoz) with both the 2000 LiDAR data (@ 0.5 m DEM resolution; Chen et al, in review) and 2012 LiDAR data (@ 35 cm DEM resolution; our team). New results to date include 1) significant variability (> 2 m) in horizontal offsets measured along short distances of the surface rupture (~100 m) within segments of the surface rupture that are localized to a single fault strand; 2) strong dependence of decadal scale fault scarp preservation on local lithology (bedrock vs. alluvial fan vs. fine sediment) and geomorphology (uphill vs. downhill facing scarp); 3) newly observed offset features which were never measured during the post-event field response; 4) newly observed offset features too small to be resolved in airborne LiDAR data (< 1 m); 5) nearly 25% of LiDAR imagery-based measurements that were later ground-truthed were judged by our team to warrant removal from the database due to

  8. Application of LiDAR to hydrologic flux estimation in Australian eucalypt forests (Invited)

    NASA Astrophysics Data System (ADS)

    Lane, P. N.; Mitchell, P. J.; Jaskierniak, D.; Hawthorne, S. N.; Griebel, A.

    2013-12-01

    The potential of LiDAR in ecohydrology is significant as characterising catchment vegetation is crucial to accurate estimation of evapotranspiration (ET). While this may be done at large scales for model parameterisation, stand-scale applications are equally appropriate where traditional methods of measurement of LAI or sapwood areas are time consuming and reliant on assumptions of representative sampling. This is particularly challenging in mountain forests where aspect, soil properties and energy budgets can vary significantly, reflected in the vegetation or where there are changes in the spatial distribution of structural attributes following disturbance. Recent research has investigated the spatial distribution of ET in a eucalypt forest in SE Australia using plot-scale sapflow, interception and forest floor ET measurements. LiDAR was used scale up these measurements. LiDAR (0.16 m scanner footprint) canopy indices were correlated via stepwise regression with 4 water use scalars: basal area (BA), sapwood area (SA), leaf area index (LAI) and canopy coverage (C), with Hmed, Hmean, H80, H95 the best predictors. Combining these indices with empirical relationships between SA and BA, and SA and transpiration (T), and inventory plot 'ground truthing' transpiration was estimated across the 1.3 km2 catchment. Interception was scaled via the Gash model with LiDAR derived inputs. The up-scaling showed a significant variability in the spatial distribution of ET, related to the distribution of SA. The use of LiDAR meant scaling could be achieved at an appropriate spatial scale (20 x 20 m) to the measurements. The second example is the use of airborne LiDAR in developing growth forest models for hydrologic modeling. LiDAR indices were used to stratify multilayered forests using mixed-effect models with a wide range of theoretical distribution functions. When combined with historical plot-scale inventory data we show demonstrated improved growth modeling over traditional

  9. A universal airborne LiDAR approach for tropical forest carbon mapping.

    PubMed

    Asner, Gregory P; Mascaro, Joseph; Muller-Landau, Helene C; Vieilledent, Ghislain; Vaudry, Romuald; Rasamoelina, Maminiaina; Hall, Jefferson S; van Breugel, Michiel

    2012-04-01

    Airborne light detection and ranging (LiDAR) is fast turning the corner from demonstration technology to a key tool for assessing carbon stocks in tropical forests. With its ability to penetrate tropical forest canopies and detect three-dimensional forest structure, LiDAR may prove to be a major component of international strategies to measure and account for carbon emissions from and uptake by tropical forests. To date, however, basic ecological information such as height-diameter allometry and stand-level wood density have not been mechanistically incorporated into methods for mapping forest carbon at regional and global scales. A better incorporation of these structural patterns in forests may reduce the considerable time needed to calibrate airborne data with ground-based forest inventory plots, which presently necessitate exhaustive measurements of tree diameters and heights, as well as tree identifications for wood density estimation. Here, we develop a new approach that can facilitate rapid LiDAR calibration with minimal field data. Throughout four tropical regions (Panama, Peru, Madagascar, and Hawaii), we were able to predict aboveground carbon density estimated in field inventory plots using a single universal LiDAR model (r ( 2 ) = 0.80, RMSE = 27.6 Mg C ha(-1)). This model is comparable in predictive power to locally calibrated models, but relies on limited inputs of basal area and wood density information for a given region, rather than on traditional plot inventories. With this approach, we propose to radically decrease the time required to calibrate airborne LiDAR data and thus increase the output of high-resolution carbon maps, supporting tropical forest conservation and climate mitigation policy.

  10. Estimating Above Ground Biomass using LiDAR in the Northcoast Redwood Forests

    NASA Astrophysics Data System (ADS)

    Rao, M.; Stewart, E.

    2010-12-01

    In recent years, LiDAR (Light Intensity Detection Amplification and Ranging) is increasingly being used in estimating biophysical parameters related to forested environments. The main goal of the project is to estimate long-term biomass accumulation and carbon sequestration potential of the redwoods ecosystem. The project objectives are aimed at providing an assessment of carbon pools within the redwood ecosystem. Specifically, we intend to develop a relational model based on LiDAR-based canopy estimates and extensive ground-based measurements available for the old-growth redwood forest located within the Prairie Creek Redwoods State Park, CA. Our preliminary analysis involved developing a geospatial database, including LiDAR data collected in 2007 for the study site, and analyzing the data using USFS Fusion software. The study area comprised of a 12-acres section of coastal redwood (Sequoia sempervirens) in the Prairie Creek Redwoods State Park, located in Orick, CA. A series of analytical steps were executed using the USFS FUSION software to produce some intermediate data such as bare earth model, canopy height model, canopy coverage model, and canopy maxima treelist. Canopy maxima tree tops were compared to ground layer to determine height of tree tops. A total of over 1000 trees were estimated, and then with thinning (to eliminate errors due to low vegetation > 3 meters tall), a total of 950 trees were delineated. Ground measurements were imported as a point based shapefile and then compared to the treetop heights created from LiDAR data to the actual ground referenced data. The results were promising as most estimated treetops were within 1-3 meters of the ground measurements and generally within 3-5m of the actual tree height. Finally, we are in the process of applying some allometric equations to estimate above ground biomass using some of the LiDAR-derived canopy metrics.

  11. Water turbidity estimation from airborne hyperspectral imagery and full waveform bathymetric LiDAR

    NASA Astrophysics Data System (ADS)

    Pan, Z.; Glennie, C. L.; Fernandez-Diaz, J. C.

    2015-12-01

    The spatial and temporal variations in water turbidity are of great interest for the study of fluvial and coastal environments; and for predicting the performance of remote sensing systems that are used to map these. Conventional water turbidity estimates from remote sensing observations have normally been derived using near infrared reflectance. We have investigated the potential of determining water turbidity from additional remote sensing sources, namely airborne hyperspectral imagery and single wavelength bathymetric LiDAR (Light Detection and Ranging). The confluence area of the Blue and Colorado River, CO was utilized as a study area to investigate the capabilities of both airborne bathymetric LiDAR and hyperspectral imagery for water turbidity estimation. Discrete and full waveform bathymetric data were collected using Optech's Gemini (1064 nm) and Aquarius (532 nm) LiDAR sensors. Hyperspectral imagery (1.2 m pixel resolution and 72 spectral bands) was acquired using an ITRES CASI-1500 imaging system. As an independent reference, measurements of turbidity were collected concurrent with the airborne remote sensing acquisitions, using a WET Labs EcoTriplet deployed from a kayak and turbidity was then derived from the measured backscatter. The bathymetric full waveform dataset contains a discretized sample of the full backscatter of water column and benthic layer. Therefore, the full waveform records encapsulate the water column characteristics of turbidity. A nonparametric support vector regression method is utilized to estimate water turbidity from both hyperspectral imagery and voxelized full waveform LiDAR returns, both individually and as a fused dataset. Results of all the evaluations will be presented, showing an initial turbidity prediction accuracy of approximately 1.0 NTU. We will also discuss our future strategy for enhanced fusion of the full waveform LiDAR and hyperspectral imagery for improved turbidity estimation.

  12. Applying a weighted random forests method to extract karst sinkholes from LiDAR data

    NASA Astrophysics Data System (ADS)

    Zhu, Junfeng; Pierskalla, William P.

    2016-02-01

    Detailed mapping of sinkholes provides critical information for mitigating sinkhole hazards and understanding groundwater and surface water interactions in karst terrains. LiDAR (Light Detection and Ranging) measures the earth's surface in high-resolution and high-density and has shown great potentials to drastically improve locating and delineating sinkholes. However, processing LiDAR data to extract sinkholes requires separating sinkholes from other depressions, which can be laborious because of the sheer number of the depressions commonly generated from LiDAR data. In this study, we applied the random forests, a machine learning method, to automatically separate sinkholes from other depressions in a karst region in central Kentucky. The sinkhole-extraction random forest was grown on a training dataset built from an area where LiDAR-derived depressions were manually classified through a visual inspection and field verification process. Based on the geometry of depressions, as well as natural and human factors related to sinkholes, 11 parameters were selected as predictive variables to form the dataset. Because the training dataset was imbalanced with the majority of depressions being non-sinkholes, a weighted random forests method was used to improve the accuracy of predicting sinkholes. The weighted random forest achieved an average accuracy of 89.95% for the training dataset, demonstrating that the random forest can be an effective sinkhole classifier. Testing of the random forest in another area, however, resulted in moderate success with an average accuracy rate of 73.96%. This study suggests that an automatic sinkhole extraction procedure like the random forest classifier can significantly reduce time and labor costs and makes its more tractable to map sinkholes using LiDAR data for large areas. However, the random forests method cannot totally replace manual procedures, such as visual inspection and field verification.

  13. Combined use of LiDAR data and multispectral earth observation imagery for wetland habitat mapping

    NASA Astrophysics Data System (ADS)

    Rapinel, Sébastien; Hubert-Moy, Laurence; Clément, Bernard

    2015-05-01

    Although wetlands play a key role in controlling flooding and nonpoint source pollution, sequestering carbon and providing an abundance of ecological services, the inventory and characterization of wetland habitats are most often limited to small areas. This explains why the understanding of their ecological functioning is still insufficient for a reliable functional assessment on areas larger than a few hectares. While LiDAR data and multispectral Earth Observation (EO) images are often used separately to map wetland habitats, their combined use is currently being assessed for different habitat types. The aim of this study is to evaluate the combination of multispectral and multiseasonal imagery and LiDAR data to precisely map the distribution of wetland habitats. The image classification was performed combining an object-based approach and decision-tree modeling. Four multispectral images with high (SPOT-5) and very high spatial resolution (Quickbird, KOMPSAT-2, aerial photographs) were classified separately. Another classification was then applied integrating summer and winter multispectral image data and three layers derived from LiDAR data: vegetation height, microtopography and intensity return. The comparison of classification results shows that some habitats are better identified on the winter image and others on the summer image (overall accuracies = 58.5 and 57.6%). They also point out that classification accuracy is highly improved (overall accuracy = 86.5%) when combining LiDAR data and multispectral images. Moreover, this study highlights the advantage of integrating vegetation height, microtopography and intensity parameters in the classification process. This article demonstrates that information provided by the synergetic use of multispectral images and LiDAR data can help in wetland functional assessment

  14. LiDAR Segmentation using Suitable Seed Points for 3D Building Extraction

    NASA Astrophysics Data System (ADS)

    Abdullah, S. M.; Awrangjeb, M.; Lu, G.

    2014-08-01

    Effective building detection and roof reconstruction has an influential demand over the remote sensing research community. In this paper, we present a new automatic LiDAR point cloud segmentation method using suitable seed points for building detection and roof plane extraction. Firstly, the LiDAR point cloud is separated into "ground" and "non-ground" points based on the analysis of DEM with a height threshold. Each of the non-ground point is marked as coplanar or non-coplanar based on a coplanarity analysis. Commencing from the maximum LiDAR point height towards the minimum, all the LiDAR points on each height level are extracted and separated into several groups based on 2D distance. From each group, lines are extracted and a coplanar point which is the nearest to the midpoint of each line is considered as a seed point. This seed point and its neighbouring points are utilised to generate the plane equation. The plane is grown in a region growing fashion until no new points can be added. A robust rule-based tree removal method is applied subsequently to remove planar segments on trees. Four different rules are applied in this method. Finally, the boundary of each object is extracted from the segmented LiDAR point cloud. The method is evaluated with six different data sets consisting hilly and densely vegetated areas. The experimental results indicate that the proposed method offers a high building detection and roof plane extraction rates while compared to a recently proposed method.

  15. Mapping the Risk of Forest Wind Damage Using Airborne Scanning LiDAR

    NASA Astrophysics Data System (ADS)

    Saarinen, N.; Vastaranta, M.; Honkavaara, E.; Wulder, M. A.; White, J. C.; Litkey, P.; Holopainen, M.; Hyyppä, J.

    2015-03-01

    Wind damage is known for causing threats to sustainable forest management and yield value in boreal forests. Information about wind damage risk can aid forest managers in understanding and possibly mitigating damage impacts. The objective of this research was to better understand and quantify drivers of wind damage, and to map the probability of wind damage. To accomplish this, we used open-access airborne scanning light detection and ranging (LiDAR) data. The probability of wind-induced forest damage (PDAM) in southern Finland (61°N, 23°E) was modelled for a 173 km2 study area of mainly managed boreal forests (dominated by Norway spruce and Scots pine) and agricultural fields. Wind damage occurred in the study area in December 2011. LiDAR data were acquired prior to the damage in 2008. High spatial resolution aerial imagery, acquired after the damage event (January, 2012) provided a source of model calibration via expert interpretation. A systematic grid (16 m x 16 m) was established and 430 sample grid cells were identified systematically and classified as damaged or undamaged based on visual interpretation using the aerial images. Potential drivers associated with PDAM were examined using a multivariate logistic regression model. Risk model predictors were extracted from the LiDAR-derived surface models. Geographic information systems (GIS) supported spatial mapping and identification of areas of high PDAM across the study area. The risk model based on LiDAR data provided good agreement with detected risk areas (73 % with kappa-value 0,47). The strongest predictors in the risk model were mean canopy height and mean elevation. Our results indicate that open-access LiDAR data sets can be used to map the probability of wind damage risk without field data, providing valuable information for forest management planning.

  16. Building Damage Assessment after Earthquake Using Post-Event LiDAR Data

    NASA Astrophysics Data System (ADS)

    Rastiveis, H.; Eslamizade, F.; Hosseini-Zirdoo, E.

    2015-12-01

    After an earthquake, damage assessment plays an important role in leading rescue team to help people and decrease the number of mortality. Damage map is a map that demonstrates collapsed buildings with their degree of damage. With this map, finding destructive buildings can be quickly possible. In this paper, we propose an algorithm for automatic damage map generation after an earthquake using post-event LiDAR Data and pre-event vector map. The framework of the proposed approach has four main steps. To find the location of all buildings on LiDAR data, in the first step, LiDAR data and vector map are registered by using a few number of ground control points. Then, building layer, selected from vector map, are mapped on the LiDAR data and all pixels which belong to the buildings are extracted. After that, through a powerful classifier all the extracted pixels are classified into three classes of "debris", "intact building" and "unclassified". Since textural information make better difference between "debris" and "intact building" classes, different textural features are applied during the classification. After that, damage degree for each candidate building is estimated based on the relation between the numbers of pixels labelled as "debris" class to the whole building area. Calculating the damage degree for each candidate building, finally, building damage map is generated. To evaluate the ability proposed method in generating damage map, a data set from Port-au-Prince, Haiti's capital after the 2010 Haiti earthquake was used. In this case, after calculating of all buildings in the test area using the proposed method, the results were compared to the damage degree which estimated through visual interpretation of post-event satellite image. Obtained results were proved the reliability of the proposed method in damage map generation using LiDAR data.

  17. Object-oriented identification of forested landslides with derivatives of single pulse LiDAR data

    NASA Astrophysics Data System (ADS)

    Van Den Eeckhaut, Miet; Kerle, Norman; Poesen, Jean; Hervás, Javier

    2012-11-01

    In contrast to the many studies that use expert-based analysis of LiDAR derivatives for landslide mapping in forested terrain, only few studies have attempted to develop (semi-)automatic methods for extracting landslides from LiDAR derivatives. While all these studies are pixel-based, it has not yet been tested whether object-oriented analysis (OOA) could be an alternative. This study investigates the potential of OOA using only single-pulse LiDAR derivatives, such as slope gradient, roughness and curvature to map landslides. More specifically, the focus is on both LiDAR data segmentation and classification of slow-moving landslides in densely vegetated areas, where spectral data do not allow accurate landslide identification. A multistage procedure has been developed and tested in the Flemish Ardennes (Belgium). The procedure consists of (1) image binarization and multiresolution segmentation, (2) classification of landslide parts (main scarps and landslide body segments) and non-landslide features (i.e. earth banks and cropland fields) with supervised support vector machines at the appropriate scale, (3) delineation of landslide flanks, (4) growing of a landslide body starting from its main scarp, and (5) final cleaning of the inventory map. The results obtained show that OOA using LiDAR derivatives allows recognition and characterization of profound morphologic properties of forested deep-seated landslides on soil-covered hillslopes, because more than 90% of the main scarps and 70% of the landslide bodies of an expert-based inventory were accurately identified with OOA. For mountainous areas with bedrock, on the other hand, creation of a transferable model is expected to be more difficult.

  18. 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 Central

    2013-01-01

    Background 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. Results 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. Conclusions 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. PMID:23819624

  19. Hospitals for sale.

    PubMed

    Costello, Michael M; West, Daniel J; Ramirez, Bernardo

    2011-01-01

    The pace of hospital merger and acquisition activity reflects the economic theory of supply and demand: Publicly traded hospital companies, private equity funds, and large nonprofit hospital systems are investing capital to purchase and operate freestanding community hospitals at a time when many of those hospitals find themselves short of capital reserves and certain forms of management expertise. But the sale of those community hospitals also raises questions about the impact of absentee ownership on the communities which those hospitals serve.

  20. 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. PMID:26250147

  1. Spatial accounting for errors in LiDAR-derived products: Snow volume and snow water equivalent estimation

    NASA Astrophysics Data System (ADS)

    Tinkham, W. T.; Hoffman, C. M.; Falkowski, M. J.; Smith, A. M.; Link, T. E.; Marshall, H.

    2011-12-01

    Light Detection and Ranging (LiDAR) has become one of the most effective and reliable means of characterizing surface topography and vegetation structure. Most LiDAR-derived estimates such as vegetation height, snow depth, and floodplain boundaries rely on the accurate creation of digital terrain models (DTM). As a result of the importance of an accurate DTM in using LiDAR data to estimate snow depth, it is necessary to understand the variables that influence the DTM accuracy in order to assess snow depth error. A series of 4 x 4 m plots that were surveyed at 0.5 m spacing in a semi-arid catchment were used for training the Random Forests algorithm along with a series of 35 variables in order to spatially predict vertical error within a LiDAR derived DTM. The final model was utilized to predict the combined error resulting from snow volume and snow water equivalent estimates derived from a snow-free LiDAR DTM and a snow-on LiDAR acquisition of the same site. The methodology allows for a statistical quantification of the spatially-distributed error patterns that are incorporated into the estimation of snow volume and snow water equivalents from LiDAR.

  2. 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

  3. Capabilities of the bathymetric Hawk Eye LiDAR for coastal habitat mapping: A case study within a Basque estuary

    NASA Astrophysics Data System (ADS)

    Chust, Guillem; Grande, Maitane; Galparsoro, Ibon; Uriarte, Adolfo; Borja, Ángel

    2010-10-01

    The bathymetric LiDAR system is an airborne laser that detects sea bottom at high vertical and horizontal resolutions in shallow coastal waters. This study assesses the capabilities of the airborne bathymetric LiDAR sensor (Hawk Eye system) for coastal habitat mapping in the Oka estuary (within the Biosphere Reserve of Urdaibai, SE Bay of Biscay, northern Spain), where water conditions are moderately turbid. Three specific objectives were addressed: 1) to assess the data quality of the Hawk Eye LiDAR, both for terrestrial and subtidal zones, in terms of height measurement density, coverage, and vertical accuracy; 2) to compare bathymetric LiDAR with a ship-borne multibeam echosounder (MBES) for different bottom types and depth ranges; and 3) to test the discrimination potential of LiDAR height and reflectance information, together with multi-spectral imagery (three visible and near infrared bands), for the classification of 22 salt marsh and rocky shore habitats, covering supralittoral, intertidal and subtidal zones. The bathymetric LiDAR Hawk Eye data enabled the generation of a digital elevation model (DEM) of the Oka estuary, at 2 m of horizontal spatial resolution in the terrestrial zone (with a vertical accuracy of 0.15 m) and at 4 m within the subtidal, extending a water depth of 21 m. Data gaps occurred in 14.4% of the area surveyed with the LiDAR (13.69 km 2). Comparison of the LiDAR system and the MBES showed no significant mean difference in depth. However, the Root Mean Square error of the former was high (0.84 m), especially concentrated upon rocky (0.55-1.77 m) rather than in sediment bottoms (0.38-0.62 m). The potential of LiDAR topographic variables and reflectance alone for discriminating 15 intertidal and submerged habitats was low (with overall classification accuracy between 52.4 and 65.4%). In particular, reflectance retrieved for this case study has been found to be not particularly useful for classification purposes. The combination of the LiDAR

  4. DArT markers: diversity analyses, genomes comparison, mapping and integration with SSR markers in Triticum monococcum

    PubMed Central

    Jing, Hai-Chun; Bayon, Carlos; Kanyuka, Kostya; Berry, Simon; Wenzl, Peter; Huttner, Eric; Kilian, Andrzej; E Hammond-Kosack, Kim

    2009-01-01

    Background Triticum monococcum (2n = 2x = 14) is an ancient diploid wheat with many useful traits and is used as a model for wheat gene discovery. DArT (Diversity Arrays Technology) employs a hybridisation-based approach to type thousands of genomic loci in parallel. DArT markers were developed for T. monococcum to assess genetic diversity, compare relationships with hexaploid genomes, and construct a genetic linkage map integrating DArT and microsatellite markers. Results A DArT array, consisting of 2304 hexaploid wheat, 1536 tetraploid wheat, 1536 T. monococcum as well as 1536 T. boeoticum representative genomic clones, was used to fingerprint 16 T. monococcum accessions of diverse geographical origins. In total, 846 polymorphic DArT markers were identified, of which 317 were of T. monococcum origin, 246 of hexaploid, 157 of tetraploid, and 126 of T. boeoticum genomes. The fingerprinting data indicated that the geographic origin of T. monococcum accessions was partially correlated with their genetic variation. DArT markers could also well distinguish the genetic differences amongst a panel of 23 hexaploid wheat and nine T. monococcum genomes. For the first time, 274 DArT markers were integrated with 82 simple sequence repeat (SSR) and two morphological trait loci in a genetic map spanning 1062.72 cM in T. monococcum. Six chromosomes were represented by single linkage groups, and chromosome 4Am was formed by three linkage groups. The DArT and SSR genetic loci tended to form independent clusters along the chromosomes. Segregation distortion was observed for one third of the DArT loci. The Ba (black awn) locus was refined to a 23.2 cM region between the DArT marker locus wPt-2584 and the microsatellite locus Xgwmd33 on 1Am; and the Hl (hairy leaf) locus to a 4.0 cM region between DArT loci 376589 and 469591 on 5Am. Conclusion DArT is a rapid and efficient approach to develop many new molecular markers for genetic studies in T. monococcum. The constructed genetic

  5. Investigating the spatial distribution of water levels in the Mackenzie Delta using airborne LiDAR

    USGS Publications Warehouse

    Hopkinson, C.; Crasto, N.; Marsh, P.; Forbes, D.; Lesack, L.

    2011-01-01

    Airborne light detection and ranging (LiDAR) data were used to map water level (WL) and hydraulic gradients (??H/??x) in the Mackenzie Delta. The LiDAR WL data were validated against eight independent hydrometric gauge measurements and demonstrated mean offsets from - 0??22 to + 0??04 m (??< 0??11). LiDAR-based WL gradients could be estimated with confidence over channel lengths exceeding 5-10 km where the WL change exceeded local noise levels in the LiDAR data. For the entire Delta, the LiDAR sample coverage indicated a rate of change in longitudinal gradient (??2H/??x) of 5??5 ?? 10-10 m m-2; therefore offering a potential means to estimate average flood stage hydraulic gradient for areas of the Delta not sampled or monitored. In the Outer Delta, within-channel and terrain gradient measurements all returned a consistent estimate of - 1 ?? 10-5 m m-1, suggesting that this is a typical hydraulic gradient for the downstream end of the Delta. For short reaches (<10 km) of the Peel and Middle Channels in the middle of the Delta, significant and consistent hydraulic gradient estimates of - 5 ?? 10-5 m m-1 were observed. Evidence that hydraulic gradients can vary over short distances, however, was observed in the Peel Channel immediately upstream of Aklavik. A positive elevation anomaly (bulge) of > 0??1 m was observed at a channel constriction entering a meander bend, suggesting a localized modification of the channel hydraulics. Furthermore, water levels in the anabranch channels of the Peel River were almost 1 m higher than in Middle Channel of the Mackenzie River. This suggests: (i) the channels are elevated and have shallower bank heights in this part of the delta, leading to increased cross-delta and along-channel hydraulic gradients; and/or (ii) a proportion of the Peel River flow is lost to Middle Channel due to drainage across the delta through anastamosing channels. This study has demonstrated that airborne LiDAR data contain valuable information describing

  6. Importance of High-Resolution LiDAR Data in Modeling Runoff Levels Over Impervious Surfaces

    NASA Astrophysics Data System (ADS)

    Melosh, C.; Rao, M.

    2013-12-01

    Directly connected impervious areas collect and deliver unfiltered runoff to modified and impacted waterways. Modeling water flow over the landscape is an effective method of observing drainage patterns and predicting pollutant and sediment loadings. Improved models applying high-resolution elevation data can identify key areas with high pollutant output. This is a crucial issue in the Lake Tahoe Basin where lakeshore urban development has increased and lake clarity has been declining for years. This study aims to evaluate an integrated LiDAR and GIS-based modeling approach that uses a fine-scaled ground surface and impervious surface connectivity to predict the pollutant load in the Lake Tahoe Basin This study produced a fine-scaled surface model of nine subset catchments in the South Tahoe basin, including areas of low (below 20%), medium (30% to 50%) and high (above 50%) impervious surface cover. Our method integrated LiDAR, multispectral imagery, and GIS data to develop accurate terrain models, hydrologic routing, and directly connected impervious area layers for the Lake Tahoe basin. The high-density ground and object elevation data collected using Light Detection and Ranging (LiDAR) creates an accurate picture of water flow over the land, and obstacles to the flow such as buildings. High-resolution LiDAR data was obtained from the Round 10 Lake Tahoe Southern Nevada Public Land Management capital program from the year 2010. This data was processed to create a digital elevation model of the ground surface. Land use classification used object height information from the LiDAR cloud, NAIP 4-band images with 1-meter resolution and a normalized difference vegetation index image derived from the NAIP imagery. The US Army Core of Engineers hydrologic modeling system (HEC-HMS) will be used to model runoff. Based on long-term simulations the effect of directly connected impervious area on rainfall-runoff characteristics for the South Lake Tahoe catchments will be

  7. Petrology, chemistry, and isotopic compositions of the Lunar highland regolith breccia Dar AL Gani 262

    NASA Astrophysics Data System (ADS)

    Bischoff, A.; Weber, D.; Clayton, R. N.; Faestermann, T.; Franchi, I. A.; Herpers, U.; Knie, K.; Korschinek, G.; Kubik, P. W.; Mayeda, T. K.; Merchel, S.; Michel, R.; Neumann, S.; Palme, H.; Pillinger, C. T.; Schultz, L.; Sexton, A. S.; Spettel, B.; Verchovsky, A. B.; Weber, H. W.; Weckwerth, G.; Wolf, D.

    1998-11-01

    Lunar meteorite Dar al Gani 262 (DG 262) found in the Libyan part of the Sahara is a mature, anorthositic regolith breccia with highland affinities. The origin from the Moon is undoubtedly indicated by its bulk chemical composition, radionuclide concentrations, noble gas, nitrogen, and oxygen isotopic compositions and petrographic features. Dar al Gani 262 is a typical anorthositic highland breccia similar in mineralogy and chemical composition to QUE93069. About 52 vol% of the studied thin sections of Dar al Gani 262 consist of fine-grained (smaller than ?100 microns) constituents, and 48 vol% is mineral and lithic clasts and impact melt veins. The most abundant clast types are feldspathic fine-grained to microporphyritic crystalline melt breccias (50.2 vol%; includes recrystallized melt breccias), whereas mafic crystalline melt breccias are extremely rare (1.4 vol%). Granulitic lithologies are 12.8 vol%, intragranularly recrystallized anorthosites and cataclastic anorthosites are 8.8 and 8.2 vol%, respectively, and (devitrified) glasses are 2.7 vol%. Impact melt veins (5.5 vol% of the whole thin sections) cutting across the entire thin section were probably formed subsequent to the lithification process of the bulk rock at pressures below 20 GPa, because the bulk rock never experienced a higher peak shock pressure. Mafic crystalline melt breccias are very rare in Dar al Gani 262 and similar in abundance to those in QUE93069. The extremely low abundance of mafic components and the bulk composition may constrain possible areas of the Moon from which the breccia was derived. The source area of Dar al Gani 262 must be a highland terrain lacking significant mafic impact melts or mare components. Based on radionuclide activities an irradiation position of DG 262 on the Moon at a depth of 55-85 g/cm3 and a maximum transit time to Earth less than 0.15 Ma is suggested. Dar al Gani 262 contains high concentrations of solar wind implanted noble gases. The isotopic abundance

  8. Information needs and seeking behaviour among health professionals working at public hospital and health centres in Bahir Dar, Ethiopia

    PubMed Central

    2013-01-01

    Background Universal access to information for health professionals is a need to achieve “health for all strategy.” A large proportion of the population including health professionals have limited access to health information in resource limited countries. The aim of this study is to assess information needs among Ethiopian health professionals. Methods A cross sectional quantitative study design complemented with qualitative method was conducted among 350 health care workers in Feburary26-June5/2012. Pretested self-administered questionnaire and observation checklist were used to collect data on different variables. Data entry and data analysis were done using Epi-Info version 3.5.1 and by SPSS version19, respectively. Descriptive statistics and multivariate regression analyses were applied to describe study objectives and identify the determinants of information seeking behaviours respectively. Odds ratio with 95% CI was used to assess the association between a factor and an outcome variable. Results The majority of the respondents acknowledged the need of health information to their routine activities. About 54.0% of respondents lacked access to health information. Only 42.8% of respondents have access to internet sources. Important barriers to access information were geographical, organizational, personal, economic, educational status and time. About 58.0% of the respondents accessed information by referring their hard copies and asking senior staff. Age, sex, income, computer literacy and access, patient size, work experience and working site were significantly associated with information needs and seeking behaviour. Conclusions The health information seeking behaviour of health professional was significant. The heaklth facilities had neither informationcenter such as library, nor internet facilities. Conducting training on managing health information, accessing computer and improving infrastructures are important interventions to facilitate evidence based descions. PMID:24373296

  9. Hospital-acquired pneumonia

    MedlinePlus

    ... tends to be more serious than other lung infections because: People in the hospital are often very sick and cannot fight off ... prevent pneumonia. Most hospitals have programs to prevent hospital-acquired infections.

  10. Advances in animal ecology from 3D-LiDAR ecosystem mapping.

    PubMed

    Davies, Andrew B; Asner, Gregory P

    2014-12-01

    The advent and recent advances of Light Detection and Ranging (LiDAR) have enabled accurate measurement of 3D ecosystem structure. Here, we review insights gained through the application of LiDAR to animal ecology studies, revealing the fundamental importance of structure for animals. Structural heterogeneity is most conducive to increased animal richness and abundance, and increased complexity of vertical vegetation structure is more positively influential compared with 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. To develop a better understanding of animal dynamics, future studies will benefit from considering 3D habitat effects in a wider variety of ecosystems and with more taxa.

  11. Characterization of Forest Ecosystems by combined Radiative Transfer Modeling for Imaging Spectrometer and LiDAR

    NASA Astrophysics Data System (ADS)

    Koetz, B.; Sun, G.; Morsdorf, F.; Rubio, J.; Kimes, D.; Ranson, J.

    2009-04-01

    This research was motivated by the increased information dimensionality provided by current Earth Observation systems measuring the complex and dynamic medium of the vegetated surface of the Earth. Advanced and reliable algorithms that fully exploit this enhanced Earth Observation information are needed to deliver consistent data sets of the Earth vegetation condition describing its spatial distribution and change over time. Spectral observation provided by imaging spectrometers and the waveform from large-footprint LiDAR are now available from space for forest ecosystem studies. The imaging spectrometer data contains information about the biochemical composition of the canopy foliage, and is widely used to estimate biophysical canopy parameters such as LAI and fractional cover. LiDAR responds to the vertical distribution of scatters and permits inferences about the plant structures required to supply water and mechanical support to those surfaces. Various canopy height indices derived from LiDAR waveform have been successfully used to infer forest above-ground biomass and the characterization of canopy structure. The structure parameters derived from LiDAR data can improve the accuracy and robustness of canopy parameter retrieval from imaging spectrometer by reducing uncertainties related to the canopy structure. The specific information content, inherent to the observations of imaging spectrometry and LIDAR, assesses thus different but complementary characteristics of the complex vegetation canopy. The combination of these two information dimensions offers a unique and reliable canopy characterization including information relevant to different aspects of the biochemical and biophysical properties and thus understanding of processes within forest ecosystems. A comprehensive canopy characterization of a forest ecosystem is derived from the combined remote sensing signal of imaging spectrometry and large footprint LIDAR. The inversion of two linked physically based

  12. Cosmogenic Records in 18 Ordinary Chondrites from the Dar Al Gani Region, Libya. 1; Noble Gases

    NASA Technical Reports Server (NTRS)

    Schultz, L.; Franke, L.; Welten, K. C.; Nishiizumi, K.; Jull, A. J. T.

    2003-01-01

    In the last decade thousands of meteorites have been recovered from hot deserts in the Sahara and Oman. One of the main meteorite concentration surfaces in the Sahara is the Dar al Gani plateau in Libya, which covers a total area of 8000 km2. More than 1000 meteorites have been reported from this area. The geological setting, meteorite pairings and the meteorite density of the Dar al Gani (DaG) field are described in more detail in [1]. In this work we report concentrations of the noble gas isotopes of He, Ne, Ar as well as 84Kr and 132Xe in 18 DaG meteorites. In a separate paper we will report the cosmogenic radionuclides [2]. We discuss the thermal history and cosmic-ray exposure (CRE) history of these meteorites, and evaluate the effects of the hot desert environment on the noble gas record.

  13. Advances in animal ecology from 3D-LiDAR ecosystem mapping.

    PubMed

    Davies, Andrew B; Asner, Gregory P

    2014-12-01

    The advent and recent advances of Light Detection and Ranging (LiDAR) have enabled accurate measurement of 3D ecosystem structure. Here, we review insights gained through the application of LiDAR to animal ecology studies, revealing the fundamental importance of structure for animals. Structural heterogeneity is most conducive to increased animal richness and abundance, and increased complexity of vertical vegetation structure is more positively influential compared with 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. To develop a better understanding of animal dynamics, future studies will benefit from considering 3D habitat effects in a wider variety of ecosystems and with more taxa. PMID:25457158

  14. Clustering and visualization of non-classified points from LiDAR data for helicopter navigation

    NASA Astrophysics Data System (ADS)

    Eisenkeil, Ferdinand; Schafhitzel, Tobias; Kühne, Uwe; Deussen, Oliver

    2014-06-01

    In this paper we propose a dynamic DBSCAN-based method to cluster and visualize unclassified and potential dangerous obstacles in data sets recorded by a LiDAR sensor. The sensor delivers data sets in a short time interval, so a spatial superposition of multiple data sets is created. We use this superposition to create clusters incrementally. Knowledge about the position and size of each cluster is used to fuse clusters and the stabilization of clusters within multiple time frames. Cluster stability is a key feature to provide a smooth and un-distracting visualization for the pilot. Only a few lines are indicating the position of threatening unclassified points, where a hazardous situation for the helicopter could happen, if it comes too close. Clustering and visualization form a part of an entire synthetic vision processing chain, in which the LiDAR points support the generation of a real-time synthetic view of the environment.

  15. Measuring and mapping forest wildlife habitat characteristics using LiDAR remote sensing and multi-sensor function

    NASA Astrophysics Data System (ADS)

    Hyde, Peter

    Managing forests for multiple, often competing uses is challenging; managing Sierra National Forest's fire regime and California spotted owl habitat is difficult and compounded by lack of information about habitat quality. Consistent and accurate measurements of forest structure will reduce uncertainties regarding the amount of habitat reduction or alteration that spotted owls can tolerate. Current methods of measuring spotted owl habitat are mostly field-based and emphasize the important of canopy cover. However, this is more because of convenience than because canopy cover is a definitive predictor of owl presence or fecundity. Canopy cover is consistently and accurately measured in the field using a moosehorn densitometer; comparable measurements can be made using airphoto interpretation or from examining satellite imagery, but the results are not consistent. LiDAR remote sensing can produce consistent and accurate measurements of canopy cover, as well as other aspects of forest structure (such as canopy height and biomass) that are known or thought to be at least as predictive as canopy cover. Moreover, LiDAR can be used to produce maps of forest structure rather than the point samples available from field measurements. However, LiDAR data sets are expensive and not available everywhere. Combining LiDAR with other, remote sensing data sets with less expensive, wall-to-wall coverage will result in broader scale maps of forest structure than have heretofore been possible; these maps can then be used to analyze spotted owl habitat. My work consists of three parts: comparison of LiDAR estimates of forest structure with field measurements, statistical fusion of LiDAR and other remote sensing data sets to produce broad scale maps of forest structure, and analysis of California spotted owl presence and fecundity as a function of LiDAR-derived canopy structure. I found that LiDAR was able to replicate field measurements accurately. Additionally, I was able to

  16. Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

    NASA Technical Reports Server (NTRS)

    Nelson, Ross; Naesset, Erik; Gobakken, T.; Gregoire, T.; Stahl, G.

    2009-01-01

    A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

  17. Quantitative study of tectonic geomorphology along Haiyuan fault based on airborne LiDAR

    USGS Publications Warehouse

    Chen, Tao; Zhang, Pei Zhen; Liu, Jing; Li, Chuan You; Ren, Zhi Kun; Hudnut, Kenneth W.

    2014-01-01

    High-precision and high-resolution topography are the fundamental data for active fault research. Light detection and ranging (LiDAR) presents a new approach to build detailed digital elevation models effectively. We take the Haiyuan fault in Gansu Province as an example of how LiDAR data may be used to improve the study of active faults and the risk assessment of related hazards. In the eastern segment of the Haiyuan fault, the Shaomayin site has been comprehensively investigated in previous research because of its exemplary tectonic topographic features. Based on unprecedented LiDAR data, the horizontal and vertical coseismic offsets at the Shaomayin site are described. The measured horizontal value is about 8.6 m, and the vertical value is about 0.8 m. Using prior dating ages sampled from the same location, we estimate the horizontal slip rate as 4.0 ± 1.0 mm/a with high confidence and define that the lower bound of the vertical slip rate is 0.4 ± 0.1 mm/a since the Holocene. LiDAR data can repeat the measurements of field work on quantifying offsets of tectonic landform features quite well. The offset landforms are visualized on an office computer workstation easily, and specialized software may be used to obtain displacement quantitatively. By combining precious chronological results, the fundamental link between fault activity and large earthquakes is better recognized, as well as the potential risk for future earthquake hazards.

  18. Evaluation of Landslide Mapping Techniques and LiDAR-based Conditioning Factors

    NASA Astrophysics Data System (ADS)

    Mahalingam, R.; Olsen, M. J.

    2014-12-01

    Landslides are a major geohazard, which result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping can help communities to plan and prepare for these damaging events. Mapping landslide susceptible locations using GIS and remote sensing techniques is gaining popularity in the past three decades. These efforts use a wide variety of procedures and consider a wide range of factors. Unfortunately, each study is often completed differently and independently of others. Further, the quality of the datasets used varies in terms of source, data collection, and generation, which can propagate errors or inconsistencies into the resulting output maps. Light detection and ranging (LiDAR) has proved to have higher accuracy in representing the continuous topographic surface, which can help minimize this uncertainty. The primary objectives of this paper are to investigate the applicability and performance of terrain factors in landslide hazard mapping, determine if LiDAR-derived datasets (slope, slope roughness, terrain roughness, stream power index and compound topographic index) can be used for predictive mapping without data representing other common landslide conditioning factors, and evaluate the differences in landslide susceptibility mapping using widely-used statistical approaches. The aforementioned factors were used to produce landslide susceptibility maps for a 140 km2 study area in northwest Oregon using six representative techniques: frequency ratio, weights of evidence, logistic regression, discriminant analysis, artificial neural network, and support vector machine. Most notably, the research showed an advantage in selecting fewer critical conditioning factors. The most reliable factors all could be derived from a single LiDAR DEM, reducing the need for laborious and costly data gathering. Most of the six techniques showed similar statistical results; however, ANN showed less accuracy for predictive mapping. Keywords : LiDAR

  19. A Comparative Study between Frequency-Modulated Continous Wave LADAR and Linear LiDAR

    NASA Astrophysics Data System (ADS)

    Massaro, R. D.; Anderson, J. E.; Nelson, J. D.; Edwards, J. D.

    2014-11-01

    Topographic Light Detection and Ranging (LiDAR) technology has advanced greatly in the past decade. Pulse repetition rates of terrestrial and airborne systems havemultiplied thus vastly increasing data acquisition rates. Geiger-mode and FLASH LiDAR have also become far more mature technologies. However, a new and relatively unknown technology is maturing rapidly: Frequency-Modulated Continuous Wave Laser Detection and Ranging (FMCW-LADAR). Possessing attributes more akin to modern radar systems, FMCWLADAR has the ability to more finely resolve objects separated by very small ranges. For tactical military applications (as described here), this can be a real advantage over single frequency, direct-detect systems. In fact, FMCW-LADAR can range resolve objects at 10-7 to 10-6 meter scales. FMCW-LADAR can also detect objects at greater range with less power. In this study, a FMCWLADAR instrument and traditional LiDAR instrument are compared. The co-located terrestrial scanning instruments were set up to perform simultaneous 3-D measurements of the given scene. Several targets were placed in the scene to expose the difference in the range resolution capabilities of the two instruments. The scans were performed at or nearly the same horizontal and vertical angular resolutions. It is demonstrated that the FMCW-LADAR surpasses the perfomance of the linear mode LiDAR scanner in terms of range resolution. Some results showing the maximum range acquisition are discussed but this was not studied in detail as the scanners' laser powers differed by a small amount. Applications and implications of this technology are also discussed.

  20. 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

  1. Topographic and Thermal Investigations of Active Pahoehoe Lava Flows Using Coupled LiDAR/FLIR Datasets

    NASA Astrophysics Data System (ADS)

    Crown, D. A.; Anderson, S. W.; Finnegan, D. C.; LeWinter, A. L.; Ramsey, M.

    2012-12-01

    Pahoehoe lava flows consist of multiple overlapping and interfingering lobes and exhibit morphologically diverse surfaces characterized by channels, smooth-surfaced sheets, and numerous, small networks of interconnected pahoehoe toes. In order to analyze the different pahoehoe emplacement regimes, we have acquired simultaneous high-resolution topographic and thermal measurements of advancing and inflating flow lobes at high temporal frequency. These datasets allow the creation of flow lobe maps at regular intervals during flow emplacement that document morphologic, thermal, and morphometric characteristics of individual pahoehoe elements (e.g., pahoehoe toes) as well as compound pahoehoe features (e.g., toe networks, channels with lateral levees). These datasets reveal patterns in flow behavior and provide quantitative documentation of flow emplacement processes. Field investigations were conducted in February and March, 2012 on tube-fed pahoehoe flows in the Puu Oo flow field, Kilauea Volcano, Hawaii. We utilized a ground-based, full-waveform scanning LiDAR and FLIR SC645 thermal infrared camera, supplemented by high-definition video and time-lapse photography. The LiDAR scanner is capable of acquiring rapid, successive scans with reproducible 5 mm resolution data at a rate of 300 kHz. The FLIR camera acquires calibrated thermal images in the 7.5 - 13 mm range; the object temperature range is -20°C to +2000°C, with a thermal sensitivity of <0.05°C at 30°C. An RTK GPS was used to acquire precise locations of scan positions and to georeference LiDAR point cloud data to real-world coordinates. The combined LiDAR/FLIR system provides rapid acquisition of high-resolution spatial and high-precision thermal datasets for advancing pahoehoe flows.

  2. 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.

  3. Abu Dhabi Basemap Update Using the LiDAR Mobile Mapping Technology

    NASA Astrophysics Data System (ADS)

    Alshaiba, Omar; Amparo Núñez-Andrés, M.; Lantada, Nieves

    2016-04-01

    Mobile LiDAR system provides a new technology which can be used to update geospatial information by direct and rapid data collection. This technology is faster than the traditional survey ways and has lower cost. Abu Dhabi Municipal System aims to update its geospatial system frequently as the government entities have invested heavily in GIS technology and geospatial data to meet the repaid growth in the infrastructure and construction projects in recent years. The Emirate of Abu Dhabi has witnessed a huge growth in infrastructure and construction projects in recent years. Therefore, it is necessary to develop and update its basemap system frequently to meet their own organizational needs. Currently, the traditional ways are used to update basemap system such as human surveyors, GPS receivers and controller (GPS assigned computer). Then the surveyed data are downloaded, edited and reviewed manually before it is merged to the basemap system. Traditional surveying ways may not be applicable in some conditions such as; bad weather, difficult topographic area and boundary area. This paper presents a proposed methodology which uses the Mobile LiDAR system to update basemap in Abu Dhabi by using daily transactions services. It aims to use and integrate the mobile LiDAR technology into the municipality's daily workflow such that it becomes the new standard cost efficiency operating procedure for updating the base-map in Abu Dhabi Municipal System. On another note, the paper will demonstrate the results of the innovated workflow for the base-map update using the mobile LiDAR point cloud and few processing algorithms.

  4. Single Pass LiDAR-derived Estimate of Site Productivity in Western Oregon

    NASA Astrophysics Data System (ADS)

    McAdam, E.; Hilker, T.; Waring, R. H.; Sousa, C. H. R. D.; Moura, Y. M.

    2014-12-01

    Accurate estimates of forest growth at different ages are essential to evaluate the effect of a changing climate and to adjust management practices accordingly. Most current approaches are spatially discrete and therefore unable to predict forest growth accurately across landscapes. While airborne LiDAR has been widely used in forestry, it can only estimate growth rates with repeated passes. In contrast, Landsat imagery records disturbances (at 30 m resolution) but is unable to measure changes in growth rates. Historical archives of Landsat imagery provided us a way of knowing when and where even-aged stands of Pseudotsuga menziesii (Douglas-fir) were cut and replanted. Since early growth rates are nearly linear with age, the height of dominant trees recorded in one pass by LiDAR yields a direct measure of growth and likely changes as stands age under recent climatic conditions. Process-based growth models are available to assess possible shifts in the growth rates of stands under a changing climate; the accuracy of such model predictions can be evaluated with additional LiDAR coverage. In this study we use the Physiological Principles Predicting Growth Model (3-PG) to estimate site index at the landscape level to predict site productivity based on the year of stand establishment obtained from Landsat, and one-pass airborne LiDAR measurement of forest height. We are monitoring forest plantations of known ages and with data on their current age we will calculate site index for 60 separate sites across western Oregon. The results of this study will allow us to create updated site index maps for the state of Oregon under varying climate scenarios.

  5. Mapping Vegetation Canopy Structure and Distribution for Great Smoky Mountains National Park Using LiDAR

    NASA Astrophysics Data System (ADS)

    Weiner, J.; Kumar, J.; Norman, S. P.

    2015-12-01

    A major challenge in forest management is the inaccessibility of large swaths of land, which makes accurate monitoring of forest change difficult. Remote sensing methods can help address this issue by allowing investigators to monitor remote or inaccessible regions using aerial or satellite-based platforms. However, most remote sensing methods do not provide a full three-dimensional (3D) description of the area. Rather, they return only a single elevation point or landcover description. Multiple-return LiDAR (Light Detection and Ranging) gathers data in a 3D point cloud, which allows forest managers to more accurately characterize and monitor changes in canopy structure and vegetation-type distribution. Our project used high-resolution aerial multiple-return LiDAR data to determine vegetation canopy structures and their spatial distribution in Great Smoky Mountains National Park. To ensure sufficient data density and to match LANDSAT resolution, we gridded the data into 30m x 30m cells. The LiDAR data points within each cell were then used to generate the vertical canopy structure for that cell. After vertical profiles had been created, we used a k-means cluster analysis algorithm to classify the landscape based on the canopy structure. The spatial distribution of distinct and unique canopy structures was mapped across the park and compared to a vegetation-type map to determine the correlation of canopy structure to vegetation types. Preliminary analysis conducted at a number of phenology sites maintained by the Great Smoky Mountains Institute at Tremont shows strong correspondence between canopy structure and vegetation type. However, more validation is needed in other regions of the park to establish this method as a reliable tool. LiDAR data has a unique ability to map full 3D structures of vegetation and the methods developed in this project offer an extensible tool for forest mapping and monitoring.

  6. 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.

  7. Road centerline extraction from airborne LiDAR point cloud based on hierarchical fusion and optimization

    NASA Astrophysics Data System (ADS)

    Hui, Zhenyang; Hu, Youjian; Jin, Shuanggen; Yevenyo, Yao Ziggah

    2016-08-01

    Road information acquisition is an important part of city informatization construction. Airborne LiDAR provides a new means of acquiring road information. However, the existing road extraction methods using LiDAR point clouds always decide the road intensity threshold based on experience, which cannot obtain the optimal threshold to extract a road point cloud. Moreover, these existing methods are deficient in removing the interference of narrow roads and several attached areas (e.g., parking lot and bare ground) to main roads extraction, thereby imparting low completeness and correctness to the city road network extraction result. Aiming at resolving the key technical issues of road extraction from airborne LiDAR point clouds, this paper proposes a novel method to extract road centerlines from airborne LiDAR point clouds. The proposed approach is mainly composed of three key algorithms, namely, Skewness balancing, Rotating neighborhood, and Hierarchical fusion and optimization (SRH). The skewness balancing algorithm used for the filtering was adopted as a new method for obtaining an optimal intensity threshold such that the "pure" road point cloud can be obtained. The rotating neighborhood algorithm on the other hand was developed to remove narrow roads (corridors leading to parking lots or sidewalks), which are not the main roads to be extracted. The proposed hierarchical fusion and optimization algorithm caused the road centerlines to be unaffected by certain attached areas and ensured the road integrity as much as possible. The proposed method was tested using the Vaihingen dataset. The results demonstrated that the proposed method can effectively extract road centerlines in a complex urban environment with 91.4% correctness and 80.4% completeness.

  8. 3D campus modeling using LiDAR point cloud data

    NASA Astrophysics Data System (ADS)

    Kawata, Yoshiyuki; Yoshii, Satoshi; Funatsu, Yukihiro; Takemata, Kazuya

    2012-10-01

    The importance of having a 3D urban city model is recognized in many applications, such as management offices of risk and disaster, the offices for city planning and developing and others. As an example of urban model, we reconstructed 3D KIT campus manually in this study, by utilizing airborne LiDAR point cloud data. The automatic extraction of building shapes was left in future work.

  9. Urban 3D GIS From LiDAR and digital aerial images

    NASA Astrophysics Data System (ADS)

    Zhou, Guoqing; Song, C.; Simmers, J.; Cheng, P.

    2004-05-01

    This paper presents a method, which integrates image knowledge and Light Detection And Ranging (LiDAR) point cloud data for urban digital terrain model (DTM) and digital building model (DBM) generation. The DBM is an Object-Oriented data structure, in which each building is considered as a building object, i.e., an entity of the building class. The attributes of each building include roof types, polygons of the roof surfaces, height, parameters describing the roof surfaces, and the LiDAR point array within the roof surfaces. Each polygon represents a roof surface of building. This type of data structure is flexible for adding other building attributes in future, such as texture information and wall information. Using image knowledge extracted, we developed a new method of interpolating LiDAR raw data into grid digital surface model (DSM) with considering the steep discontinuities of buildings. In this interpolation method, the LiDAR data points, which are located in the polygon of roof surfaces, first are determined, and then interpolation via planar equation is employed for grid DSM generation. The basic steps of our research are: (1) edge detection by digital image processing algorithms; (2) complete extraction of the building roof edges by digital image processing and human-computer interactive operation; (3) establishment of DBM; (4) generation of DTM by removing surface objects. Finally, we implement the above functions by MS VC++ programming. The outcome of urban 3D DSM, DTM and DBM is exported into urban database for urban 3D GIS.

  10. Characterizing active volcanic processes at Kilauea volcano using LiDAR scanning

    NASA Astrophysics Data System (ADS)

    LeWinter, A. L.; Finnegan, D. C.; Patrick, M. R.; Anderson, S. W.; Orr, T. R.

    2012-12-01

    Active craters and lava lakes evolve in response to a variety of volcanic processes. Quantifying those changes can be difficult or even impossible, for safety reasons, due to the technical limitations of sensors that require a minimum standoff distance. In recent years, advancements in ground-based Light Detection and Ranging (LiDAR) scanners and accessibility to these systems have enhanced our ability to capture data in a diversity of volcanic settings at the highest spatial and temporal resolutions yet seen. Moreover, advancements in full-waveform digitization have significantly improved the ability to acquire data in environments where ash, steam, and sulfur dioxide emissions have historically hampered efforts. Kilauea's ongoing summit eruption, which began in March 2008, has been characterized in part by the evolution of its vent into a 160-meter diameter collapse crater holding an active lava lake. This process has been documented in detail by field and webcam observations, but has not been accurately quantified. Our research focuses on acquiring repeat, high-resolution full-waveform LiDAR data throughout 2012 to monitor changes in the geometry of Kilauea's active lava lake and the crater to which it is confined. We collected LiDAR data in February and July 2012, with plans for an additional survey in October 2012. Our results show changes in the shape of the vent walls and the shape and level of the confined lava lake. Specifically, the LiDAR data has revealed 1) changes in the lava lake level, corresponding to tiltmeter observations of pressure fluctuations in the summit magma reservoir, 2) enlargement of the vent cavity, due to frequent rock falls, and 3) modifications to the lake size and surrounding lava ledges due to competing processes of accretion and collapse. The rapid acquisition of repeat, high-resolution topographic data enables researchers to more accurately characterize shape and volume changes involved in a range of eruptive systems, while

  11. NASA Goddards LiDAR, Hyperspectral and Thermal (G-LiHT) Airborne Imager

    NASA Technical Reports Server (NTRS)

    Cook, Bruce D.; Corp, Lawrence A.; Nelson, Ross F.; Middleton, Elizabeth M.; Morton, Douglas C.; McCorkel, Joel T.; Masek, Jeffrey G.; Ranson, Kenneth J.; Ly, Vuong; Montesano, Paul M.

    2013-01-01

    The combination of LiDAR and optical remotely sensed data provides unique information about ecosystem structure and function. Here, we describe the development, validation and application of a new airborne system that integrates commercial off the shelf LiDAR hyperspectral and thermal components in a compact, lightweight and portable system. Goddard's LiDAR, Hyperspectral and Thermal (G-LiHT) airborne imager is a unique system that permits simultaneous measurements of vegetation structure, foliar spectra and surface temperatures at very high spatial resolution (approximately 1 m) on a wide range of airborne platforms. The complementary nature of LiDAR, optical and thermal data provide an analytical framework for the development of new algorithms to map plant species composition, plant functional types, biodiversity, biomass and carbon stocks, and plant growth. In addition, G-LiHT data enhance our ability to validate data from existing satellite missions and support NASA Earth Science research. G-LiHT's data processing and distribution system is designed to give scientists open access to both low- and high-level data products (http://gliht.gsfc.nasa.gov), which will stimulate the community development of synergistic data fusion algorithms. G-LiHT has been used to collect more than 6,500 km2 of data for NASA-sponsored studies across a broad range of ecoregions in the USA and Mexico. In this paper, we document G-LiHT design considerations, physical specifications, instrument performance and calibration and acquisition parameters. In addition, we describe the data processing system and higher-level data products that are freely distributed under NASA's Data and Information policy.

  12. 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. PMID:27410085

  13. 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.

  14. Motion field estimation for a dynamic scene using a 3D LiDAR.

    PubMed

    Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

    2014-09-09

    This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively.

  15. Motion Field Estimation for a Dynamic Scene Using a 3D LiDAR

    PubMed Central

    Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

    2014-01-01

    This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively. PMID:25207868

  16. Phylogenetic relationships between four Salix L. species based on DArT markers.

    PubMed

    Przyborowski, Jerzy A; Sulima, Paweł; Kuszewska, Anna; Załuski, Dariusz; Kilian, Andrzej

    2013-12-11

    The objectives of this study were to evaluate the usefulness of DArT markers in genotypic identification of willow species and describe genetic relationships between four willow species: Salix viminalis, S. purpurea, S. alba and S. triandra. The experimental plant material comprised 53 willow genotypes of these four species, which are popularly grown in Poland. DArT markers seem to identify Salix species with a high degree of accuracy. As a result, the examined species were divided into four distinct groups which corresponded to the four analyzed species. In our study, we observed that S. triandra was very different genetically from the other species, including S. alba which is generally classified into the same subgenus of Salix. The above corroborates the findings of other authors who relied on molecular methods to reveal that the classification of S. triandra to the subgenus Salix was erroneous. The Principal Coordinate Analysis (PCoA) and the neighbor-joining dendrogram also confirmed the clear division of the studied willow genotypes into four clusters corresponding to individual species. This confirmed the usefulness of DArT markers in taxonomic analyses and identification of willow species.

  17. Assessment of human thermal perception in the hot-humid climate of Dar es Salaam, Tanzania

    NASA Astrophysics Data System (ADS)

    Ndetto, Emmanuel L.; Matzarakis, Andreas

    2016-06-01

    Dar es Salaam, Tanzania, is a typical African city along the Indian Ocean coast, and therefore an important urban area to examine human thermal perception in the hot-humid tropical climate. Earlier research on human bioclimate at Dar es Salaam indicated that heat stress prevails during the hot season from October to March, peaking between December and February, particularly the early afternoons. In order to assess the human thermal perception and adaptation, two popular places, one at an urban park and another at a beach environment, were selected and questionnaire surveys were conducted in August-September 2013 and January 2014, concurrently with local micro-meteorological measurements at survey locations. The thermal conditions were quantified in terms of the thermal index of the physiologically equivalent temperature (PET) using the micro-scale climate model RayMan. The thermal comfort range of human thermal comfort and the local thermal adaptive capacity were determined in respect to the thermal index by binning thermal sensation votes. The thermal comfort range was found to be well above that in temperate climates at about 23-31 °C of PET. The study could significantly contribute to urban planning in Dar es Salaam and other coastal cities in the tropics.

  18. Flood damage analysis: uncertainties for first floor elevation yielded from LiDAR data

    NASA Astrophysics Data System (ADS)

    Bodoque, Jose Maria; Aroca-Jimenez, Estefania; Guardiola-Albert, Carolina; Eguibar, Miguel Angel

    2016-04-01

    The use of high resolution ground-base light detection and ranging (LiDAR) datasets provide the spatial density and vertical precisión to obtain Digital Elevation Models (DEMs) highly accurate. As a result, reliability of flood damage analysis has been improved significantly, as accuracy of hydrodinamic model is increased. Additionally, an important error reduction also takes place in estimating first floor elevation, which is a critical parameter to determine structural and content damages in buildings. However, justlike any discrete measurement technique, LiDAR data contain object space ambiguities, especially in urban areas where the presence of buildings and the floodplain determines a highly complex landscape that is largely corrected by using data ancillory information based on breaklines. Here, we provide an uncertainty assessment based on: a) improvement of DEMs to be used in flood damage based on adding breaklines as ancillary information; b) geostatistical estimation of errors in DEMs; c) implementing a 2D hydrodynamic model considering the 500 yr flood return period; and d) determining first floor elevation uncertainty. As main conclusion of this study, worth to outline the need of processing raw LiDAR in order to generate efficient and high-quality DEMs that minimize the uncertainty of determining first-floor elevation and, as a result, reliability of flood damage assessment is increased.

  19. Range determination for generating point clouds from airborne small footprint LiDAR waveforms.

    PubMed

    Qin, Yuchu; Vu, Tuong Thuy; Ban, Yifang; Niu, Zheng

    2012-11-01

    This paper presents a range determination approach for generating point clouds from small footprint LiDAR waveforms. Waveform deformation over complex terrain area is simulated using convolution. Drift of the peak center position is analyzed to identify the first echo returned by the illuminated objects in the LiDAR footprint. An approximate start point of peak in the waveform is estimated and adopted as the indicator of range calculation; range correction method is proposed to correct pulse widening over complex terrain surface. The experiment was carried out on small footprint LiDAR waveform data acquired by RIEGL LMS-Q560. The results suggest that the proposed approach generates more points than standard commercial products; based on field measurements, a comparative analysis between the point clouds generated by the proposed approach and the commercial software GeocodeWF indicates that: 1). the proposed approach obtained more accurate tree heights; 2). smooth surface can be achieved with low standard deviation. In summary, the proposed approach provides a satisfactory solution for range determination in estimating 3D coordinate values of point clouds, especially for correcting range information of waveforms containing deformed peaks.

  20. An Efficient Method for Automatic Road Extraction Based on Multiple Features from LiDAR Data

    NASA Astrophysics Data System (ADS)

    Li, Y.; Hu, X.; Guan, H.; Liu, P.

    2016-06-01

    The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D) points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1) road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2) local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3) hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform) proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for "Urban Classification and 3D Building Reconstruction" project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.

  1. Geodetic imaging with airborne LiDAR: the Earth's surface revealed.

    PubMed

    Glennie, C L; Carter, W E; Shrestha, R L; Dietrich, W E

    2013-08-01

    The past decade has seen an explosive increase in the number of peer reviewed papers reporting new scientific findings in geomorphology (including fans, channels, floodplains and landscape evolution), geologic mapping, tectonics and faulting, coastal processes, lava flows, hydrology (especially snow and runoff routing), glaciers and geo-archaeology. A common genesis of such findings is often newly available decimeter resolution 'bare Earth' geodetic images, derived from airborne laser swath mapping, a.k.a. airborne LiDAR, observations. In this paper we trace nearly a half century of advances in geodetic science made possible by space age technology, such as the invention of short-pulse-length high-pulse-rate lasers, solid state inertial measurement units, chip-based high speed electronics and the GPS satellite navigation system, that today make it possible to map hundreds of square kilometers of terrain in hours, even in areas covered with dense vegetation or shallow water. To illustrate the impact of the LiDAR observations we present examples of geodetic images that are not only stunning to the eye, but help researchers to develop quantitative models explaining how terrain evolved to its present form, and how it will likely change with time. Airborne LiDAR technology continues to develop quickly, promising ever more scientific discoveries in the years ahead. PMID:23828665

  2. Geodetic imaging with airborne LiDAR: the Earth's surface revealed.

    PubMed

    Glennie, C L; Carter, W E; Shrestha, R L; Dietrich, W E

    2013-08-01

    The past decade has seen an explosive increase in the number of peer reviewed papers reporting new scientific findings in geomorphology (including fans, channels, floodplains and landscape evolution), geologic mapping, tectonics and faulting, coastal processes, lava flows, hydrology (especially snow and runoff routing), glaciers and geo-archaeology. A common genesis of such findings is often newly available decimeter resolution 'bare Earth' geodetic images, derived from airborne laser swath mapping, a.k.a. airborne LiDAR, observations. In this paper we trace nearly a half century of advances in geodetic science made possible by space age technology, such as the invention of short-pulse-length high-pulse-rate lasers, solid state inertial measurement units, chip-based high speed electronics and the GPS satellite navigation system, that today make it possible to map hundreds of square kilometers of terrain in hours, even in areas covered with dense vegetation or shallow water. To illustrate the impact of the LiDAR observations we present examples of geodetic images that are not only stunning to the eye, but help researchers to develop quantitative models explaining how terrain evolved to its present form, and how it will likely change with time. Airborne LiDAR technology continues to develop quickly, promising ever more scientific discoveries in the years ahead.

  3. Range determination for generating point clouds from airborne small footprint LiDAR waveforms.

    PubMed

    Qin, Yuchu; Vu, Tuong Thuy; Ban, Yifang; Niu, Zheng

    2012-11-01

    This paper presents a range determination approach for generating point clouds from small footprint LiDAR waveforms. Waveform deformation over complex terrain area is simulated using convolution. Drift of the peak center position is analyzed to identify the first echo returned by the illuminated objects in the LiDAR footprint. An approximate start point of peak in the waveform is estimated and adopted as the indicator of range calculation; range correction method is proposed to correct pulse widening over complex terrain surface. The experiment was carried out on small footprint LiDAR waveform data acquired by RIEGL LMS-Q560. The results suggest that the proposed approach generates more points than standard commercial products; based on field measurements, a comparative analysis between the point clouds generated by the proposed approach and the commercial software GeocodeWF indicates that: 1). the proposed approach obtained more accurate tree heights; 2). smooth surface can be achieved with low standard deviation. In summary, the proposed approach provides a satisfactory solution for range determination in estimating 3D coordinate values of point clouds, especially for correcting range information of waveforms containing deformed peaks. PMID:23187409

  4. Automatic extraction of highway light poles and towers from mobile LiDAR data

    NASA Astrophysics Data System (ADS)

    Yan, Wai Yeung; Morsy, Salem; Shaker, Ahmed; Tulloch, Mark

    2016-03-01

    Mobile LiDAR has been recently demonstrated as a viable technique for pole-like object detection and classification. Despite that a desirable accuracy (around 80%) has been reported in the existing studies, majority of them were presented in the street level with relatively flat ground and very few of them addressed how to extract the entire pole structure from the ground or curb surface. Therefore, this paper attempts to fill the research gap by presenting a workflow for automatic extraction of light poles and towers from mobile LiDAR data point cloud, with a particular focus on municipal highway. The data processing workflow includes (1) an automatic ground filtering mechanism to separate aboveground and ground features, (2) an unsupervised clustering algorithm to cluster the aboveground data point cloud, (3) a set of decision rules to identify and classify potential light poles and towers, and (4) a least-squares circle fitting algorithm to fit the circular pole structure so as to remove the ground points. The workflow was tested with a set of mobile LiDAR data collected for a section of highway 401 located in Toronto, Ontario, Canada. The results showed that the proposed method can achieve an over 91% of detection rate for five types of light poles and towers along the study area.

  5. Sociocultural factors that reduce risks of homicide in Dar es Salaam: a case control study

    PubMed Central

    Kibusi, Stephen Matthew; Ohnishi, Mayumi; Outwater, Anne; Seino, Kaoruko; Kizuki, Masashi; Takano, Takehito

    2013-01-01

    Objectives This study was performed to examine the potential contributions of sociocultural activities to reduce risks of death by homicide. Methods This study was designed as a case control study. Relatives of 90 adult homicide victims in Dar es Salaam Region, Tanzania, in 2005 were interviewed. As controls, 211 participants matched for sex and 5-year age group were randomly selected from the same region and interviewed regarding the same contents. Results Bivariate analysis revealed significant differences between victims and controls regarding educational status, occupation, family structure, frequent heavy drinking, hard drug use and religious attendance. Conditional logistic regression analysis indicated that the following factors were significantly related to not becoming victims of homicide: being in employment (unskilled labour: OR=0.04, skilled labour: OR=0.07, others: OR=0.04), higher educational status (OR=0.02), residence in Dar es Salaam after becoming an adult (compared with those who have resided in Dar es Salaam since birth: OR=3.95), living with another person (OR=0.07), not drinking alcohol frequently (OR=0.15) and frequent religious service attendance (OR=0.12). Conclusions Frequent religious service attendance, living in the same place for a long time and living with another person were shown to be factors that contribute to preventing death by homicide, regardless of place of residence and neighbourhood environment. Existing non-structural community resources and social cohesive networks strengthen individual and community resilience against violence. PMID:23322260

  6. Downstream hydraulic geometry relationships: Gathering reference reach-scale width values from LiDAR

    NASA Astrophysics Data System (ADS)

    Sofia, G.; Tarolli, P.; Cazorzi, F.; Dalla Fontana, G.

    2015-12-01

    This paper examines the ability of LiDAR topography to provide reach-scale width values for the analysis of downstream hydraulic geometry relationships along some streams in the Dolomites (northern Italy). Multiple reach-scale dimensions can provide representative geometries and statistics characterising the longitudinal variability in the channel, improving the understanding of geomorphic processes across networks. Starting from the minimum curvature derived from a LiDAR DTM, the proposed algorithm uses a statistical approach for the identification of the scale of analysis, and for the automatic characterisation of reach-scale bankfull widths. The downstream adjustment in channel morphology is then related to flow parameters (drainage area and stream power). With the correct planning of a LiDAR survey, uncertainties in the procedure are principally due to the resolution of the DTM. The outputs are in general comparable in quality to field survey measurements, and the procedure allows the quick comparison among different watersheds. The proposed automatic approach could improve knowledge about river systems with highly variable widths, and about systems in areas covered by vegetation or inaccessible to field surveys. With proven effectiveness, this research could offer an interesting starting point for the analysis of differences between watersheds, and to improve knowledge about downstream channel adjustment in relation, for example, to scale and landscape forcing (e.g. sediment transport, tectonics, lithology, climate, geomorphology, and anthropic pressure).

  7. Supporting Indonesia's National Forest Monitoring System with LiDAR Observations

    NASA Astrophysics Data System (ADS)

    Hagen, S. C.

    2015-12-01

    Scientists at Applied GeoSolutions, Jet Propulsion Laboratory, Winrock International, and the University of New Hampshire are working with the government of Indonesia to enhance the National Forest Monitoring System in Kalimantan, Indonesia. The establishment of a reliable, transparent, and comprehensive NFMS has been limited by a dearth of relevant data that are accurate, low-cost, and spatially resolved at subnational scales. In this NASA funded project, we are developing, evaluating, and validating several critical components of a NFMS in Kalimantan, Indonesia, focusing on the use of LiDAR and radar imagery for improved carbon stock and forest degradation information. Applied GeoSolutions and the University of New Hampshire have developed an Open Source Software package to process large amounts LiDAR data quickly, easily, and accurately. The Open Source project is called lidar2dems and includes the classification of raw LAS point clouds and the creation of Digital Terrain Models (DTMs), Digital Surface Models (DSMs), and Canopy Height Models (CHMs). Preliminary estimates of forest structure and forest damage from logging from these data sets support the idea that comprehensive, well documented, freely available software for processing LiDAR data can enable countries such as Indonesia to cost effectively monitor their forests with high precision.

  8. [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.

  9. 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

  10. Hospital Charges of Potentially Preventable Pediatric Hospitalizations

    PubMed Central

    Lu, Sam; Kuo, Dennis Z.

    2014-01-01

    Objectives Reducing the number of preventable hospitalizations represents a possible source of healthcare savings. However, the current literature lacks a description of the extent of potentially preventable pediatric hospitalizations. The study objectives are to (1) identify the charges and (2) demographic characteristics associated with potentially preventable pediatric hospitalizations. Methods Secondary analysis of the 2006 Kids’ Inpatient Database (weighted N=7,558,812). ICD-9-CM codes for 16 previously validated pediatric ambulatory care-sensitive (ACS) conditions identified potentially preventable hospitalizations; seven additional conditions reflected updated care guidelines. Outcome variables included number of admissions, hospitalization days, and hospital charges. Demographic and diagnostic variables associated with an ACS condition were compared with regression analyses using appropriate person-level weights. Results Pediatric ACS hospitalizations totaled $4.05B in charges and 1,087,570 hospitalization days in 2006. Two respiratory conditions—asthma and bacterial pneumonia—comprised 48.4% of ACS hospital charges and 46.7% of ACS hospitalization days. In multivariate analysis, variables associated with an ACS condition included: male gender (OR: 1.10; 95% CI: 1.07–1.13); race/ethnicity of black (OR: 1.22; 95% CI: 1.16–1.27) or Hispanic (OR: 1.12; 95% CI: 1.06–1.18); and emergency department (ED) as admission source (OR: 1.37; 95% CI: 1.27–1.48). Conclusions Respiratory conditions comprised the largest proportion of potentially preventable pediatric hospitalizations, totaling as much as $1.96B in hospital charges. Children hospitalized with an ACS condition tend to be male, non-white, and admitted through the ED. Future research to prevent pediatric hospitalizations should examine targeted interventions in the primary care setting, specifically around respiratory conditions and minority populations. PMID:22922047

  11. Mobile LiDAR Measurement for Aerosol Investigation in South-Central Hebei, China

    NASA Astrophysics Data System (ADS)

    qin, kai; Wu, Lixin; Zheng, Yunhui; Wong Man, Sing; Wang, Runfeng; Hu, Mingyu; Lang, Hongmei; Wang, Luyao; Bai, Yang; Rao, Lanlan

    2016-04-01

    With the rapid industrialization and urbanization in China during the last decades, the increasing anthropogenic pollutant emissions have significantly caused serious air pollution problems which are adversely influencing public health. Hebei is one of the most air polluted provinces in China. In January 2013, an extremely severe and persistent haze episode with record-breaking PM2.5 outbreak affecting hundreds of millions of people occurred over eastern and northern China. During that haze episode, 7 of the top 10 most polluted cities in China were located in the Hebei Province according to the report of China's Ministry of Environmental Protection. To investigate and the spatial difference and to characterize the vertical distribution of aerosol in different regions of south-central Hebei, mobile measurements were carried out using a mini micro pulse LiDAR system (model: MiniMPL) in March 2014. The mobile LiDAR kit consisting of a MiniMPL, a vibration reduction mount, a power inverter, a Windows surface tablet and a GPS receiver were mounted in a car watching though the sunroof opening. For comparison, a fixed measurement using a traditional micro pulse LiDAR system (model: MPL-4B) was conducted simultaneously in Shijiazhuang, the capital of Hebei Province. The equipped car was driven from downtown Shijiazhuang by way of suburban and rural area to downtown Cangzhou, Handan, and Baoding respectively at almost stable speed around 100Km per hour along different routes which counted in total more than 1000Km. The results can be summarized as: 1) the spatial distribution of total aerosol optical depth along the measurement routes in south-central Hebei was controlled by local terrain and population in general, with high values in downtown and suburban in the plain areas, and low values in rural areas along Taihang mountain to the west and Yan mountain to the north; 2) obviously high AODs were obtained at roads crossing points, inside densely populated area and nearby

  12. Classification and Characterization of Neotropical Rainforest Vegetation from Hyperspectral and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Crawford, M. M.; Prasad, S.; Jung, J.; Yang, H.; Zhang, Y.

    2013-12-01

    Mapping species and forest vertical structure at regional, continental, and global scale is of increasing importance for climate science and decision support systems. Remote sensing technologies have been widely utilized to achieve this goal since they help overcome limitations of the direct and indirect measurement approaches. While the use of multi-sensor data for characterizing forest structure has gained significant attention in recent years, research on the integration of full waveform LiDAR and hyperspectral data for a) classification and b) characterization of vegetation structure has been limited. Given sufficient labeled ground reference samples, supervised learning methods have evolved to effectively classify data in a high dimensional feature space. However, it is expensive and time-consuming to obtain labeled data, although the very high dimensionality of feature spaces from hyperspectral and LiDAR inputs make it difficult to design reliable classifiers with a limited quantity of labeled data. Therefore, it is important to concentrate on developing training data sets which are the most 'informative' and 'useful' for the classification task. Active learning (AL) was developed in the machine learning community, and has been demonstrated to be useful for classification of remote sensing data. In the active learning framework, classifiers are initially trained on a very limited pool of training samples, but additional informative and representative samples are identified from the abundant unlabeled data, labeled, and then inducted into this pool, thereby growing the training dataset in a systematic way. The goal is to choose data points such that a more accurate classification boundary is learned. We propose a novel Multi-kernel Active Learning (MKL-AL) approach that incorporates features from multiple sensors with an automatically optimized kernel composite ¬function, and kernel parameters are selected intelligently during the AL learning process. The

  13. Hospital Library Administration.

    ERIC Educational Resources Information Center

    Cramer, Anne

    The objectives of a hospital are to improve patient care, while the objectives of a hospital library are to improve services to the staff which will support their efforts. This handbook dealing with hospital administration is designed to aid the librarian in either implementing a hospital library, or improving services in an existing medical…

  14. Hospital marketing revisited.

    PubMed

    Costello, M M

    1987-05-01

    With more hospitals embracing the marketing function in their organizational management over the past decade, hospital marketing can no longer be considered a fad. However, a review of hospital marketing efforts as reported in the professional literature indicates that hospitals must pay greater attention to the marketing mix elements of service, price and distribution channels as their programs mature.

  15. Measuring Rural Hospital Quality

    ERIC Educational Resources Information Center

    Moscovice, Ira; Wholey, Douglas R.; Klingner, Jill; Knott, Astrid

    2004-01-01

    Increased interest in the measurement of hospital quality has been stimulated by accrediting bodies, purchaser coalitions, government agencies, and other entities. This paper examines quality measurement for hospitals in rural settings. We seek to identify rural hospital quality measures that reflect quality in all hospitals and that are sensitive…

  16. 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

  17. LESTO: an Open Source GIS-based toolbox for LiDAR analysis

    NASA Astrophysics Data System (ADS)

    Franceschi, Silvia; Antonello, Andrea; Tonon, Giustino

    2015-04-01

    During the last five years different research institutes and private companies stared to implement new algorithms to analyze and extract features from LiDAR data but only a few of them also created a public available software. In the field of forestry there are different examples of software that can be used to extract the vegetation parameters from LiDAR data, unfortunately most of them are closed source (even if free), which means that the source code is not shared with the public for anyone to look at or make changes to. In 2014 we started the development of the library LESTO (LiDAR Empowered Sciences Toolbox Opensource): a set of modules for the analysis of LiDAR point cloud with an Open Source approach with the aim of improving the performance of the extraction of the volume of biomass and other vegetation parameters on large areas for mixed forest structures. LESTO contains a set of modules for data handling and analysis implemented within the JGrassTools spatial processing library. The main subsections are dedicated to 1) preprocessing of LiDAR raw data mainly in LAS format (utilities and filtering); 2) creation of raster derived products; 3) flight-lines identification and normalization of the intensity values; 4) tools for extraction of vegetation and buildings. The core of the LESTO library is the extraction of the vegetation parameters. We decided to follow the single tree based approach starting with the implementation of some of the most used algorithms in literature. These have been tweaked and applied on LiDAR derived raster datasets (DTM, DSM) as well as point clouds of raw data. The methods range between the simple extraction of tops and crowns from local maxima, the region growing method, the watershed method and individual tree segmentation on point clouds. The validation procedure consists in finding the matching between field and LiDAR-derived measurements at individual tree and plot level. An automatic validation procedure has been developed

  18. Seagrass Identification Using High-Resolution 532nm Bathymetric LiDAR and Hyperspectral Imagery

    NASA Astrophysics Data System (ADS)

    Pan, Z.; Prasad, S.; Starek, M. J.; Fernandez Diaz, J. C.; Glennie, C. L.; Carter, W. E.; Shrestha, R. L.; Singhania, A.; Gibeaut, J. C.

    2013-12-01

    Seagrass provides vital habitat for marine fisheries and is a key indicator species of coastal ecosystem vitality. Monitoring seagrass is therefore an important environmental initiative, but measuring details of seagrass distribution over large areas via remote sensing has proved challenging. Developments in airborne bathymetric light detection and ranging (LiDAR) provide great potential in this regard. Traditional bathymetric LiDAR systems have been limited in their ability to map within the shallow water zone (< 1 m) where seagrass is typically present due to limitations in receiver response and laser pulse length. Emergent short-pulse width bathymetric LiDAR sensors and waveform processing algorithms enable depth measurements in shallow water environments previously inaccessible. This 3D information of the benthic layer can be applied to detect seagrass and characterize its distribution. Researchers with the National Center for Airborne Laser Mapping (NCALM) at the University of Houston (UH) and the Coastal and Marine Geospatial Sciences Lab (CMGL) of the Harte Research Institute at Texas A&M University-Corpus Christi conducted a coordinated airborne and boat-based survey of the Redfish Bay State Scientific Area as part of a collaborative study to investigate the capabilities of bathymetric LiDAR and hyperspectral imaging for seagrass mapping. Redfish Bay, located along the middle Texas coast of the Gulf of Mexico, is a state scientific area designated for the purpose of protecting and studying native seagrasses. Redfish Bay is part of the broader Coastal Bend Bays estuary system recognized by the US Environmental Protection Agency (EPA) as a national estuary of significance. For this survey, UH acquired high-resolution discrete-return and full-waveform bathymetric data using their Optech Aquarius 532 nm green LiDAR. In a separate flight, UH collected 2 sets of hyperspectral imaging data (1.2-m pixel resolution and 72 bands, and 0.6m pixel resolution and 36

  19. 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.

  20. 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, L.

    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.

  1. 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).

  2. Similarity and Complementarity of Airborne and Terrestrial LiDAR Data in High Mountain Regions

    NASA Astrophysics Data System (ADS)

    Kamp, Nicole; Glira, Philipp; Pfeifer, Norbert

    2013-04-01

    Glacier melt and a consequential increased sediment transport (erosion, transportation and accumulation) in high mountain regions are causing a frequent occurrence of geomorphic processes such as landslides and other natural hazards. These effects are investigated at the Gepatschferner (Kaunertal, Oetztal Alps, Tyrol), the second largest glacier in Austria, in the PROSA project (Catholic University Eichstätt - Ingolstadt, Vienna University of Technology, Friedrich Alexander University Erlangen-Nürnberg, Martin-Luther-University Halle-Wittenberg, University of Innsbruck, Munich University of Technology). To monitor these geomorphic processes, data with a very high spatial and very high temporally accuracy and resolution are needed. For this purpose multi-temporal terrestrial and aerial laser scanning data are acquired, processed and analysed. Airborne LiDAR data are collected with a density of 10 points/m² over the whole study area of the glacier and its foreland. Terrestrial LiDAR data are gathered to complement and improve the airborne LiDAR data. The different viewing geometry results in differences between airborne and terrestrial data. Very steep slopes and rock faces (around 90°, depending on the viewing direction) are not visible from the airborne view point. On the other hand, terrestrial viewpoints exhibit shadows for areas above the scanner position and in viewing direction behind vertical or steep faces. In addition, the density of terrestrial data is varying strongly, but has for most of the covered area a much higher level of detail than the airborne dataset. A small temporal baseline is also inevitable and may cause differences between acquisition of airborne and terrestrial data. The goal of this research work is to develop a method for merging airborne and terrestrial LiDAR data. One prerequisite for merging is the identification of areas which are measurements of the same physical surface in either data set. This allows a transformation of the

  3. Hospitable Classrooms: Biblical Hospitality and Inclusive Education

    ERIC Educational Resources Information Center

    Anderson, David W.

    2011-01-01

    This paper contributes to a Christian hermeneutic of special education by suggesting the biblical concept of hospitality as a necessary characteristic of classroom and school environments in which students with disabilities and other marginalized students can be effectively incorporated into the body of the classroom. Christian hospitality, seen…

  4. High-Resolution LiDAR Topography of the Plate-Boundary Faults in Northern California

    NASA Astrophysics Data System (ADS)

    Prentice, C. S.; Phillips, D. A.; Furlong, K. P.; Brown, A.; Crosby, C. J.; Bevis, M.; Shrestha, R.; Sartori, M.; Brocher, T. M.; Brown, J.

    2007-12-01

    GeoEarthScope acquired more than 1500 square km of airborne LiDAR data in northern California, providing high-resolution topographic data of most of the major strike-slip faults in the region. The coverage includes the San Andreas Fault from its northern end near Shelter Cove to near Parkfield, as well as the Rodgers Creek, Maacama, Calaveras, Green Valley, Paicines, and San Gregorio Faults. The Hayward fault was added with funding provided by the US Geological Survey, the City of Berkeley, and the San Francisco Public Utilities Commission. Data coverage is typically one kilometer in width, centered on the fault. In areas of particular fault complexity the swath width was increased to two kilometers, and in selected areas swath width is as wide as five kilometers. A five-km-wide swath was flown perpendicular to the plate boundary immediately south of Cape Mendocino to capture previously unidentified faults and to understand off-fault deformation associated with the transition zone between the transform margin and the Cascadia subduction zone. The data were collected in conjunction with an intensive GPS campaign designed to improve absolute data accuracy and provide quality control. Data processing to classify the LiDAR point data by return type allows users to filter out vegetation and produce high-resolution DEMs of the ground surface beneath forested regions, revealing geomorphic features along and adjacent to the faults. These data will allow more accurate mapping of fault traces in regions where the vegetation canopy has hampered this effort in the past. In addition, the data provide the opportunity to locate potential sites for detailed paleoseismic studies aimed at providing slip rates and event chronologies. The GeoEarthScope LiDAR data will be made available via an interactive data distribution and processing workflow currently under development.

  5. Investigation on the contribution of LiDAR data in 3D cadastre

    NASA Astrophysics Data System (ADS)

    Giannaka, Olga; Dimopoulou, Efi; Georgopoulos, Andreas

    2014-08-01

    The existing 2D cadastral systems worldwide cannot provide a proper registration and representation of the land ownership rights, restrictions and responsibilities in a 3D context, which appear in our complex urban environment. Ιn such instances, it may be necessary to consider the development of a 3D Cadastre in which proprietary rights acquire appropriate three-dimensional space both above and below conventional ground level. Such a system should contain the topology and the coordinates of the buildings' outlines and infrastructure. The augmented model can be formed as a full 3D Cadastre, a hybrid Cadastre or a 2D Cadastre with 3D tags. Each country has to contemplate which alternative is appropriate, depending on the specific situation, the legal framework and the available technical means. In order to generate a 3D model for cadastral purposes, a system is required which should be able to exploit and represent 3D data such as LiDAR, a remote sensing technology which acquires three-dimensional point clouds that describe the earth's surface and the objects on it. LiDAR gives a direct representation of objects on the ground surface and measures their coordinates by analyzing the reflecting light. Moreover, it provides very accurate position and height information, although direct information about the objects' geometrical shape is not conveyed. In this study, an experimental implementation of 3D Cadastre using LiDAR data is developed, in order to investigate if this information can satisfy the specifications that are set for the purposes of the Hellenic Cadastre. GIS tools have been used for analyzing DSM and true orthophotos of the study area. The results of this study are presented and evaluated in terms of usability and efficiency.

  6. LiDAR-based volume assessment of the origin of the Wadena drumlin field, Minnesota, USA

    NASA Astrophysics Data System (ADS)

    Sookhan, Shane; Eyles, Nick; Putkinen, Niko

    2016-06-01

    The Wadena drumlin field (WDF; ~ 7500 km2) in west-central Minnesota, USA, is bordered along its outer extremity by the till-cored Alexandria moraine marking the furthest extent of the southwesterly-flowing Wadena ice lobe at c. 15,000 kyr BP. Newly available high-resolution Light Detection and Ranging (LiDAR) data reveal new information regarding the number, morphology and extent of streamlined bedforms in the WDF. In addition, a newly-developed quantitative methodology based on relief curvature analysis of LiDAR elevation-based raster data is used to evaluate sediment volumes represented by the WDF and its bounding end moraine. These data are used to evaluate models for the origin of drumlins. High-resolution LiDAR-based mapping doubles the streamlined footprint of the Wadena Lobe to ~ 16,500 km2 increases the number of bedforms from ~ 2000 to ~ 6000, and most significantly, reclassifies large numbers of bedforms mapped previously as 'drumlins' as 'mega-scale glacial lineations' (MSGLs), indicating that the Wadena ice lobe experienced fast ice flow. The total volume of sediment in the Alexandria moraine is ~ 71-110 km3, that in the drumlins and MSGLs is ~ 2.83 km3, and the volume of swales between these bedforms is ~ 74.51 km3. The moraine volume is equivalent to a till layer 6.8 m thick across the entire bed of the Wadena lobe, suggesting drumlinization and moraine formation were accompanied by widespread lowering of the bed. This supports the hypothesis that drumlins and MSGLs are residual erosional features carved from a pre-existing till; swales represent 'missing sediment' that was eroded subglacially and advected downglacier to build the Alexandria Moraine during fast ice flow. Alternatively, the relatively small volume of sediment represented by subglacial bedforms indicates they could have formed rapidly by depositional processes.

  7. Fusing Hyperspectral and LiDAR data from CAO-VSWIR for Increased Data Dimensionality

    NASA Astrophysics Data System (ADS)

    Knapp, D. E.; Asner, G. P.; Boardman, J. W.; Kennedy-Bowdoin, T.; Eastwood, M.; Anderson, C.; Martin, R. E.; Green, R. O.

    2012-12-01

    The use of multi-sensor platforms for scientific data collection requires precise co-location in order to gain maximum data dimensionality for Earth system research. The different types of collection mechanisms of the sensors (e.g., scanning and pushbroom) can make it difficult to precisely match data from multiple sensors, even when the sensors are flown on the same aircraft at the same time. To overcome these problems, the Carnegie Airborne Observatory (CAO) AToMS sensor suite uses a method that maximizes the match between the Light Detection and Ranging (LiDAR), Visible-to-Near Infrared (VNIR), and Visible-to-Shortwave Infrared (VSWIR) sensors. This is done by generating an intensity image from the LiDAR data that serves as a base on which the spectrometers (VNIR and VSWIR) are matched using ground control points (GCPs). To do so, we employ the use of automated tie point matching in the overlap regions of the spectrometers to improve the co-location between flightlines. The combination of the GCPs and tie points produce data that is used to build camera models for the VNIR and VSWIR spectrometers such that they will match the LiDAR data. The result produces a matched hyper-dimensional data set with great scientific information content. We compare the data dimensionality of two contrasting scenes - a built environment at Stanford University and a lowland tropical forest in Amazonia. Principal components analysis revealed 336 dimensions (degrees of freedom) in the Stanford case, and 218 dimensions in the Amazon. The Amazon case presents what could be the highest level of remotely sensed data dimensionality ever reported for a forested ecosystem. Simulated misalignment of data streams reduced the effective information content by up to 48%, highlighting the critical role of achieving high precision when undertaking multi-sensor fusion. The instrumentation and methods described here are a pathfinder for future airborne applications undertaken by the National

  8. Horizontal geometrical reaction time model for two-beam nacelle LiDARs

    NASA Astrophysics Data System (ADS)

    Beuth, Thorsten; Fox, Maik; Stork, Wilhelm

    2015-06-01

    Wind energy is one of the leading sustainable energies. To attract further private and state investment in this technology, a broad scaled drop of the cost of energy has to be enforced. There is a trend towards using Laser Doppler Velocimetry LiDAR systems for enhancing power output and minimizing downtimes, fatigue and extreme forces. Since most used LiDARs are horizontally setup on a nacelle and work with two beams, it is important to understand the geometrical configuration which is crucial to estimate reaction times for the actuators to compensate wind gusts. In the beginning of this article, the basic operating modes of wind turbines are explained and the literature on wind behavior is analyzed to derive specific wind speed and wind angle conditions in relation to the yaw angle of the hub. A short introduction to the requirements for the reconstruction of the wind vector length and wind angle leads to the problem of wind shear detection of angled but horizontal homogeneous wind fronts due to the spatial separation of the measuring points. A distance is defined in which the wind shear of such homogeneous wind fronts is not present which is used as a base to estimate further distance calculations. The reaction time of the controller and the actuators are having a negative effect on the effective overall reaction time for wind regulation as well. In the end, exemplary calculations estimate benefits and disadvantages of system parameters for wind gust regulating LiDARs for a wind turbine of typical size. An outlook shows possible future improvements concerning the vertical wind behavior.

  9. The offshore wind resources assessment application of floating LiDAR in the Taiwan Strait

    NASA Astrophysics Data System (ADS)

    Hsuan, Chung-Yao; Wu, Yu-Ting; Lin, Ta-Hui

    2015-04-01

    Wind and wave measurements of a Floating LiDAR (Light Detection And Ranging) Device (FLD) are performed on the site of Fuhai Offshore Wind Farm in the Taiwan Strait. The location of the deployment is situated 10 kilometers off-coast of Changhua County, and the anchored water depth is 25 meters. It is the very first time in Asia Pacific Region to use such device for tasks of offshore wind and wave measurement. Six range gate heights were set at 55m, 71m, 90m, 110m, 150m and 200m from the FLD sensor lens. Wind speeds and wind directions were measured by a remote sensing technology. Wave heights and periods were also measured by the buoy wave sensor. A validation campaign of NCKU WindSentinel has performed by a portable LiDAR (WINDCUBE v2) at Hsing-Da Harbor in the south of Taiwan from October 16th to 26th, 2013. The results showed good agreements with 10 minute averaged data of the wind speed and wind direction measured by the two LiDARs. NCKU WindSentinel data are planning comparisons with Fuhai's offshore fixed mast data when the meteorological mast is completed. The goal is to convince the wind energy community that FLD are a reliable and cost effective way of obtaining data for resource assessment. Until this moment, The FLD are observing and measuring the offshore wind farm's meteorological and oceanographic data. In September of 2014, a mild typhoon (Fung-Wong) passed through from east of Taiwan. NCKU WindSentinel continuously measured during typhoon period in the sea. The present preliminary measurements campaign presented the convenient and more cost effective option of the FLD, which may be a key tool for assessment of offshore wind resources in the near-future offshore wind farm developments.

  10. Regional forest biomass estimation using ICESat/GLAS spaceborne LiDAR

    NASA Astrophysics Data System (ADS)

    Hayashi, M.; Saigusa, N.; Habura, B.; Sawada, Y.; Yamagata, Y.; Hirano, T.; Ichii, K.

    2015-12-01

    Spaceborne LiDAR can observe vertical structure of forests and provide a means for accurate forest monitoring, therefore, it may meet the growing demand of forest resources monitoring on a large scale. This study aims to clarify the potential of ICESat/GLAS, which had been the only spaceborne LiDAR up to now, for forest resources monitoring on a regional scale. The study areas were three regions: Hokkaido Island in Japan (cool-temperate forest), Borneo Island (tropical forest) and Siberia (boreal forest). Firstly, we conducted field measurements at 106 points in Hokkaido and 37 points in Borneo to measure the average canopy height (Lorey's height) and the above-ground biomass (AGB) for each GLAS-footprint, then, we developed some models to estimate canopy height and AGB from the GLAS waveform parameters. Next, we applied the developed models to the GLAS data which were 14,000 points in Hokkaido, and 130,000 points in Borneo, to estimate canopy height and AGB on a regional scale. As a result, we clarified the forest condition concerning canopy height and AGB for each region, namely, the average value, the comparison between the average of each forest type, and the spatial distribution. Furthermore, we detected the AGB change over the years (forest degradation) and estimated the forest loss rate of 1.6% yr-1 in Borneo. Next, we applied the developed models in Hokkaido to the 1,600,000 points GLAS data observed in Siberia. As a result, we clarified that the average AGB in Siberia was a remarkable low value as compared with those in Hokkaido and Borneo, and that the AGB change over the years (forest degradation) was significant in the southern region of western Siberia. This study showed that spaceborne LiDAR had an ability of forest resources monitoring on a regional scale for various forests over the world.

  11. Structural effects of liana presence in secondary tropical dry forests using ground LiDAR

    NASA Astrophysics Data System (ADS)

    Sánchez-Azofeifa, A.; Portillo-Quintero, C.; Durán, S. M.

    2015-10-01

    Lianas, woody vines, are a key component of tropical forest because they may reduce carbon storage potential. Lianas are increasing in density and biomass in tropical forests, but it is unknown what the potential consequences of these increases are for forest dynamics. Lianas may proliferate in disturbed areas, such as regenerating forests, but little is known about the role of lianas in secondary succession. In this study, we evaluated the potential of the ground LiDAR to detect differences in the vertical structure of stands of different ages with and without lianas in tropical dry forests. Specifically, we used a terrestrial laser scanner called VEGNET to assess whether liana presence influences the vertical signature of stands of different ages, and whether successional trajectories as detected by the VEGNET could be altered by liana presence. We deployed the VEGNET ground LiDAR system in 15 secondary forests of different ages early (21 years old since land abandonment), intermediate (32-35 years old) and late stages (> 80 years old) with and without lianas. We compared laser-derived vegetation components such as Plant Area Index (PAI), plant area volume density (PAVD), and the radius of gyration (RG) across forest stands between liana and no-liana treatments. In general forest stands without lianas show a clearer distinction of vertical strata and the vertical height of accumulated PAVD. A significant increase of PAI was found from intermediate to late stages in stands without lianas, but in stands where lianas were present there was not a significant trend. This suggests that lianas may be influencing successional trajectories in secondary forests, and these effects can be captured by terrestrial laser scanners such as the VEGNET. This research contributes to estimate the potential effects of lianas in secondary dry forests and highlight the role of ground LiDAR to monitor structural changes in tropical forests due to liana presence.

  12. Numerical simulation of groundwater flow in Dar es Salaam Coastal Plain (Tanzania)

    NASA Astrophysics Data System (ADS)

    Luciani, Giulia; Sappa, Giuseppe; Cella, Antonella

    2016-04-01

    They are presented the results of a groundwater modeling study on the Coastal Aquifer of Dar es Salaam (Tanzania). Dar es Salaam is one of the fastest-growing coastal cities in Sub-Saharan Africa, with with more than 4 million of inhabitants and a population growth rate of about 8 per cent per year. The city faces periodic water shortages, due to the lack of an adequate water supply network. These two factors have determined, in the last ten years, an increasing demand of groundwater exploitation, carried on by quite a number of private wells, which have been drilled to satisfy human demand. A steady-state three dimensional groundwater model has been set up by the MODFLOW code, and calibrated with the UCODE code for inverse modeling. The aim of the model was to carry out a characterization of groundwater flow system in the Dar es Salaam Coastal Plain. The inputs applied to the model included net recharge rate, calculated from time series of precipitation data (1961-2012), estimations of average groundwater extraction, and estimations of groundwater recharge, coming from zones, outside the area under study. Parametrization of the hydraulic conductivities was realized referring to the main geological features of the study area, based on available literature data and information. Boundary conditions were assigned based on hydrogeological boundaries. The conceptual model was defined in subsequent steps, which added some hydrogeological features and excluded other ones. Calibration was performed with UCODE 2014, using 76 measures of hydraulic head, taken in 2012 referred to the same season. Data were weighted on the basis of the expected errors. Sensitivity analysis of data was performed during calibration, and permitted to identify which parameters were possible to be estimated, and which data could support parameters estimation. Calibration was evaluated based on statistical index, maps of error distribution and test of independence of residuals. Further model

  13. A High Density Consensus Map of Rye (Secale cereale L.) Based on DArT Markers

    PubMed Central

    Myśków, Beata; Stojałowski, Stefan; Heller-Uszyńska, Katarzyna; Góralska, Magdalena; Brągoszewski, Piotr; Uszyński, Grzegorz; Kilian, Andrzej; Rakoczy-Trojanowska, Monika

    2011-01-01

    Background Rye (Secale cereale L.) is an economically important crop, exhibiting unique features such as outstanding resistance to biotic and abiotic stresses and high nutrient use efficiency. This species presents a challenge to geneticists and breeders due to its large genome containing a high proportion of repetitive sequences, self incompatibility, severe inbreeding depression and tissue culture recalcitrance. The genomic resources currently available for rye are underdeveloped in comparison with other crops of similar economic importance. The aim of this study was to create a highly saturated, multilocus linkage map of rye via consensus mapping, based on Diversity Arrays Technology (DArT) markers. Methodology/Principal Findings Recombinant inbred lines (RILs) from 5 populations (564 in total) were genotyped using DArT markers and subjected to linkage analysis using Join Map 4.0 and Multipoint Consensus 2.2 software. A consensus map was constructed using a total of 9703 segregating markers. The average chromosome map length ranged from 199.9 cM (2R) to 251.4 cM (4R) and the average map density was 1.1 cM. The integrated map comprised 4048 loci with the number of markers per chromosome ranging from 454 for 7R to 805 for 4R. In comparison with previously published studies on rye, this represents an eight-fold increase in the number of loci placed on a consensus map and a more than two-fold increase in the number of genetically mapped DArT markers. Conclusions/Significance Through the careful choice of marker type, mapping populations and the use of software packages implementing powerful algorithms for map order optimization, we produced a valuable resource for rye and triticale genomics and breeding, which provides an excellent starting point for more in-depth studies on rye genome organization. PMID:22163026

  14. Comparison of remotely sensed water stages from LiDAR, topographic contours and SRTM

    NASA Astrophysics Data System (ADS)

    Schumann, G.; Matgen, P.; Cutler, M. E. J.; Black, A.; Hoffmann, L.; Pfister, L.

    Digital elevation models (DEMs) are at the core of most environmental process modelling and disaster management. In flood inundation modelling, surface elevation constitutes one of the most important model boundary conditions. With the availability of high-precision DEMs (e.g. LiDAR) and globally available DEMs (e.g. SRTM InSAR) a big step seems to have been taken in terms of hydraulic modelling application or hydraulic information retrieval from such DEMs, with high potential in particular for ungauged basins. Comparative studies exist that report on both the validation of different remotely sensed elevation sources and their use for both hydrologic and hydraulic studies. To contribute to the existing literature on DEMs and hydraulic information, this study aims at comparing water stages derived from LiDAR, topographic contours and SRTM. A flood inundation model calibrated with distributed ground-surveyed high water marks is used to evaluate the remotely sensed water stages. The results show that, as expected, LiDAR derived water stages exhibit the lowest RMSE (0.35 m), followed by the contour DEM (0.7 m). A relatively good performance of the SRTM (1.07 m), which is possibly linked to the low-lying floodplain, suggests that the SRTM is a valuable source for initial vital flood information extraction in large, homogeneous floodplains. Subsequent 3D flood mapping from remotely sensed water stages confirms this but also indicates that flood mapping with low-resolution, low-precision surface elevation data is hardly possible on the small scale, as the accuracy of the resulting map depends too much on DEM uncertainties and errors both in the horizontal and vertical directions.

  15. Quantification of uncertainty in aboveground biomass estimates derived from small-footprint LiDAR data

    NASA Astrophysics Data System (ADS)

    Xu, Q.; Greenberg, J. A.; Li, B.; Ramirez, C.; Balamuta, J. J.; Evans, K.; Man, A.; Xu, Z.

    2015-12-01

    A promising approach to determining aboveground biomass (AGB) in forests comes through the use of individual tree crown delineation (ITCD) techniques applied to small-footprint LiDAR data. These techniques, when combined with allometric equations, can produce per-tree estimates of AGB. At this scale, AGB estimates can be quantified in a manner similar to how ground-based forest inventories are produced. However, these approaches have significant uncertainties that are rarely described in full. Allometric equations are often based on species-specific diameter-at-breast height (DBH) relationships, but neither DBH nor species can be reliably determined using remote sensing analysis. Furthermore, many approaches to ITCD only delineate trees appearing in the upper canopy so subcanopy trees are often missing from the inventories. In this research, we performed a propagation-of-error analysis to determine the spatially varying uncertainties in AGB estimates at the individual plant and stand level for a large collection of LiDAR acquisitions covering a large portion of California. Furthermore, we determined the relative contribution of various aspects of the analysis towards the uncertainty, including errors in the ITCD results, the allometric equations, the taxonomic designation, and the local biophysical environment. Watershed segmentation was used to obtain the preliminary crown segments. Lidar points within the preliminary segments were extracted to form profiling data of the segments, and then mode detection algorithms were applied to identify the tree number and tree heights within each segment. As part of this analysis, we derived novel "remote sensing aware" allometric equations and their uncertainties based on three-dimensional morphological metrics that can be accurately derived from LiDAR data.

  16. Residents’ perceptions of institutional performance in water supply in Dar es Salaam

    NASA Astrophysics Data System (ADS)

    Mwakalila, Shadrack

    This paper addresses the performance of institutions in water supply systems for improving social and economic benefits of people living in Dar es Salaam city. The methods employed in field data and information collection included interviews, questionnaire, focus group discussions and participatory observation. Kinondoni and Ilala Districts were used as case study. The study revealed that, the main water sources in the study areas are boreholes, shallow wells, rain water and water vendors. Other minor sources are piped water and natural water sources, such as rivers and streams. The supply of piped water by Dar es Salaam Water Sewerage and Sanitation Company (DAWASA/DAWASCO) meets only 45% of the total water demands. Individuals own and sell water from boreholes, shallow wells, piped water connected to their individual houses and natural wells located in their individual plots. The price of one 20 l bucket of water from a water vendor depends on the availability of water and the distance walked from the water source to the customer. Majority of the respondents (77.5%) indicated that individual water delivery systems provide sufficient water as compared to five years ago in the study areas. Few of the respondents (6.3%) said individual water delivery systems have no capacity to provide sufficient water while 16.3% indicate that individual water delivery systems provide moderate water supply but are important in supplementing other water providers in the study areas. The study reveals that a majority of the local population are satisfied with the capacity of individual water delivery systems in providing water for household uses. This paper recommends some improvements to be done to water supply systems in the Dar es Salaam city.

  17. Classification of breaklines derived from airborne LiDAR data for geomorphological activity mapping

    NASA Astrophysics Data System (ADS)

    Rutzinger, Martin; Höfle, Bernhard; Vetter, Michael; Stötter, Johann; Pfeifer, Norbert

    2010-05-01

    Airborne LiDAR surveys provide 3D high-resolution elevation information for area-wide applications. Due to the capability of LiDAR to penetrate vegetation cover highly accurate digital terrain models (DTMs) can be derived also for forested areas. Breaklines derived from LiDAR DTMs mark regions of slope discontinuities, describing the main characteristics of a terrain surface in an efficient manner. Breaklines are often used for DTM enhancement but also for the detection and interpretation of geomorphologically relevant landforms such as landslides, torrents, erosion scraps and tectonic faults. Because of human activities geomorphologic landforms are often disturbed and reshaped i.e. by construction of roads, skiing slopes, drainage channels and surface mining. Therefore, DTMs contain both, anthropogenic and geomorphologic discontinuities. This significantly disturbs morphometric analysis and causes problems for automatic landform mapping algorithms. In this research an automatic breakline detection method is applied in an alpine region with high relief variation containing surface discontinuities such as torrents, creeping slope failure, and landslides, which are reshaped by anthropogenic activities. Regions of high curvature are classified and vectorised in order to derive 3D breaklines. These are further filtered and classified based on object-based properties such as their size, shape and slope to separate natural i.e. geomorphologic relevant and anthropogenic structures. The classification result is compared to reference map data indicating a high reliability of the classification quality. After the removal of anthropogenic breaklines the remaining natural breaklines are used to compute line density maps using a moving window approach. These density maps point out areas of different relief energy and assist to delineate areas of geomorphologic relevance. These areas are also of most interest to identify geomorphological landforms. The methodology presented

  18. LiDAR Individual Tree Detection for Assessing Structurally Diverse Forest Landscapes

    NASA Astrophysics Data System (ADS)

    Jeronimo, Sean

    Contemporary forest management on public land incorporates a focus on restoration and maintenance of ecological functions through silvicultural manipulation of forest structure on a landscape scale. Incorporating reference conditions into restoration treatment planning and monitoring can improve treatment efficacy, but the typical ground-based methods of quantifying reference condition data---and comparing it to pre- and post-treatment stands---are expensive, time-consuming, and limited in scale. Airborne LiDAR may be part of the solution to this problem, since LiDAR acquisitions have both broad coverage and high resolution. I evaluated the ability of LiDAR Individual Tree Detection (ITD) to describe forest structure across a structurally variable landscape in support of large-scale forest restoration. I installed nineteen 0.25 ha stem map plots across a range of structural conditions in potential reference areas (Yosemite National Park) and potential restoration treatment areas (Sierra National Forest) in the Sierra Nevada of California. I used the plots to evaluate a common ITD algorithm, the watershed transform, compare it to past uses of ITD, and determine which aspects of forest structure contributed to errors in ITD. I found that ITD across this structurally diverse landscape was generally less accurate than across the smaller and less diverse areas over which it has previously been studied. However, the pattern of tree recognition is consistent: regardless of forest structure, canopy dominants are almost always detected and relatively shorter trees are almost never detected. Correspondingly, metrics dominated by large trees, such as biomass, basal area, and spatial heterogeneity, can be measured using ITD, while metrics dominated by smaller trees, such as stand density, cannot. Bearing these limitations in mind, ITD can be a powerful tool for describing forest structure across heterogeneous landscape restoration project areas.

  19. 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.

  20. 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

    2015-01-01

    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

  1. 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.

  2. 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.

  3. Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping.

    PubMed

    Qin, Yuchu; Li, Shihua; Vu, Tuong-Thuy; Niu, Zheng; Ban, Yifang

    2015-06-01

    Urban land cover map is essential for urban planning, environmental studies and management. This paper aims to demonstrate the potential of geometric and radiometric features derived from LiDAR waveform and point cloud data in urban land cover mapping with both parametric and non-parametric classification algorithms. Small footprint LiDAR waveform data acquired by RIEGL LMS-Q560 in Zhangye city, China is used in this study. A LiDAR processing chain is applied to perform waveform decomposition, range determination and radiometric characterization. With the synergic utilization of geometric and radiometric features derived from LiDAR data, urban land cover classification is then conducted using the Maximum Likelihood Classification (MLC), Support Vector Machines (SVM) and random forest algorithms. The results suggest that the random forest classifier achieved the most accurate result with overall classification accuracy of 91.82% and the kappa coefficient of 0.88. The overall accuracies of MLC and SVM are 84.02, and 88.48, respectively. The study suggest that the synergic utilization of geometric and radiometric features derived from LiDAR data can be efficiently used for urban land cover mapping, the non-parametric random forest classifier is a promising approach for the various features with different physical meanings.

  4. 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.

  5. 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

  6. The use of 1572 nm Mie LiDAR for observation of the optical properties of aerosols over Wuhan, China

    NASA Astrophysics Data System (ADS)

    Gong, Wei; Ma, Xin; Dong, Yanni; Lin, Hong; Li, Jun

    2014-03-01

    CO2 is a major component of greenhouse gases. When CO2 concentration is measured by satellites, calibration of the lower atmosphere becomes an essential procedure. Since the 1572 nm infrared region is widely used in remote sensing of CO2, we constructed a Mie LiDAR system, designed to work at 1572 nm, for measuring the optical properties of aerosols in the lower troposphere. Based on the particle size distribution measured by the heliograph, the LiDAR ratio is independently determined for Wuhan, China. The LiDAR echo signal is then processed by the Fernald method to calculate the extinction coefficient on both clear and cloudy days. The maximum detection height is restricted by the low laser energy and quantum efficiency of the Photomultiplier Tube (PMT) used. Moreover, a simplified method for detecting the position of clouds is presented and this method is verified using a variety of passive radiation instruments that offer partial support for calibrating and verifying LiDAR data. The observed results indicate that this LiDAR system could be a reliable source of data support for the spaceborne remote sensing of CO2.

  7. Development of the Philippine Hydrologic Dataset (PHD) from LiDAR and other remotely-sensed data

    NASA Astrophysics Data System (ADS)

    Perez, A. M. C.; Gaspa, M. C.; Aloc, D. S.; Mahor, M. A. P.; Gonzalez, K. A. C.; Borlongan, N. J. B.; De La Cruz, R. M.; Olfindo, N. T.; Blanco, A. C.

    2015-10-01

    Water resource monitoring and management has been an important concern in the Philippines, considering that the country is archipelagic in nature and is exposed to a lot of disasters imposed by the global effects of climate change. The design and implementation of an effective management scheme relies heavily on accurate, complete, and updated water resource inventories, usually in the form of digital maps and geodatabases. With the aim of developing a detailed and comprehensive database of all water resources in the Philippines, the 3-year project "Development of the Philippine Hydrologic Dataset (PHD) for Watersheds from LiDAR Surveys" under the Phil-LiDAR 2 Program (National Resource Inventory), has been initiated by the University of the Philippines Diliman (UPD) and the Department of Science and Technology (DOST). Various workflows has already been developed to extract inland hydrologic features in the Philippines using accurate Light Detection and Ranging (LiDAR) Digital Terrain Models (DTMs) and LiDAR point cloud data obtained through other government-funded programs such as Disaster Risk and Exposure Assessment for Mitigation (DREAM) and Phil-LiDAR 1, supplemented with other remotely-sensed imageries and ancillary information from Local Government Units (LGUs) and National Government Agencies (NGAs). The methodologies implemented are mainly combinations of object-based image analysis, pixel-based image analysis, modeling, and field surveys. This paper presents the PHD project, the methodologies developed, and some sample outputs produced.

  8. Calculating LiDAR Point Cloud Uncertainty and Propagating Uncertainty to Snow-Water Equivalent Data Products

    NASA Astrophysics Data System (ADS)

    Gadomski, P. J.; Deems, J. S.; Glennie, C. L.; Hartzell, P. J.; Butler, H.; Finnegan, D. C.

    2015-12-01

    The use of high-resolution topographic data in the form of three-dimensional point clouds obtained from laser scanning systems (LiDAR) is becoming common across scientific disciplines.However little consideration has typically been given to the accuracy and the precision of LiDAR-derived measurements at the individual point scale.Numerous disparate sources contribute to the aggregate precision of each point measurement, including uncertainties in the range measurement, measurement of the attitude and position of the LiDAR collection platform, uncertainties associated with the interaction between the laser pulse and the target surface, and more.We have implemented open-source software tools to calculate per-point stochastic measurement errors for a point cloud using the general LiDAR georeferencing equation.We demonstrate the use of these propagated uncertainties by applying our methods to data collected by the Airborne Snow Observatory ALS, a NASA JPL project using a combination of airborne hyperspectral and LiDAR data to estimate snow-water equivalent distributions over full river basins.We present basin-scale snow depth maps with associated uncertainties, and demonstrate the propagation of those uncertainties to snow volume and snow-water equivalent calculations.

  9. Financial sustainability in municipal solid waste management--costs and revenues in Bahir Dar, Ethiopia.

    PubMed

    Lohri, Christian Riuji; Camenzind, Ephraim Joseph; Zurbrügg, Christian

    2014-02-01

    Providing good solid waste management (SWM) services while also ensuring financial sustainability of the system continues to be a major challenge in cities of developing countries. Bahir Dar in northwestern Ethiopia outsourced municipal waste services to a private waste company in 2008. While this institutional change has led to substantial improvement in the cleanliness of the city, its financial sustainability remains unclear. Is the private company able to generate sufficient revenues from their activities to offset the costs and generate some profit? This paper presents a cost-revenue analysis, based on data from July 2009 to June 2011. The analysis reveals that overall costs in Bahir Dar's SWM system increased significantly during this period, mainly due to rising costs related to waste transportation. On the other hand, there is only one major revenue stream in place: the waste collection fee from households, commercial enterprises and institutions. As the efficiency of fee collection from households is only around 50%, the total amount of revenues are not sufficient to cover the running costs. This results in a substantial yearly deficit. The results of the research therefore show that a more detailed cost structure and cost-revenue analysis of this waste management service is important with appropriate measures, either by the privates sector itself or with the support of the local authorities, in order to enhance cost efficiency and balance the cost-revenues towards cost recovery. Delays in mitigating the evident financial deficit could else endanger the public-private partnership (PPP) and lead to failure of this setup in the medium to long term, thus also endangering the now existing improved and currently reliable service. We present four options on how financial sustainability of the SWM system in Bahir Dar might be enhanced: (i) improved fee collection efficiency by linking the fees of solid waste collection to water supply; (ii) increasing the value

  10. Financial sustainability in municipal solid waste management--costs and revenues in Bahir Dar, Ethiopia.

    PubMed

    Lohri, Christian Riuji; Camenzind, Ephraim Joseph; Zurbrügg, Christian

    2014-02-01

    Providing good solid waste management (SWM) services while also ensuring financial sustainability of the system continues to be a major challenge in cities of developing countries. Bahir Dar in northwestern Ethiopia outsourced municipal waste services to a private waste company in 2008. While this institutional change has led to substantial improvement in the cleanliness of the city, its financial sustainability remains unclear. Is the private company able to generate sufficient revenues from their activities to offset the costs and generate some profit? This paper presents a cost-revenue analysis, based on data from July 2009 to June 2011. The analysis reveals that overall costs in Bahir Dar's SWM system increased significantly during this period, mainly due to rising costs related to waste transportation. On the other hand, there is only one major revenue stream in place: the waste collection fee from households, commercial enterprises and institutions. As the efficiency of fee collection from households is only around 50%, the total amount of revenues are not sufficient to cover the running costs. This results in a substantial yearly deficit. The results of the research therefore show that a more detailed cost structure and cost-revenue analysis of this waste management service is important with appropriate measures, either by the privates sector itself or with the support of the local authorities, in order to enhance cost efficiency and balance the cost-revenues towards cost recovery. Delays in mitigating the evident financial deficit could else endanger the public-private partnership (PPP) and lead to failure of this setup in the medium to long term, thus also endangering the now existing improved and currently reliable service. We present four options on how financial sustainability of the SWM system in Bahir Dar might be enhanced: (i) improved fee collection efficiency by linking the fees of solid waste collection to water supply; (ii) increasing the value

  11. 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

  12. Wallace Creek Virtual Field Trip: Teaching Geoscience Concepts with LiDAR

    NASA Astrophysics Data System (ADS)

    Robinson, S. E.; Arrowsmith, R.; Crosby, C. J.

    2009-12-01

    Recently available data such as LiDAR (Light Detection and Ranging) high-resolution topography can assist students to better visualize and understand geosciences concepts. It is important to bring these data into geosciences curricula as teaching aids while ensuring that the visualization tools, virtual environments, etc. do not serve as barriers to student learning. As a Southern California Earthquake Center ACCESS-G intern, I am creating a “virtual field trip” to Wallace Creek along the San Andreas Fault (SAF) using Google Earth as a platform and the B4 project LiDAR data. Wallace Creek is an excellent site for understanding the centennial-to-millennial record of SAF slip because of its dramatic stream offsets. Using the LiDAR data instead of, or alongside, traditional visualizations and teaching methods enhances a student’s ability to understand plate tectonics, the earthquake cycle, strike-slip faults, and geomorphology. Viewing a high-resolution representation of the topography in Google Earth allows students to analyze the landscape and answer questions about the behavior of the San Andreas Fault. The activity guides students along the fault allowing them to measure channel offsets using the Google Earth measuring tool. Knowing the ages of channels, they calculate slip rate. They look for the smallest channel offsets around Wallace Creek in order to determine the slip per event. At both a “LiDAR and Education” workshop and the Cyberinfrastructure Summer Institute for Geoscientists (CSIG), I presented the Wallace Creek activity to high school and college earth science teachers. The teachers were positive in their responses and had numerous important suggestions including the need for a teacher’s manual for instruction and scientific background, and that the student goals and science topics should be specific and well-articulated for the sake of both the teacher and the student. The teachers also noted that the technology in classrooms varies

  13. Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds.

    PubMed

    Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

    2016-06-17

    Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average

  14. Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds†

    PubMed Central

    Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

    2016-01-01

    Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average

  15. Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds.

    PubMed

    Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

    2016-01-01

    Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average

  16. Landslide displacement vectors derived from multi-temporal topographic LiDAR data

    NASA Astrophysics Data System (ADS)

    Fey, Christine; Rutzinger, Martin; Bremer, Magnus; Prager, Christoph; Zangerl, Christian

    2014-05-01

    Information about slope geometry and kinematics of landslides is essential for hazard assessment, monitoring and planning of protection and mitigation measures. Especially for remote and inaccessible slopes, subsurface data (e.g. boreholes, tunnels, investigation adits) are often not available and thus the deformation characteristics must be derived from surface displacement data. In recent years, multi-temporal topographic LiDAR (Light Detection and Ranging) data became an increasingly improved tool for detecting topographic surface deformations. In this context, LiDAR-based change detection is commonly applied for quantifying surface elevation changes. Advanced change detection methods derive displacement vectors with direction and velocities of slope movements. To extract displacement vectors from LiDAR raster data (i) an approach based on feature tracking by image correlation and (ii) an approach based on feature tracking by vectors breaklines are investigated. The image correlation method is based on the IMCORR software (National Snow and Ice Data Center, University of Colorado, Boulder), implemented in a SAGA GIS module. The image correlation algorithm is based on a normalized cross-covariance method. The algorithm searches tie points in two feature rasters derived from a digital surface model acquired at different time stamps. The method assesses automatically the displacement rates and directions of distinct terrain features e.g. displaced mountain ridges or striking boulders. In contrast the vector-based breakline methods require manual selection of tie points. The breaklines are the product of vectorized curvature raster images and extracting the "upper terrain edges" (topographic ridges) and "lower terrain edges" (topographic depressions). Both methods were tested on simulated terrain with determined displacement rates in order to quantify i) the accuracy ii) the minimum detectable movement rates iii) the influence of terrain characteristics iv) the

  17. Unsupervised building detection from irregularly spaced LiDAR and aerial imagery

    NASA Astrophysics Data System (ADS)

    Shorter, Nicholas Sven

    As more data sources containing 3-D information are becoming available, an increased interest in 3-D imaging has emerged. Among these is the 3-D reconstruction of buildings and other man-made structures. A necessary preprocessing step is the detection and isolation of individual buildings that subsequently can be reconstructed in 3-D using various methodologies. Applications for both building detection and reconstruction have commercial use for urban planning, network planning for mobile communication (cell phone tower placement), spatial analysis of air pollution and noise nuisances, microclimate investigations, geographical information systems, security services and change detection from areas affected by natural disasters. Building detection and reconstruction are also used in the military for automatic target recognition and in entertainment for virtual tourism. Previously proposed building detection and reconstruction algorithms solely utilized aerial imagery. With the advent of Light Detection and Ranging (LiDAR) systems providing elevation data, current algorithms explore using captured LiDAR data as an additional feasible source of information. Additional sources of information can lead to automating techniques (alleviating their need for manual user intervention) as well as increasing their capabilities and accuracy. Several building detection approaches surveyed in the open literature have fundamental weaknesses that hinder their use; such as requiring multiple data sets from different sensors, mandating certain operations to be carried out manually, and limited functionality to only being able to detect certain types of buildings. In this work, a building detection system is proposed and implemented which strives to overcome the limitations seen in existing techniques. The developed framework is flexible in that it can perform building detection from just LiDAR data (first or last return), or just nadir, color aerial imagery. If data from both LiDAR and

  18. The application of hospitality elements in hospitals.

    PubMed

    Wu, Ziqi; Robson, Stephani; Hollis, Brooke

    2013-01-01

    In the last decade, many hospital designs have taken inspiration from hotels, spurred by factors such as increased patient and family expectations and regulatory or financial incentives. Increasingly, research evidence suggests the value of enhancing the physical environment to foster healing and drive consumer decisions and perceptions of service quality. Although interest is increasing in the broader applicability of numerous hospitality concepts to the healthcare field, the focus of this article is design innovations, and the services that such innovations support, from the hospitality industry. To identify physical hotel design elements and associated operational features that have been used in the healthcare arena, a series of interviews with hospital and hotel design experts were conducted. Current examples and suggestions for future hospitality elements were also sought from the experts, academic journals, and news articles. Hospitality elements applied in existing hospitals that are addressed in this article include hotel-like rooms and decor; actual hotels incorporated into medical centers; hotel-quality food, room service, and dining facilities for families; welcoming lobbies and common spaces; hospitality-oriented customer service training; enhanced service offerings, including concierges; spas or therapy centers; hotel-style signage and way-finding tools; and entertainment features. Selected elements that have potential for future incorporation include executive lounges and/or communal lobbies with complimentary wireless Internet and refreshments, centralized controls for patients, and flexible furniture. Although the findings from this study underscore the need for more hospitality-like environments in hospitals, the investment decisions made by healthcare executives must be balanced with cost-effectiveness and the assurance that clinical excellence remains the top priority.

  19. The application of hospitality elements in hospitals.

    PubMed

    Wu, Ziqi; Robson, Stephani; Hollis, Brooke

    2013-01-01

    In the last decade, many hospital designs have taken inspiration from hotels, spurred by factors such as increased patient and family expectations and regulatory or financial incentives. Increasingly, research evidence suggests the value of enhancing the physical environment to foster healing and drive consumer decisions and perceptions of service quality. Although interest is increasing in the broader applicability of numerous hospitality concepts to the healthcare field, the focus of this article is design innovations, and the services that such innovations support, from the hospitality industry. To identify physical hotel design elements and associated operational features that have been used in the healthcare arena, a series of interviews with hospital and hotel design experts were conducted. Current examples and suggestions for future hospitality elements were also sought from the experts, academic journals, and news articles. Hospitality elements applied in existing hospitals that are addressed in this article include hotel-like rooms and decor; actual hotels incorporated into medical centers; hotel-quality food, room service, and dining facilities for families; welcoming lobbies and common spaces; hospitality-oriented customer service training; enhanced service offerings, including concierges; spas or therapy centers; hotel-style signage and way-finding tools; and entertainment features. Selected elements that have potential for future incorporation include executive lounges and/or communal lobbies with complimentary wireless Internet and refreshments, centralized controls for patients, and flexible furniture. Although the findings from this study underscore the need for more hospitality-like environments in hospitals, the investment decisions made by healthcare executives must be balanced with cost-effectiveness and the assurance that clinical excellence remains the top priority. PMID:23424818

  20. Hospitals as health educators

    MedlinePlus

    ... than your local hospital. From health videos to yoga classes, many hospitals offer information families need to ... care and breastfeeding Parenting Baby sign language Baby yoga or massage Babysitting courses for teens Exercise classes ...

  1. Surviving Your Child's Hospitalization.

    ERIC Educational Resources Information Center

    Cohen, David A.

    1988-01-01

    The parent of a young child who required major open heart surgery shares his suggestions for coping with a young child's hospitalization including parent visitation, relating to the hospital staff, getting answers to questions, and utilizing available services. (DB)

  2. The use of local indicators of spatial association to improve LiDAR-derived predictions of potential amphibian breeding ponds

    USGS Publications Warehouse

    Julian, J.T.; Young, J.A.; Jones, J.W.; Snyder, C.D.; Wright, C.W.

    2009-01-01

    We examined whether spatially explicit information improved models that use LiDAR return signal intensity to discriminate in-pond habitat from terrestrial habitat at 24 amphibian breeding ponds. The addition of Local Indicators of Spatial Association (LISA) to LiDAR return intensity data significantly improved predictive models at all ponds, reduced residual error by as much as 74%, and appeared to improve models by reducing classification errors associated with types of in-pond vegetation. We conclude that LISA statistics can help maximize the information content that can be extracted from time resolved LiDAR return data in models that predict the occurrence of small, seasonal ponds. ?? Springer-Verlag 2008.

  3. University Hospitals for Sale.

    ERIC Educational Resources Information Center

    Culliton, Barbara J.

    1984-01-01

    Although faculty opposition stopped the sale of Harvard's McLean Hospital to the Hospital Corporation of America (HCA), a partnership remains a possibility. Issues related to the proposed sale as well as those affecting hospital economics are considered. Proposed terms of the sale are included. (JN)

  4. HOSPITALS FOR RURAL PEOPLE.

    ERIC Educational Resources Information Center

    MANNY, ELSIE S.; ROGERS, CHARLES E.

    MODERN ADVANCEMENTS IN MEDICAL SCIENCE HAVE PRECIPITATED THE NEED FOR ADEQUATE UP-TO-DATE HOSPITAL FACILITIES REASONABLY CLOSE TO ALL PEOPLE. RURAL COMMUNITIES HAVE UTILIZED FEDERAL AID, STATE AID, ASSISTANCE FROM FOUNDATIONS, CIVIC BONDS, AND VOLUNTEER CONTRIBUTIONS AND DRIVES TO ERECT AND EQUIP HOSPITALS. HOSPITAL CARE FOR RURAL PEOPLE USUALLY…

  5. An Airborne Scanning LiDAR System for Ocean and Coastal Applications

    NASA Astrophysics Data System (ADS)

    Reineman, B. D.; Lenain, L.; Castel, D.; Melville, W. K.

    2008-12-01

    We have developed an airborne scanning LiDAR (Light Detection And Ranging) system and demonstrated its functionality for terrestrial and oceanographic measurements. Differential GPS (DGPS) and an Inertial Navigation System (INS) are synchronized with the LiDAR, providing end result vertical rms errors of approximately 6~cm. Flying 170~m above the surface, we achieve a point density of ~ 0.7 m-2 and a swath width of 90 to 120~m over ocean and 200~m over land. Georeferencing algorithms were developed in-house and earth-referenced data are available several hours after acquisition. Surveys from the system are compared with ground DGPS surveys and existing airborne surveys of fixed targets. Twelve research flights in a Piper Twin Comanche from August 2007 to July 2008 have provided topography of the Southern California coastline and sea surface wave fields in the nearshore ocean environment. Two of the flights also documented the results of the October 2007 landslide on Mt.~Soledad in La Jolla, California. Eight research flights aboard a Cessna Caravan surveyed the topography, lagoon, reef, and surrounding seas of Lady Elliot Island (LEI) in Australia's Great Barrier Reef in April 2008. We describe applications for the system, including coastal topographic surveys, wave measurements, reef research, and ship wake studies.

  6. LiDAR-Assisted identification of an active fault near Truckee, California

    USGS Publications Warehouse

    Hunter, L.E.; Howle, J.F.; Rose, R.S.; Bawden, G.W.

    2011-01-01

    We use high-resolution (1.5-2.4 points/m2) bare-earth airborne Light Detection and Ranging (LiDAR) imagery to identify, map, constrain, and visualize fault-related geomorphology in densely vegetated terrain surrounding Martis Creek Dam near Truckee, California. Bare-earth LiDAR imagery reveals a previously unrecognized and apparently youthful right-lateral strike-slip fault that exhibits laterally continuous tectonic geomorphic features over a 35-km-long zone. If these interpretations are correct, the fault, herein named the Polaris fault, may represent a significant seismic hazard to the greater Truckee-Lake Tahoe and Reno-Carson City regions. Three-dimensional modeling of an offset late Quaternary terrace riser indicates a minimum tectonic slip rate of 0.4 ?? 0.1 mm/yr.Mapped fault patterns are fairly typical of regional patterns elsewhere in the northern Walker Lane and are in strong coherence with moderate magnitude historical seismicity of the immediate area, as well as the current regional stress regime. Based on a range of surface-rupture lengths and depths to the base of the seismogenic zone, we estimate a maximum earthquake magnitude (M) for the Polaris fault to be between 6.4 and 6.9.

  7. GeoEarthScope Airborne LiDAR and Satellite InSAR Imagery

    NASA Astrophysics Data System (ADS)

    Phillips, D. A.; Jackson, M. E.; Meertens, C.

    2008-12-01

    UNAVCO has successfully acquired a significant volume of aerial and satellite geodetic imagery as part of GeoEarthScope, a component of the EarthScope Facility project funded by the National Science Foundation. All GeoEarthScope acquisition activities are now complete. Airborne LiDAR data acquisitions took place in 2007 and 2008 and cover a total area of more than 5000 square kilometers. The primary LiDAR survey regions cover features in Northern California, Southern/Eastern California, the Pacific Northwest, the Intermountain Seismic Belt (including the Wasatch and Teton faults and Yellowstone), and Alaska. We have ordered and archived more than 28,000 scenes (more than 81,000 frames) of synthetic aperture radar (SAR) data suitable for interferometric analyses covering most of the western U.S. and parts of Alaska and Hawaii from several satellite platforms, including ERS-1/2, ENVISAT and RADARSAT. In addition to ordering data from existing archives, we also tasked the ESA ENVISAT satellite to acquire new SAR data in 2007 and 2008. GeoEarthScope activities were led by UNAVCO, guided by the community and conducted in partnership with the USGS and NASA. Processed imagery products, in addition to formats intended for use in standard research software, can also be viewed using general purpose tools such as Google Earth. We present a summary of these vast geodetic imagery datasets, totaling tens of terabytes, which are freely available to the community.

  8. Tree Crown Delineation using Watershed Techniques and Forest Metrics from NEON LiDAR Data

    NASA Astrophysics Data System (ADS)

    Luong, K. Y.

    2014-12-01

    LiDAR is a powerful remote sensing tool allowing for forest metrics to be taken on varying scales, which ultimately provide important forestry variables used to calculate factors such as total biomass or leaf area index. These variables are most useful when calculated for individual trees throughout a stand, but in very dense forests, identifying single trees becomes more difficult by traditional means. Full forests can be quantified uniquely for the best understanding of ecological contributions as opposed to purely in situ tree inventories which are time consuming and extremely localized. Canopy height models (CHM) can be used to understand the forest as a whole. By inverting the CHM, the tree data becomes sinks in the ground, mimicking ponds; by applying watershed-related spatial analyst tools in ArcGIS and GrassGIS, the trees are delineated by makeshift "flooding." Within this algorithm, the crown peaks are also extracted as an intermediate step to delineation, but this is a reliable means to obtain an accurate number of trees, as well as their individual heights with high reliability (R2 = 0.87). Delineated tree polygons can be directly overlaid onto different rasters to get many forest variables. In tightly clustered and very sparse stands, this method of delineation has a high level of accuracy. Following the workflow studies conducted on NEON LiDAR data on the Soaproot Saddle site, a ground-truth comparison was made with the Teakettle Experimental Forest site due to the availability of tree inventory data.

  9. Use of Airborne LiDAR To Estimate Forest Stand Characteristics

    NASA Astrophysics Data System (ADS)

    Li, Qi; Zhou, Wei; Li, Chang

    2014-03-01

    Small-Footprint Airborne LiDAR(light detection and ranging) remote sensing is a breakthrough technology for deriving forest canopy structural characteristics. Because the technique is relatively new as applied to canopy measurement in China, there is a tremendous need for experiments that integrate field work, LiDAR remote sensing and subsequent analyses for retrieving the full complement of structural measures critical for forestry applications. Data storage capacity and high processing speed available today have made it possible to digitally sample and store the entire reflected waveform, instead of only extracting the discrete coordinates which form the so-called point clouds. Return waveforms can give more detailed insights into the vertical structure of surface objects, surface slope, roughness and reflectivity than the conventional echoes. In this paper, an improved Expectation Maximum (EM) algorithm is adopted to decompose raw waveform data. Derived forest biophysical parameters, such as vegetation height, subcanopy topography, crown volume, ground reflectivity, vegetation reflectivity and canopy closure, are able to describe the horizontal and vertical forest canopy structure.

  10. Road traffic sign detection and classification from mobile LiDAR point clouds

    NASA Astrophysics Data System (ADS)

    Weng, Shengxia; Li, Jonathan; Chen, Yiping; Wang, Cheng

    2016-03-01

    Traffic signs are important roadway assets that provide valuable information of the road for drivers to make safer and easier driving behaviors. Due to the development of mobile mapping systems that can efficiently acquire dense point clouds along the road, automated detection and recognition of road assets has been an important research issue. This paper deals with the detection and classification of traffic signs in outdoor environments using mobile light detection and ranging (Li- DAR) and inertial navigation technologies. The proposed method contains two main steps. It starts with an initial detection of traffic signs based on the intensity attributes of point clouds, as the traffic signs are always painted with highly reflective materials. Then, the classification of traffic signs is achieved based on the geometric shape and the pairwise 3D shape context. Some results and performance analyses are provided to show the effectiveness and limits of the proposed method. The experimental results demonstrate the feasibility and effectiveness of the proposed method in detecting and classifying traffic signs from mobile LiDAR point clouds.

  11. Estimating Water Storage in Prairie Wetlands from a LiDAR DEM

    NASA Astrophysics Data System (ADS)

    Westbrook, C. J.; Minke, A. G.; Pomeroy, J. W.; Guo, X.

    2010-12-01

    The Prairie Pothole Region (PPR) of North America contains millions of wetlands in shallow depressions that have potential to store a significant volume of surface water. Assessing and modeling the effect of wetland storage on streamflow requires accurate methods to quantify wetland water volume. Currently, many methods rely on utilizing the strong statistical relationships between area (A), volume (V), and depth (h) to estimate wetland storage. While V-A equations are commonly used throughout the PPR, equations that utilize the V-A-h relationship are not used extensively because detailed topographic data are required. This paper suggests a new approach for implementing V-A-h relationships to determine wetland volume from wetland characteristics extracted from a high resolution LiDAR digital elevation model. GIS analysis was used to generate elevation contours that represent potential surface areas measurements, as well as provide a measure of the change in area with depth. This data collection process was also automated to generate the necessary input for estimating volume through the V-A-h equations. These volumes were compared to estimates from two V-A equations commonly used in the PPR. Results demonstrate that the automated LiDAR V-A-h method provided a better estimate of wetland volume than the V-A equations. This new method could be useful in quantifying the capacity of prairie pothole wetlands to store water and modeling their role in attenuating streamflows at a variety of spatial scales.

  12. The use of social media among adolescents in Dar es Salaam and Mtwara, Tanzania.

    PubMed

    Pfeiffer, Constanze; Kleeb, Matthis; Mbelwa, Alice; Ahorlu, Collins

    2014-05-01

    Social media form part of the rapid worldwide digital development that is re-shaping the life of many young people. While the use of social media by youths is increasingly researched in the North, studies about youth in the South are missing. It therefore remains unclear how social media can be included in interventions that aim at informing young people in many countries of the global South about sexual and reproductive health. This paper presents findings of a mixed-methods study of young people's user behaviour on the internet and specifically of social media as a platform for sexual health promotion in Tanzania. The study used questionnaires with 60 adolescents and in-depth interviews with eight students aged 15 to 19 years in Dar es Salaam, and in Mtwara, Southern Tanzania. Findings show that youth in Dar es Salaam and Mtwara access the internet mainly through mobile phones. Facebook is by far the most popular internet site. Adolescents highlighted their interest in reproductive and sexual health messages and updates being delivered through humorous posts, links and clips, as well as by youth role models like music stars and actors that are entertaining and reflect up-to-date trends of modern youth culture.

  13. LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments.

    PubMed

    Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha

    2015-07-10

    A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies-INS and LiDAR SLAM-into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform-NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment.

  14. Indirect Correspondence-Based Robust Extrinsic Calibration of LiDAR and Camera

    PubMed Central

    Sim, Sungdae; Sock, Juil; Kwak, Kiho

    2016-01-01

    LiDAR and cameras have been broadly utilized in computer vision and autonomous vehicle applications. However, in order to convert data between the local coordinate systems, we must estimate the rigid body transformation between the sensors. In this paper, we propose a robust extrinsic calibration algorithm that can be implemented easily and has small calibration error. The extrinsic calibration parameters are estimated by minimizing the distance between corresponding features projected onto the image plane. The features are edge and centerline features on a v-shaped calibration target. The proposed algorithm contributes two ways to improve the calibration accuracy. First, we use different weights to distance between a point and a line feature according to the correspondence accuracy of the features. Second, we apply a penalizing function to exclude the influence of outliers in the calibration datasets. Additionally, based on our robust calibration approach for a single LiDAR-camera pair, we introduce a joint calibration that estimates the extrinsic parameters of multiple sensors at once by minimizing one objective function with loop closing constraints. We conduct several experiments to evaluate the performance of our extrinsic calibration algorithm. The experimental results show that our calibration method has better performance than the other approaches. PMID:27338416

  15. Indirect Correspondence-Based Robust Extrinsic Calibration of LiDAR and Camera.

    PubMed

    Sim, Sungdae; Sock, Juil; Kwak, Kiho

    2016-06-22

    LiDAR and cameras have been broadly utilized in computer vision and autonomous vehicle applications. However, in order to convert data between the local coordinate systems, we must estimate the rigid body transformation between the sensors. In this paper, we propose a robust extrinsic calibration algorithm that can be implemented easily and has small calibration error. The extrinsic calibration parameters are estimated by minimizing the distance between corresponding features projected onto the image plane. The features are edge and centerline features on a v-shaped calibration target. The proposed algorithm contributes two ways to improve the calibration accuracy. First, we use different weights to distance between a point and a line feature according to the correspondence accuracy of the features. Second, we apply a penalizing function to exclude the influence of outliers in the calibration datasets. Additionally, based on our robust calibration approach for a single LiDAR-camera pair, we introduce a joint calibration that estimates the extrinsic parameters of multiple sensors at once by minimizing one objective function with loop closing constraints. We conduct several experiments to evaluate the performance of our extrinsic calibration algorithm. The experimental results show that our calibration method has better performance than the other approaches.

  16. The use of social media among adolescents in Dar es Salaam and Mtwara, Tanzania.

    PubMed

    Pfeiffer, Constanze; Kleeb, Matthis; Mbelwa, Alice; Ahorlu, Collins

    2014-05-01

    Social media form part of the rapid worldwide digital development that is re-shaping the life of many young people. While the use of social media by youths is increasingly researched in the North, studies about youth in the South are missing. It therefore remains unclear how social media can be included in interventions that aim at informing young people in many countries of the global South about sexual and reproductive health. This paper presents findings of a mixed-methods study of young people's user behaviour on the internet and specifically of social media as a platform for sexual health promotion in Tanzania. The study used questionnaires with 60 adolescents and in-depth interviews with eight students aged 15 to 19 years in Dar es Salaam, and in Mtwara, Southern Tanzania. Findings show that youth in Dar es Salaam and Mtwara access the internet mainly through mobile phones. Facebook is by far the most popular internet site. Adolescents highlighted their interest in reproductive and sexual health messages and updates being delivered through humorous posts, links and clips, as well as by youth role models like music stars and actors that are entertaining and reflect up-to-date trends of modern youth culture. PMID:24908469

  17. A comprehensive framework of building model reconstruction from airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Xiao, Y.; Wang, C.; Xi, X. H.; Zhang, W. M.

    2014-03-01

    This paper presents a comprehensive framework of reconstructing 3D building models from airborne LiDAR data, which involves building extraction, roof segmentation and model generation. Firstly, building points are extracted from LiDAR point clouds by removing walls, trees, ground and noises. Walls and trees are identified by the normal and multi-return features respectively and then ground and noise are detected by the region growing algorithm which aims at extracting smooth surfaces. Then the connected component analysis is performed to extract building points. Secondly, once the building points are acquired, building roofs are separated by the region growing algorithm which employs the normal vector and curvature of points to detect planar clusters. Finally, by combining regular building outlines obtained from building points and roof intersections acquired from the roof segmentation results, 3D building models with high accuracy are derived. Experimental results demonstrate that the proposed method is able to correctly obtain building points and reconstruct 3D building models with high accuracy.

  18. A Voxel-based Method for Forest Change Detection after Fire Using LiDAR Data

    NASA Astrophysics Data System (ADS)

    Xu, Z.

    2015-12-01

    A Voxel-based Method for Forest Change Detection after Fire Using LiDAR DataZewei Xu and Jonathan A. Greenberg Traditional methods of forest fire modeling focus on the patterns of burning in two-dimensions at relatively coarse resolutions. However, fires spread in complex, three-dimensional patterns related to the horizontal and vertical distributions of woody fuel as well as the prevailing climate conditions, and the micro-scale patterns of fuel distributions over scales of only meters can determine the path that fire can take through a complex landscape. One challenge in understanding the full three-dimensional (3D) path that a fire takes through a landscape is a lack of data at landscape scales of these burns. Remote sensing approaches, while operating at landscape scales, typically focus on two-dimensional analyses using standard image-based change detection techniques. In this research, we develop a 3D voxel-based change detection method applied to multitemporal LiDAR data collected before and after forest fires in California to quantify the full 3D pattern of vegetation loss. By changing the size of the voxel, forest loss at different spatial scales is revealed. The 3D tunnel of fuel loss created by the fire was used to examine ground-to-crown transitions, firebreaks, and other three-dimensional aspects of a forest fire.

  19. Building Change Detection by Combining LiDAR Data and Ortho Image

    NASA Astrophysics Data System (ADS)

    Peng, Daifeng; Zhang, Yongjun

    2016-06-01

    The elevation information is not considered in the traditional building change detection methods. This paper presents an algorithm of combining LiDAR data and ortho image for 3D building change detection. The advantages of the proposed approach lie in the fusion of the height and spectral information by thematic segmentation. Furthermore, the proposed method also combines the advantages of pixel-level and object-level change detection by image differencing and object analysis. Firstly, two periods of LiDAR data are filtered and interpolated to generate their corresponding DSMs. Secondly, a binary image of the changed areas is generated by means of differencing and filtering the two DSMs, and then thematic layer is generated and projected onto the DSMs and DOMs. Thirdly, geometric and spectral features of the changed area are calculated, which is followed by decision tree classification for the purpose of extracting the changed building areas. Finally, the statistics of the elevation and area change information as well as the change type of the changed buildings are done for building change analysis. Experimental results show that the completeness and correctness of building change detection are close to 81.8% and 85.7% respectively when the building area is larger than 80 m2, which are increased about 10% when compared with using ortho image alone.

  20. Indirect Correspondence-Based Robust Extrinsic Calibration of LiDAR and Camera.

    PubMed

    Sim, Sungdae; Sock, Juil; Kwak, Kiho

    2016-01-01

    LiDAR and cameras have been broadly utilized in computer vision and autonomous vehicle applications. However, in order to convert data between the local coordinate systems, we must estimate the rigid body transformation between the sensors. In this paper, we propose a robust extrinsic calibration algorithm that can be implemented easily and has small calibration error. The extrinsic calibration parameters are estimated by minimizing the distance between corresponding features projected onto the image plane. The features are edge and centerline features on a v-shaped calibration target. The proposed algorithm contributes two ways to improve the calibration accuracy. First, we use different weights to distance between a point and a line feature according to the correspondence accuracy of the features. Second, we apply a penalizing function to exclude the influence of outliers in the calibration datasets. Additionally, based on our robust calibration approach for a single LiDAR-camera pair, we introduce a joint calibration that estimates the extrinsic parameters of multiple sensors at once by minimizing one objective function with loop closing constraints. We conduct several experiments to evaluate the performance of our extrinsic calibration algorithm. The experimental results show that our calibration method has better performance than the other approaches. PMID:27338416

  1. LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments

    PubMed Central

    Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha

    2015-01-01

    A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies—INS and LiDAR SLAM—into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform—NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment. PMID:26184206

  2. 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.

  3. Characterization of the OPAL LiDAR under controlled obscurant conditions

    NASA Astrophysics Data System (ADS)

    Cao, Xiaoying; Church, Philip; Matheson, Justin

    2016-05-01

    Neptec Technologies' OPAL-120 3D LiDAR is optimized for obscurant penetration. The OPAL-120 uses a scanning mechanism based on the Risley prism pair. The scan patterns are created by rotating two prisms under independent motor control. The geometry and material properties of the prisms define the conical field-of-view of the sensor, which can be built to between 60 to 120 degrees. The OPAL-120 was recently evaluated using a controlled obscurant chamber capable of generating clouds of obscurants over a depth of 22m. Obscurants used in this investigation include: Arizona road dust, water fog, and fog-oil. The obscurant cloud optical densities were monitored with a transmissometer. Optical depths values ranged from an upper value of 6 and progressively decreased to 0. Targets were positioned at the back of the obscurant chamber at a distance of 60m from the LiDAR. The targets are made of a foreground array of equally spaced painted wood stripes in front of a solid background. Reflectivity contrasts were achieved with foreground/background combinations of white/white, white/black and black/white. Data analysis will be presented on the effect of optical densities on range and cross-range resolution, and accuracy. The analysis includes the combinations of all obscurant types and target reflectivity contrasts.

  4. Identifying Ancient Settlement Patterns through LiDAR in the Mosquitia Region of Honduras.

    PubMed

    Fisher, Christopher T; Fernández-Diaz, Juan Carlos; Cohen, Anna S; Neil Cruz, Oscar; Gonzáles, Alicia M; Leisz, Stephen J; Pezzutti, Florencia; Shrestha, Ramesh; Carter, William

    2016-01-01

    The Mosquitia ecosystem of Honduras occupies the fulcrum between the American continents and as such constitutes a critical region for understanding past patterns of socio-political development and interaction. Heavy vegetation, rugged topography, and remoteness have limited scientific investigation. This paper presents prehistoric patterns of settlement and landuse for a critical valley within the Mosquitia derived from airborne LiDAR scanning and field investigation. We show that (i) though today the valley is a wilderness it was densely inhabited in the past; (ii) that this population was organized into a three-tiered system composed of 19 settlements dominated by a city; and, (iii) that this occupation was embedded within a human engineered landscape. We also add to a growing body of literature that demonstrates the utility of LiDAR as means for rapid cultural assessments in undocumented regions for analysis and conservation. Our ultimate hope is for our work to promote protections to safeguard the unique and critically endangered Mosquitia ecosystem and other similar areas in need of preservation.

  5. LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments.

    PubMed

    Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha

    2015-01-01

    A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies-INS and LiDAR SLAM-into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform-NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment. PMID:26184206

  6. Genetic diversity of carotenoid-rich bananas evaluated by Diversity Arrays Technology (DArT)

    PubMed Central

    2009-01-01

    The aim of this work was to evaluate the carotenoid content and genetic variability of banana accessions from the Musa germplasm collection held at Embrapa Cassava and Tropical Fruits, Brazil. Forty-two samples were analyzed, including 21 diploids, 19 triploids and two tetraploids. The carotenoid content was analyzed spectrophotometrically and genetic variability was estimated using 653 DArT markers. The average carotenoid content was 4.73 μg.g -1 , and ranged from 1.06 μg.g -1 for the triploid Nanica (Cavendish group) to 19.24 μg.g -1 for the triploid Saney. The diploids Modok Gier and NBA-14 and the triploid Saney had a carotenoid content that was, respectively, 7-fold, 6-fold and 9-fold greater than that of cultivars from the Cavendish group (2.19 μg.g -1). The mean similarity among the 42 accessions was 0.63 (range: 0.24 to 1.00). DArT analysis revealed extensive genetic variability in accessions from the Embrapa Musa germplasm bank. PMID:21637652

  7. Genetic diversity of carotenoid-rich bananas evaluated by Diversity Arrays Technology (DArT).

    PubMed

    Amorim, Edson P; Vilarinhos, Alberto D; Cohen, Kelly O; Amorim, Vanusia B O; Dos Santos-Serejo, Janay A; Silva, Sebastião Oliveira E; Pestana, Kátia N; Dos Santos, Vânia J; Paes, Norma S; Monte, Damares C; Dos Reis, Ronaldo V

    2009-01-01

    The aim of this work was to evaluate the carotenoid content and genetic variability of banana accessions from the Musa germplasm collection held at Embrapa Cassava and Tropical Fruits, Brazil. Forty-two samples were analyzed, including 21 diploids, 19 triploids and two tetraploids. The carotenoid content was analyzed spectrophotometrically and genetic variability was estimated using 653 DArT markers. The average carotenoid content was 4.73 μg.g (-1) , and ranged from 1.06 μg.g (-1) for the triploid Nanica (Cavendish group) to 19.24 μg.g (-1) for the triploid Saney. The diploids Modok Gier and NBA-14 and the triploid Saney had a carotenoid content that was, respectively, 7-fold, 6-fold and 9-fold greater than that of cultivars from the Cavendish group (2.19 μg.g (-1)). The mean similarity among the 42 accessions was 0.63 (range: 0.24 to 1.00). DArT analysis revealed extensive genetic variability in accessions from the Embrapa Musa germplasm bank.

  8. Identifying Ancient Settlement Patterns through LiDAR in the Mosquitia Region of Honduras.

    PubMed

    Fisher, Christopher T; Fernández-Diaz, Juan Carlos; Cohen, Anna S; Neil Cruz, Oscar; Gonzáles, Alicia M; Leisz, Stephen J; Pezzutti, Florencia; Shrestha, Ramesh; Carter, William

    2016-01-01

    The Mosquitia ecosystem of Honduras occupies the fulcrum between the American continents and as such constitutes a critical region for understanding past patterns of socio-political development and interaction. Heavy vegetation, rugged topography, and remoteness have limited scientific investigation. This paper presents prehistoric patterns of settlement and landuse for a critical valley within the Mosquitia derived from airborne LiDAR scanning and field investigation. We show that (i) though today the valley is a wilderness it was densely inhabited in the past; (ii) that this population was organized into a three-tiered system composed of 19 settlements dominated by a city; and, (iii) that this occupation was embedded within a human engineered landscape. We also add to a growing body of literature that demonstrates the utility of LiDAR as means for rapid cultural assessments in undocumented regions for analysis and conservation. Our ultimate hope is for our work to promote protections to safeguard the unique and critically endangered Mosquitia ecosystem and other similar areas in need of preservation. PMID:27560962

  9. Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas

    NASA Astrophysics Data System (ADS)

    Zhao, Xiaoqian; Guo, Qinghua; Su, Yanjun; Xue, Baolin

    2016-07-01

    Filtering of light detection and ranging (LiDAR) data into the ground and non-ground points is a fundamental step in processing raw airborne LiDAR data. This paper proposes an improved progressive triangulated irregular network (TIN) densification (IPTD) filtering algorithm that can cope with a variety of forested landscapes, particularly both topographically and environmentally complex regions. The IPTD filtering algorithm consists of three steps: (1) acquiring potential ground seed points using the morphological method; (2) obtaining accurate ground seed points; and (3) building a TIN-based model and iteratively densifying TIN. The IPTD filtering algorithm was tested in 15 forested sites with various terrains (i.e., elevation and slope) and vegetation conditions (i.e., canopy cover and tree height), and was compared with seven other commonly used filtering algorithms (including morphology-based, slope-based, and interpolation-based filtering algorithms). Results show that the IPTD achieves the highest filtering accuracy for nine of the 15 sites. In general, it outperforms the other filtering algorithms, yielding the lowest average total error of 3.15% and the highest average kappa coefficient of 89.53%.

  10. Characterizing Croatian Wheat Germplasm Diversity and Structure in a European Context by DArT Markers

    PubMed Central

    Novoselović, Dario; Bentley, Alison R.; Šimek, Ruđer; Dvojković, Krešimir; Sorrells, Mark E.; Gosman, Nicolas; Horsnell, Richard; Drezner, Georg; Šatović, Zlatko

    2016-01-01

    Narrowing the genetic base available for future genetic progress is a major concern to plant breeders. In order to avoid this, strategies to characterize and protect genetic diversity in regional breeding pools are required. In this study, 89 winter wheat cultivars released in Croatia between 1936 and 2006 were genotyped using 1,229 DArT (diversity array technology) markers to assess the diversity and population structure. In order to place Croatian breeding pool (CBP) in a European context, Croatian wheat cultivars were compared to 523 European cultivars from seven countries using a total of 166 common DArT markers. The results show higher genetic diversity in the wheat breeding pool from Central Europe (CE) as compared to that from Northern and Western European (NWE) countries. The most of the genetic diversity was attributable to the differences among cultivars within countries. When the geographical criterion (CE vs. NWE) was applied, highly significant difference between regions was obtained that accounted for 16.19% of the total variance, revealing that the CBP represents genetic variation not currently captured in elite European wheat. The current study emphasizes the important contribution made by plant breeders to maintaining wheat genetic diversity and suggests that regional breeding is essential to the maintenance of this diversity. The usefulness of open-access wheat datasets is also highlighted. PMID:26941756

  11. Identifying Ancient Settlement Patterns through LiDAR in the Mosquitia Region of Honduras

    PubMed Central

    Fernández-Diaz, Juan Carlos; Cohen, Anna S.; Neil Cruz, Oscar; Gonzáles, Alicia M.; Leisz, Stephen J.; Pezzutti, Florencia; Shrestha, Ramesh; Carter, William

    2016-01-01

    The Mosquitia ecosystem of Honduras occupies the fulcrum between the American continents and as such constitutes a critical region for understanding past patterns of socio-political development and interaction. Heavy vegetation, rugged topography, and remoteness have limited scientific investigation. This paper presents prehistoric patterns of settlement and landuse for a critical valley within the Mosquitia derived from airborne LiDAR scanning and field investigation. We show that (i) though today the valley is a wilderness it was densely inhabited in the past; (ii) that this population was organized into a three-tiered system composed of 19 settlements dominated by a city; and, (iii) that this occupation was embedded within a human engineered landscape. We also add to a growing body of literature that demonstrates the utility of LiDAR as means for rapid cultural assessments in undocumented regions for analysis and conservation. Our ultimate hope is for our work to promote protections to safeguard the unique and critically endangered Mosquitia ecosystem and other similar areas in need of preservation. PMID:27560962

  12. Invasive Shrub Mapping in an Urban Environment from Hyperspectral and LiDAR-Derived Attributes

    PubMed Central

    Chance, Curtis M.; Coops, Nicholas C.; Plowright, Andrew A.; Tooke, Thoreau R.; Christen, Andreas; Aven, Neal

    2016-01-01

    Proactive management of invasive species in urban areas is critical to restricting their overall distribution. The objective of this work is to determine whether advanced remote sensing technologies can help to detect invasions effectively and efficiently in complex urban ecosystems such as parks. In Surrey, BC, Canada, Himalayan blackberry (Rubus armeniacus) and English ivy (Hedera helix) are two invasive shrub species that can negatively affect native ecosystems in cities and managed urban parks. Random forest (RF) models were created to detect these two species using a combination of hyperspectral imagery, and light detection and ranging (LiDAR) data. LiDAR-derived predictor variables included irradiance models, canopy structural characteristics, and orographic variables. RF detection accuracy ranged from 77.8 to 87.8% for Himalayan blackberry and 81.9 to 82.1% for English ivy, with open areas classified more accurately than areas under canopy cover. English ivy was predicted to occur across a greater area than Himalayan blackberry both within parks and across the entire city. Both Himalayan blackberry and English ivy were mostly located in clusters according to a Local Moran’s I analysis. The occurrence of both species decreased as the distance from roads increased. This study shows the feasibility of producing highly accurate detection maps of plant invasions in urban environments using a fusion of remotely sensed data, as well as the ability to use these products to guide management decisions.

  13. Basic analysis of climate and urban bioclimate of Dar es Salaam, Tanzania

    NASA Astrophysics Data System (ADS)

    Ndetto, Emmanuel L.; Matzarakis, Andreas

    2013-10-01

    Better understanding of urban microclimate and bioclimate of any city is imperative today when the world is constrained by both urbanisation and global climate change. Urbanisation generally triggers changes in land cover and hence influencing the urban local climate. Dar es Salaam city in Tanzania is one of the fast growing cities. Assessment of its urban climate and the human biometeorological conditions was done using the easily available synoptic meteorological data covering the period 2001-2011. In particular, the physiologically equivalent temperature (PET) was calculated using the RayMan software and results reveal that the afternoon period from December to February (DJF season) is relatively the most thermal stressful period to human beings in Dar es Salaam where PET values of above 35 °C were found. Additionally, the diurnal cycle of the individual meteorological elements that influence the PET index were analysed and found that air temperature of 30-35 °C dominate the afternoon period from 12:00 to 15:00 hours local standard time at about 60 % of occurrence. The current results, though considered as preliminary to the ongoing urban climate study in the city, provide an insight on how urban climate research is of significant importance in providing useful climatic information for ensuring quality of life and wellbeing of city dwellers.

  14. 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.

  15. Detection of large above-ground biomass variability in lowland forest ecosystems by airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Jubanski, J.; Ballhorn, U.; Kronseder, K.; Franke, J.; Siegert, F.

    2013-06-01

    Quantification of tropical forest above-ground biomass (AGB) over large areas as input for Reduced Emissions from Deforestation and forest Degradation (REDD+) projects and climate change models is challenging. This is the first study which attempts to estimate AGB and its variability across large areas of tropical lowland forests in Central Kalimantan (Indonesia) through correlating airborne light detection and ranging (LiDAR) to forest inventory data. Two LiDAR height metrics were analysed, and regression models could be improved through the use of LiDAR point densities as input (R2 = 0.88; n = 52). Surveying with a LiDAR point density per square metre of about 4 resulted in the best cost / benefit ratio. We estimated AGB for 600 km of LiDAR tracks and showed that there exists a considerable variability of up to 140% within the same forest type due to varying environmental conditions. Impact from logging operations and the associated AGB losses dating back more than 10 yr could be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat classification for a 1 million ha study area where AGB values were based on site-specific field inventory data, regional literature estimates, and default values by the Intergovernmental Panel on Climate Change (IPCC) showed an overestimation of 43%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong greenhouse gas (GHG) emission estimates due to deforestation in climate models. For REDD+ projects this leads to inaccurate carbon stock estimates and consequently to significantly wrong REDD+ based compensation payments.

  16. 3-D earthquake surface displacements from differencing pre- and post-event LiDAR point clouds

    NASA Astrophysics Data System (ADS)

    Krishnan, A. K.; Nissen, E.; Arrowsmith, R.; Saripalli, S.

    2012-12-01

    The explosion in aerial LiDAR surveying along active faults across the western United States and elsewhere provides a high-resolution topographic baseline against which to compare repeat LiDAR datasets collected after future earthquakes. We present a new method for determining 3-D coseismic surface displacements and rotations by differencing pre- and post-earthquake LiDAR point clouds using an adaptation of the Iterative Closest Point (ICP) algorithm, a point set registration technique widely used in medical imaging, computer vision and graphics. There is no need for any gridding or smoothing of the LiDAR data and the method works well even with large mismatches in the density of the two point clouds. To explore the method's performance, we simulate pre- and post-event point clouds using real ("B4") LiDAR data on the southern San Andreas Fault perturbed with displacements of known magnitude. For input point clouds with ~2 points per square meter, we are able to reproduce displacements with a 50 m grid spacing and with horizontal and vertical accuracies of ~20 cm and ~4 cm. In the future, finer grids and improved precisions should be possible with higher shot densities and better survey geo-referencing. By capturing near-fault deformation in 3-D, LiDAR differencing with ICP will complement satellite-based techniques such as InSAR which map only certain components of the surface deformation and which often break down close to surface faulting or in areas of dense vegetation. It will be especially useful for mapping shallow fault slip and rupture zone deformation, helping inform paleoseismic studies and better constrain fault zone rheology. Because ICP can image rotations directly, the technique will also help resolve the detailed kinematics of distributed zones of faulting where block rotations may be common.

  17. Modeling Urban Growth Spatial Dynamics: Case studies of Addis Ababa and Dar es Salaam

    NASA Astrophysics Data System (ADS)

    Buchta, Katja; Abo El Wafa, Hany; Printz, Andreas; Pauleit, Stephan

    2013-04-01

    Rapid urbanization, and consequently, the dramatic spatial expansion of mostly informal urban areas increases the vulnerability of African cities to the effects of climate change such as sea level rise, more frequent flooding, droughts and heat waves. The EU FP 7 funded project CLUVA (Climate Change and Urban Vulnerability in Africa, www.cluva.eu) aims to develop strategies for minimizing the risks of natural hazards caused by climate change and to improve the coping capacity of African cities. Green infrastructure may play a particular role in climate change adaptation by providing ecosystem services for flood protection, stormwater retention, heat island moderation and provision of food and fuel wood. In this context, a major challenge is to gain a better understanding of the spatial and temporal dynamics of the cities and how these impact on green infrastructure and hence their vulnerability. Urban growth scenarios for two African cities, namely Addis Ababa, Ethiopia and Dar es Salaam, Tanzania, were developed based on a characterization of their urban morphology. A population growth driven - GIS based - disaggregation modeling approach was applied. Major impact factors influencing the urban dynamics were identified both from literature and interviews with local experts. Location based factors including proximity to road infrastructure and accessibility, and environmental factors including slope, surface and flood risk areas showed a particular impact on urban growth patterns. In Addis Ababa and Dar es Salaam, population density scenarios were modeled comparing two housing development strategies. Results showed that a densification scenario significantly decreases the loss of agricultural and green areas such as forests, bushland and sports grounds. In Dar es Salaam, the scenario of planned new settlements with a population density of max. 350 persons per hectare would lead until 2025 to a loss of agricultural land (-10.1%) and green areas (-6.6%). On the other

  18. 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

  19. Measuring the effects of morphological changes to sea turtle nesting beaches over time with LiDAR data

    NASA Astrophysics Data System (ADS)

    Yamamoto, Kristina H.; Anderson, Sharolyn J.; Sutton, Paul C.

    2015-10-01

    Sea turtle nesting beaches in southeastern Florida were evaluated for changes from 1999 to 2005 using LiDAR datasets. Changes to beach volume were correlated with changes in several elevation-derived characteristics, such as elevation and slope. In addition, these changes to beach geomorphology were correlated to changes in nest success, illustrating that beach alterations may affect sea turtle nesting behavior. The ability to use LiDAR datasets to quickly and efficiently conduct beach comparisons for habitat use represents another benefit to this high spatial resolution data.

  20. 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

  1. Three-dimensional building roof boundary extraction using high-resolution aerial image and LiDAR data

    NASA Astrophysics Data System (ADS)

    Dal Poz, A. P.; Fazan, Antonio J.

    2014-10-01

    This paper presents a semiautomatic method for rectilinear building roof boundary extraction, based on the integration of high-resolution aerial image and LiDAR (Light Detection and Ranging) data. The proposed method is formulated as an optimization problem, in which a snakes-based objective function is developed to represent the building roof boundaries in an object-space coordinate system. Three-dimensional polylines representing building roof boundaries are obtained by optimizing the objective function using the dynamic programming optimization technique. The results of our experiments showed that the proposed method satisfactorily performed the task of extracting different building roof boundaries from aerial image and LiDAR data.

  2. Object-Based Integration of Photogrammetric and LiDAR Data for Automated Generation of Complex Polyhedral Building Models

    PubMed Central

    Kim, Changjae; Habib, Ayman

    2009-01-01

    This research is concerned with a methodology for automated generation of polyhedral building models for complex structures, whose rooftops are bounded by straight lines. The process starts by utilizing LiDAR data for building hypothesis generation and derivation of individual planar patches constituting building rooftops. Initial boundaries of these patches are then refined through the integration of LiDAR and photogrammetric data and hierarchical processing of the planar patches. Building models for complex structures are finally produced using the refined boundaries. The performance of the developed methodology is evaluated through qualitative and quantitative analysis of the generated building models from real data. PMID:22346722

  3. Quantification of L-band InSAR decorrelation in volcanic terrains using airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    Sedze, M.; Heggy, E.; Jacquemoud, S.; Bretar, F.

    2011-12-01

    Repeat-pass InSAR LOS measurements of the Piton de La Fournaise (La Reunion Island, France) suffer from substantial phase decorrelation due to the occurrence of vegetation and ash deposits on the caldera and slopes of the edifice. To correct this deficiency, we combine normalized airborne LiDAR (Light Detection and Ranging) intensity data with spaceborne InSAR coherence images from ALOS PALSAR L-band acquired over the volcano in 2008 and 2009, following the 2007 major eruption. The fusion of the two data sets improves the calculation of coherence and the textural classification of different volcanic surfaces. For future missions considering both InSAR and/or LiDAR such as DESDynI (Deformation, Ecosystem Structure and Dynamics of Ice), such data fusion studies can provide a better analysis of the spatiotemporal variations in InSAR coherence in order to enhance the monitoring of pre-eruptive ground displacements. The airborne surveys conducted in 2008 and 2009, cover different types of vegetation and terrain roughness on the central and western parts of the volcano. The topographic data are first processed to generate a high-resolution digital terrain model (DTM) of the volcanic edifice with elevation accuracy better than 1 m. For our purposes, the phase variations caused by the surface relief can be eliminated using the LiDAR-derived DTM. Then normalized LiDAR intensities are correlated to the L-band polarimetric coherence for different zones of the volcano to assess the LiDAR-InSAR statistical behavior of different lava flows, pyroclastics, and vegetated surfaces. Results suggest that each volcanic terrain type is characterized by a unique LiDAR-InSAR histogram pattern. We identified four LiDAR-InSAR distinguished relations: (1) pahoehoe lava flow surfaces show an agglomerate histogram pattern which may be explained by low surface scattering and low wave penetration into the geological medium; (2) eroded a'a lava surfaces is characterized by high standard deviation

  4. Santa Barbara Cottage Hospital.

    PubMed

    1984-01-01

    The 465-bed Santa Barbara Cottage Hospital is the largest medical facility on the California coast between Los Angeles and the San Francisco bay area. The hospital dates back to 1888, when a group of local citizens began raising funds to build a "cottage-style" hospital for the growing community. Their original plans called for a complex in which each medical specialty would be housed in a separate bungalow. Even then, however, such a decentralized plan was too costly, so work began instead on a single cottage for all hospital departments. The first Cottage Hospital opened in 1891, with 25 beds housed in a two story Victorian building. Now a hugh medical complex employing some 1,500 people, the hospital continues to be called "Cottage" after the original home-like building. Rodney J. Lamb has been Hospital Administrator for the last 30 years.

  5. Light Detection and Ranging (LiDAR): What We Can and Cannot See in the Forest for the Trees

    NASA Astrophysics Data System (ADS)

    Edson, Curtis B.

    Recently concerns over anthropogenic carbon pollution have received increased global attention and research in forest biomass and carbon sequestration has gained momentum. Light Detection and Ranging (LiDAR) remote sensing has in the last decade demonstrated forest measurement and biomass estimation potential. The project objective was to compare LiDAR forest biomass estimates to traditional field biomass estimates in a conifer predominant forest located in the Pacific Northwest region of the United States. Chapter 2 of this dissertation investigated mapping-grade GPS accuracy in determining tree locations. Results indicated that post processing of coded pseudorange satellite signals is the most accurate of those we tested for GPS surveying under a conifer dominant forest canopy. Chapter 3 compared LiDAR, total station, and GPS receiver discrete point elevations and DEMs across a range of forest settings. Average total station plot elevation differences ranged from -0.06 m (SD 0.40) to -0.59 m (SD 0.23) indicating that LiDAR elevations are higher than actual elevations. Average plot GPS elevation differences ranged from 0.24 (SD 1.55) to 2.82 m (SD 4.58), and from 0.27 (SD 2.33) to 2.69 m (SD 5.06) for LiDAR DEMs. Chapter 4 assessed LiDAR's ability to measure three-dimensional forest structure and estimate biomass using single stem (trees and shrubs) remote sensing. The LiDAR data tree extraction computer software programs FUSION, TreeVaW, and watershed segmentation were compared. LiDAR spatial accuracy assessment resulted in overall average error and standard deviation (SD) for FUSION, TreeVaW, and watershed segmentation of 2.05 m (SD 1.67 m), 2.19 m (SD 1.83 m), and 2.31 m (SD 1.94 m) respectively. Overall average LiDAR tree height error and standard deviations (SD) respectively for FUSION, TreeVaW and watershed segmentation were -0.09 m (SD 2.43 m), 0.28 m (SD 1.86 m), and 0.22 m (2.45 m) in even-age, uneven-age, and old growth plots combined; and for one

  6. A Bayesian Hierarchical Model for Spatio-Temporal Prediction and Uncertainty Assessment Using Repeat LiDAR Acquisitions for the Kenai Peninsula, AK, USA

    NASA Astrophysics Data System (ADS)

    Babcock, C. R.; Andersen, H. E.; Finley, A. O.; Cook, B.; Morton, D. C.

    2015-12-01

    Models using repeat LiDAR and field campaigns may be one mechanism to monitor carbon storage and flux in forested regions. Considering the ability of multi-temporal LiDAR to estimate growth, it is not surprising that there is great interest in developing forest carbon monitoring strategies that rely on repeated LiDAR acquisitions. Allowing for sparser field campaigns, LiDAR stands to make monitoring forest carbon cheaper and more efficient than field-only sampling procedures. Here, we look to the spatio-temporally data-rich Kenai Peninsula in Alaska to examine the potential for Bayesian spatio-temporal mapping of forest carbon storage and uncertainty. The framework explored here can predict forest carbon through space and time, while formally propagating uncertainty through to prediction. Bayesian spatio-temporal models are flexible frameworks allowing for forest growth processes to be formally integrated into the model. By incorporating a mechanism for growth---using temporally repeated field and LiDAR data---we can more fully exploit the information-rich inventory network to improve prediction accuracy. LiDAR data for the Kenai Peninsula has been collected on four different occasions---spatially coincident LiDAR strip samples in 2004, 09 and 14, along with a wall-to-wall collection in 2008. There were 436 plots measured twice between 2002 and 2014. LiDAR was acquired at least once over most inventory plots with many having LiDAR collected during 2, 3 or 4 different campaigns. Results from this research will impact how forests are inventoried. It is too expensive to monitor terrestrial carbon using field-only sampling strategies and currently proposed LiDAR model-based techniques lack the ability to properly utilize temporally repeated and misaligned data. Bayesian hierarchical spatio-temporal models offer a solution to these shortcomings and allow for formal predictive error assessment, which is useful for policy development and decision making.

  7. Hospital diversification strategy.

    PubMed

    Eastaugh, Steven R

    2014-01-01

    To determine the impact of health system restructuring on the levels of hospital diversification and operating ratio this article analyzed 94 teaching hospitals and 94 community hospitals during the period 2008-2013. The 47 teaching hospitals are matched with 47 other teaching hospitals experiencing the same financial market position in 2008, but with different levels of preference for risk and diversification in their strategic plan. Covariates in the analysis included levels of hospital competition and the degree of local government planning (for example, highly regulated in New York, in contrast to Texas). Moreover, 47 nonteaching community hospitals are matched with 47 other community hospitals in 2008, having varying manager preferences for service-line diversification and risk. Diversification and operating ratio are modeled in a two-stage least squares (TSLS) framework as jointly dependent. Institutional diversification is found to yield better financial position, and the better operating profits provide the firm the wherewithal to diversify. Some services are in a growth phase, like bariatric weight-loss surgery and sleep disorder clinics. Hospital managers' preferences for risk/return potential were considered. An institution life cycle hypothesis is advanced to explain hospital behavior: boom and bust, diversification, and divestiture, occasionally leading to closure or merger. PMID:25223156

  8. Hospital diversification strategy.

    PubMed

    Eastaugh, Steven R

    2014-01-01

    To determine the impact of health system restructuring on the levels of hospital diversification and operating ratio this article analyzed 94 teaching hospitals and 94 community hospitals during the period 2008-2013. The 47 teaching hospitals are matched with 47 other teaching hospitals experiencing the same financial market position in 2008, but with different levels of preference for risk and diversification in their strategic plan. Covariates in the analysis included levels of hospital competition and the degree of local government planning (for example, highly regulated in New York, in contrast to Texas). Moreover, 47 nonteaching community hospitals are matched with 47 other community hospitals in 2008, having varying manager preferences for service-line diversification and risk. Diversification and operating ratio are modeled in a two-stage least squares (TSLS) framework as jointly dependent. Institutional diversification is found to yield better financial position, and the better operating profits provide the firm the wherewithal to diversify. Some services are in a growth phase, like bariatric weight-loss surgery and sleep disorder clinics. Hospital managers' preferences for risk/return potential were considered. An institution life cycle hypothesis is advanced to explain hospital behavior: boom and bust, diversification, and divestiture, occasionally leading to closure or merger.

  9. Beyond Cross Sections; LiDAR in Support of Sprague River geomorphology Studies, Klamath Basin, Oregon

    NASA Astrophysics Data System (ADS)

    O'Connor, J. E.; McDowell, P. F.; Lind, P.; Haluska, T.; Jackson, K.

    2007-12-01

    LiDAR terrain data was collected in November 2004 for 750 square kilometers of the Sprague River valley, Oregon, by Watershed Sciences, Inc., under contract with the Klamath Tribes. This coverage, obtained to support multiple ecologic analysis and restoration activities in the Klamath Basin, encompasses about 90 km of valley- bottom corridor for the main Sprague River as well as downstream alluvial sections of principal tributaries, including 15 km of the Sycan River, 15 km of the South Fork Sprague River, and 10 km of the North Fork Sprague River. Acquisition conditions were leaf-off at normal fall low flow. Assessment of the vertical divergence between 967 surveyed points and the laser points gave a RMSE of 0.052 m with a standard deviation of 0.051 m. The resulting bare-earth 1-m grid has been used for geomorphic mapping, paleo- and historical-channel mapping, qualitative and quantitative analysis of floodplain morphology, and assessment of channel incision over various timescales.4 Using the high resolution topography in combination with floodplain stratigraphy, we delineated the late Holocene (post 7.7 ka Mazama eruption) active floodplain. The morphology of this floodplain reveals processes locally important in forming the Sprague and Sycan river floodplains, including avulsion, meander abandonment and filling, lateral bar building, deposition by crevasses, and lateral migration. Mapping present and paleo-channel positions determined from historic photos and maps onto the LiDAR digital terrain model, coupled with augering to determine channel gravel depths, has allowed local assessment of long term channel incision and aggradation over the last several thousand years. Reaches of possible historic incision have also been delineated by comparing floodplain elevation to channel elevation in an essentially continuous manner along the valley corridor. This analysis reveals multiple reaches where the 1940 channel, as depicted on aerial photographs, is apparently

  10. LiDAR Acquisition for the GeoEarthScope Community

    NASA Astrophysics Data System (ADS)

    Phillips, D. A.; Furlong, K.; Bruhn, R.; Dolan, J.; Oldow, J.; Prentice, C.; Rubin, C.; Burbank, D.; Wernicke, B.; Wesnousky, S.

    2007-12-01

    LiDAR acquisition is a key component of the GeoEarthScope Initiative. LiDAR provides data with a broad range of applicability to many of the EarthScope goals. A working group was convened to identify primary targets for data acquisition, rank these targets, and propose a data acquisition scheme to effectively acquire these data within the GeoEarthScope funding time frame. The Regional Targets are: a.) Northern California - including the San Andreas Fault north of Parkfield, and other major strands of the San Andreas Fault system; b.) Southern California - including the Garlock Fault, Eastern California Shear zone south of the Garlock, and the Elsinore Fault; c.) Eastern California, Walker Lane, and Basin and Range fault systems - including faults of the Eastern California Shear Zone north of the Garlock Fault; d.) Intermountain Seismic Belt - including the Wasatch Fault, Teton Fault, and Yellowstone Park area; e.) Alaska - including the Castle Mountain and Denali Faults; f.) Cascadia - including the Little Salmon fault zone in southern Cascadia, the Calawah Fault in the Washington forearc, and imagery in the Yakima Fold belt termination. The Working Group recognized that available funding would likely preclude obtaining data from all high priority sites The Working Group wrestled with several important issues that affect the data acquisition plan and the prioritization of sites. The WG tried to develop a plan that honored the primary EarthScope goals, recognizing the limited funding available. In particular, in order to maximize the coverage obtained and serve the broadest community, the WG elected to utilize relatively narrow swath widths (typically 1 km, widened to 2+km in key regions), which allowed more line-kilometers of data to be obtained. The unavoidable consequences of this choice are that areas away from the main fault strands will be unsampled. Data acquisition is underway. The Northern California acquisition (supplemented by financial support from state

  11. Building a LiDAR point cloud simulator: Testing algorithms for high resolution topographic change

    NASA Astrophysics Data System (ADS)

    Carrea, Dario; Abellán, Antonio; Derron, Marc-Henri; Jaboyedoff, Michel

    2014-05-01

    Terrestrial laser technique (TLS) is becoming a common tool in Geosciences, with clear applications ranging from the generation of a high resolution 3D models to the monitoring of unstable slopes and the quantification of morphological changes. Nevertheless, like every measurement techniques, TLS still has some limitations that are not clearly understood and affect the accuracy of the dataset (point cloud). A challenge in LiDAR research is to understand the influence of instrumental parameters on measurement errors during LiDAR acquisition. Indeed, different critical parameters interact with the scans quality at different ranges: the existence of shadow areas, the spatial resolution (point density), and the diameter of the laser beam, the incidence angle and the single point accuracy. The objective of this study is to test the main limitations of different algorithms usually applied on point cloud data treatment, from alignment to monitoring. To this end, we built in MATLAB(c) environment a LiDAR point cloud simulator able to recreate the multiple sources of errors related to instrumental settings that we normally observe in real datasets. In a first step we characterized the error from single laser pulse by modelling the influence of range and incidence angle on single point data accuracy. In a second step, we simulated the scanning part of the system in order to analyze the shifting and angular error effects. Other parameters have been added to the point cloud simulator, such as point spacing, acquisition window, etc., in order to create point clouds of simple and/or complex geometries. We tested the influence of point density and vitiating point of view on the Iterative Closest Point (ICP) alignment and also in some deformation tracking algorithm with same point cloud geometry, in order to determine alignment and deformation detection threshold. We also generated a series of high resolution point clouds in order to model small changes on different environments

  12. Applying modified high resolution airborne LiDAR DTM for floodplain mapping

    NASA Astrophysics Data System (ADS)

    Vetter, M.; Jochem, A.; Franke, M.; Schöberl, F.; Stötter, J.; Werthmann, M.

    2009-04-01

    Today, airborne LiDAR derived digital terrain models (DTM) are used in the research context and various scientific disciplines. In hydrology such high resolution DTMs are used for computing flood simulations, calculating roughness maps, floodplain mapping, etc. The presented approach outlines the strength of a LiDAR derived DTM (1m) in comparison to a photogrammetric derived DTM (10m). By implementing an interpolated river bed model, which is derived by using terrestrial measured river cross sections and hence modifying the high resolution DTM for hydraulic task floodplain mapping and modeling routines, could be improved. The river bed interpolation routine includes an automatic bridge detection algorithm to delete bridge pillars in the relevant river cross sections. Furthermore, the position of riverbanks, which are a contributing factor in the field of hydraulic modeling and influence the results of the hydraulic simulations, can be detected. Once the DTM is modified, river cross profiles can be extracted directly on each position along the river axis and can be used as input for hydraulic models. In this study the software HEC-RAS is used to calculate different floodplain areas on the basis of the HQ30, HQ100 and HQ200 flood scenarios, which are calibrated on key data of the flood in August 2005. The comparison of the floodplain area in the city of Innsbruck (Tyrol, Austria), modeled on the basis of a modified LiDAR derived DTM, with those from the HORA study (Hochwasserrisikozonierung Austria), shows remarkable differences. These differences result from (i) the different hydraulic modeling methods and (ii) the used DTMs, which HORA does not consider flood protection measures. The results show that the resolution of the used DTM is the determining factor for modeling adequate floodplain areas whereas the applied hydraulic model has secondary effects. The grade of accuracy attained by this approach is reflected by the numbers ,of flooding affected buildings (e

  13. Long-term persistence of throughfall yield assessed by small footprint LiDAR data

    NASA Astrophysics Data System (ADS)

    Bischoff, Sebastian; Levia, Delphis F.; Nieschulze, Jens; Schulz, Florian; Michalzik, Beate

    2016-04-01

    Throughfall (TF) represents an important relocation mechanism for the spatial distribution of intercepted precipitation and hence associated nutrients in wooded ecosystems. To date, a broad range of studies showed that the spatial patterns of TF distribution exhibit a pronounced temporal stability. These studies, however, have examined TF temporal stability at the tree scale or they were computed from event-based data. Here, we seek to evaluate the utility of temporally aggregated TF data at one, three, and six year intervals to determine whether such long-term TF monitoring data could serve as the basis for TF temporal persistence measurements for both beech and spruce forests. In addition, we examine the temporal persistence of TF in relation to small footprint LiDAR data. In context of the German Science Foundation (DFG) founded "Biodiversity Exploratories" (www.biodiversity-exploratories.de) we studied water-bound nutrient fluxes on a set of three differently managed forest plots (spruce plantation, age class forest beech, unmanaged beech) in central Germany throughout the vegetation periods of 2010 - 2015. For long-term monitoring purposes, TF samples were collected in biweekly routine sampling intervals using X-shaped transects of 20 bulk samplers (axis length 32 m) per experimental plot. In this study, we aim to identify canopy structural parameters explaining the temporal patterns observed. We therefore used small footprint LiDAR (Light Detection And Ranging) data to calculate several canopy structural parameters on base of a gridded canopy model (grid cell resolution = 0.75 m). As LiDAR allows a three-dimensional description of the complex forest canopy structure it might help to extend our understanding of complex canopy processes influencing the spatial dispersal of precipitation water, and hence associated nutrient fluxes, in wooded ecosystems. Preliminary data analysis reveals that normalized TF values identify a number of TF collectors on each of the

  14. Prevalence of Cryptosporidium parvum/hominis, Entamoeba histolytica and Giardia lamblia among Young Children with and without Diarrhea in Dar es Salaam, Tanzania

    PubMed Central

    Tellevik, Marit G.; Moyo, Sabrina J.; Blomberg, Bjørn; Hjøllo, Torunn; Maselle, Samuel Y.; Langeland, Nina; Hanevik, Kurt

    2015-01-01

    Background 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. Methodology/Principal Findings 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). Conclusions Cryptosporidium infection is common among young Tanzanian children with diarrhea

  15. Geometric Calibration and Radiometric Correction of LiDAR Data and Their Impact on the Quality of Derived Products

    PubMed Central

    Habib, Ayman F.; Kersting, Ana P.; Shaker, Ahmed; Yan, Wai-Yeung

    2011-01-01

    LiDAR (Light Detection And Ranging) systems are capable of providing 3D positional and spectral information (in the utilized spectrum range) of the mapped surface. Due to systematic errors in the system parameters and measurements, LiDAR systems require geometric calibration and radiometric correction of the intensity data in order to maximize the benefit from the collected positional and spectral information. This paper presents a practical approach for the geometric calibration of LiDAR systems and radiometric correction of collected intensity data while investigating their impact on the quality of the derived products. The proposed approach includes the use of a quasi-rigorous geometric calibration and the radar equation for the radiometric correction of intensity data. The proposed quasi-rigorous calibration procedure requires time-tagged point cloud and trajectory position data, which are available to most of the data users. The paper presents a methodology for evaluating the impact of the geometric calibration on the relative and absolute accuracy of the LiDAR point cloud. Furthermore, the impact of the geometric calibration and radiometric correction on land cover classification accuracy is investigated. The feasibility of the proposed methods and their impact on the derived products are demonstrated through experimental results using real data. PMID:22164121

  16. National and Global: A History of Scholars' Experiences with Research at the University of Dar Es Salaam, Tanzania (1961-Present)

    ERIC Educational Resources Information Center

    Jamison, Amy J.

    2010-01-01

    In this dissertation, I draw on research carried out at the University of Dar es Salaam (UDSM), Tanzania in 2008 to examine Tanzanian academics' experience with research throughout the history of this institution. This dissertation is designed as an historical case study and investigates how economic and political changes in Tanzania's…

  17. Intimate Partner Violence and the Association with HIV Risk Behaviors among Young Men in Dar Es Salaam, Tanzania

    ERIC Educational Resources Information Center

    Maman, Suzanne; Yamanis, Thespina; Kouyoumdjian, Fiona; Watt, Melissa; Mbwambo, Jessie

    2010-01-01

    There is growing evidence of the association between gender-based violence and HIV from the perspective and experiences of women. The purpose of this study is to examine these associations from the perspective of young men living in Dar es Salaam, Tanzania. A community-based sample of 951 men were interviewed, of whom 360 had sex in the past 6…

  18. Assessing Surface Fuel Hazard in Coastal Conifer Forests through the Use of LiDAR Remote Sensing

    NASA Astrophysics Data System (ADS)

    Koulas, Christos

    The research problem that this thesis seeks to examine is a method of predicting conventional fire hazards using data drawn from specific regions, namely the Sooke and Goldstream watershed regions in coastal British Columbia. This thesis investigates whether LiDAR data can be used to describe conventional forest stand fire hazard classes. Three objectives guided this thesis: to discuss the variables associated with fire hazard, specifically the distribution and makeup of fuel; to examine the relationship between derived LiDAR biometrics and forest attributes related to hazard assessment factors defined by the Capitol Regional District (CRD); and to assess the viability of the LiDAR biometric decision tree in the CRD based on current frameworks for use. The research method uses quantitative datasets to assess the optimal generalization of these types of fire hazard data through discriminant analysis. Findings illustrate significant LiDAR-derived data limitations, and reflect the literature in that flawed field application of data modelling techniques has led to a disconnect between the ways in which fire hazard models have been intended to be used by scholars and the ways in which they are used by those tasked with prevention of forest fires. It can be concluded that a significant trade-off exists between computational requirements for wildfire simulation models and the algorithms commonly used by field teams to apply these models with remote sensing data, and that CRD forest management practices would need to change to incorporate a decision tree model in order to decrease risk.

  19. 3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data

    NASA Astrophysics Data System (ADS)

    Van der Zande, Dimitry; Stuckens, Jan; Verstraeten, Willem W.; Mereu, Simone; Muys, Bart; Coppin, Pol

    2011-10-01

    A methodology is presented that describes the direct interaction of a forest canopy with incoming radiation using terrestrial LiDAR based vegetation structure in a radiative transfer model. The proposed 'Voxel-based Light Interception Model' (VLIM) is designed to estimate the Percentage of Above Canopy Light (PACL) at any given point of the forest scene. First a voxel-based representation of trees is derived from terrestrial LiDAR data as structural input to model and analyze the light interception of canopies at near leaf level scale. Nine virtual forest stands of three species (beech, poplar, plantain) were generated by means of stochastic L-systems as tree descriptors. Using ray tracer technology hemispherical LiDAR measurements were simulated inside these virtual forests. The leaf area density (LAD) estimates derived from the LiDAR datasets resulted in a mean absolute error of 32.57% without correction and 16.31% when leaf/beam interactions were taken into account. Next, comparison of PACL estimates, computed with VLIM with fully rendered light distributions throughout the canopy based on the L-systems, yielded a mean absolute error of 5.78%. This work shows the potential of the VLIM to model both instantaneous light interception by a canopy as well as average light distributions for entire seasons.

  20. Fine-spatial scale predictions of understory species using climate- and LiDAR-derived terrain and canopy metrics

    NASA Astrophysics Data System (ADS)

    Nijland, Wiebe; Nielsen, Scott E.; Coops, Nicholas C.; Wulder, Michael A.; Stenhouse, Gordon B.

    2014-01-01

    Food and habitat resources are critical components of wildlife management and conservation efforts. The grizzly bear (Ursus arctos) has diverse diets and habitat requirements particularly for understory plant species, which are impacted by human developments and forest management activities. We use light detection and ranging (LiDAR) data to predict the occurrence of 14 understory plant species relevant to bear forage and compare our predictions with more conventional climate- and land cover-based models. We use boosted regression trees to model each of the 14 understory species across 4435 km2 using occurrence (presence-absence) data from 1941 field plots. Three sets of models were fitted: climate only, climate and basic land and forest covers from Landsat 30-m imagery, and a climate- and LiDAR-derived model describing both the terrain and forest canopy. Resulting model accuracies varied widely among species. Overall, 8 of 14 species models were improved by including the LiDAR-derived variables. For climate-only models, mean annual precipitation and frost-free periods were the most important variables. With inclusion of LiDAR-derived attributes, depth-to-water table, terrain-intercepted annual radiation, and elevation were most often selected. This suggests that fine-scale terrain conditions affect the distribution of the studied species more than canopy conditions.

  1. Approaching a more Complete Picture of Rockfall Activity: Seismic and LiDAR Detection, Loaction and Volume Estimates

    NASA Astrophysics Data System (ADS)

    Dietze, Michael; Mohadjer, Solmaz; Turowski, Jens; Ehlers, Todd; Hovius, Niels

    2016-04-01

    Rockfall activity in steep alpine landscapes is often difficult to survey due to its infrequent nature. Classic approaches are limited by temporal and spatial resolution. In contrast, seismic monitoring provides access to catchment-wide analysis of activity patterns in rockfall-dominated environments. The deglaciated U-shaped Lauterbrunnen Valley in the Bernese Oberland, Switzerland, is a perfect example of such landscapes. It was instrumented with up to six broadband seismometers and repeatedly surveyed by terrestrial LiDAR to provide independent validation data. During August-October 2014 and April-June 2015 more than 23 (LiDAR) to hundred (seismic) events were detected. Their volumes range from < 0.01 to 5.80 cubic metres as detected by LiDAR. The evolution of individual events (i.e., precursor activity, detachment, falling phase, impact, talus cone activity) can be quantified in terms of location and duration. For events that consist of single detachments rather than a series of releases, volume scaling relationships are possible. Seismic monitoring approaches are well-suited for studying not only the rockfall process but also for understanding the geomorphic framework and boundary conditions that control such processes in a comprehensive way. Taken together, the combined LiDAR and seismic monitoring approach provides high fidelity spatial and temporal resolution of individual events.

  2. Testing the Suitability of a Terrestrial 2D LiDAR Scanner for Canopy Characterization of Greenhouse Tomato Crops.

    PubMed

    Llop, Jordi; Gil, Emilio; Llorens, Jordi; Miranda-Fuentes, Antonio; Gallart, Montserrat

    2016-09-06

    Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with electronic methods difficult. Therefore, the accuracy of the terrestrial 2D LiDAR sensor is evaluated for determining canopy parameters related to volume and density and established useful correlations between manual and electronic parameters for leaf area estimation. Experiments were performed in three commercial tomato greenhouses with a paired plantation system. In the electronic characterization, a LiDAR sensor scanned the plant pairs from both sides. The canopy height, canopy width, canopy volume, and leaf area were obtained. From these, other important parameters were calculated, like the tree row volume, leaf wall area, leaf area index, and leaf area density. Manual measurements were found to overestimate the parameters compared with the LiDAR sensor. The canopy volume estimated with the scanner was found to be reliable for estimating the canopy height, volume, and density. Moreover, the LiDAR scanner could assess the high variability in canopy density along rows and hence is an important tool for generating canopy maps.

  3. Testing the Suitability of a Terrestrial 2D LiDAR Scanner for Canopy Characterization of Greenhouse Tomato Crops

    PubMed Central

    Llop, Jordi; Gil, Emilio; Llorens, Jordi; Miranda-Fuentes, Antonio; Gallart, Montserrat

    2016-01-01

    Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with electronic methods difficult. Therefore, the accuracy of the terrestrial 2D LiDAR sensor is evaluated for determining canopy parameters related to volume and density and established useful correlations between manual and electronic parameters for leaf area estimation. Experiments were performed in three commercial tomato greenhouses with a paired plantation system. In the electronic characterization, a LiDAR sensor scanned the plant pairs from both sides. The canopy height, canopy width, canopy volume, and leaf area were obtained. From these, other important parameters were calculated, like the tree row volume, leaf wall area, leaf area index, and leaf area density. Manual measurements were found to overestimate the parameters compared with the LiDAR sensor. The canopy volume estimated with the scanner was found to be reliable for estimating the canopy height, volume, and density. Moreover, the LiDAR scanner could assess the high variability in canopy density along rows and hence is an important tool for generating canopy maps. PMID:27608025

  4. 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.

  5. Geometric calibration and radiometric correction of LiDAR data and their impact on the quality of derived products.

    PubMed

    Habib, Ayman F; Kersting, Ana P; Shaker, Ahmed; Yan, Wai-Yeung

    2011-01-01

    LiDAR (Light Detection And Ranging) systems are capable of providing 3D positional and spectral information (in the utilized spectrum range) of the mapped surface. Due to systematic errors in the system parameters and measurements, LiDAR systems require geometric calibration and radiometric correction of the intensity data in order to maximize the benefit from the collected positional and spectral information. This paper presents a practical approach for the geometric calibration of LiDAR systems and radiometric correction of collected intensity data while investigating their impact on the quality of the derived products. The proposed approach includes the use of a quasi-rigorous geometric calibration and the radar equation for the radiometric correction of intensity data. The proposed quasi-rigorous calibration procedure requires time-tagged point cloud and trajectory position data, which are available to most of the data users. The paper presents a methodology for evaluating the impact of the geometric calibration on the relative and absolute accuracy of the LiDAR point cloud. Furthermore, the impact of the geometric calibration and radiometric correction on land cover classification accuracy is investigated. The feasibility of the proposed methods and their impact on the derived products are demonstrated through experimental results using real data.

  6. Calculating the ecosystem service of water storage in isolated wetlands using LiDAR in north central Florida, USA (presentation)

    EPA Science Inventory

    This study used remotely-sensed Light Detection and Ranging (LiDAR) data to estimate potential water storage capacity of isolated wetlands in north central Florida. The data were used to calculate the water storage potential of >8500 polygons identified as isolated wetlands. We f...

  7. Provision of Vocational Skills Education to Orphans: Lessons from Orphanage Centres in Dar es Salaam City, Tanzania

    ERIC Educational Resources Information Center

    Meli, Benjamin Mbeba

    2015-01-01

    This paper utilises data from a study that investigated the efficacy of vocational skills training provided to orphans from three orphanages in Temeke District, Dar es Salaam. The three orphanage centres that were studied are Kurasini National Children Home, Saudia and Don Bosco Vocational Centre. The sample comprised of 45 orphans, an official…

  8. Characterization and classification of vegetation canopy structure and distribution within the Great Smoky Mountains National Park using LiDAR

    SciTech Connect

    Kumar, Jitendra; HargroveJr., William Walter; Norman, Steven P; Hoffman, Forrest M; Newcomb, Doug

    2015-01-01

    Vegetation canopy structure is a critically important habit characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape pro- vided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify and analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and to characterize and map the vegetation canopy structures for 139,859 hectares (540 sq. miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.

  9. Testing the Suitability of a Terrestrial 2D LiDAR Scanner for Canopy Characterization of Greenhouse Tomato Crops.

    PubMed

    Llop, Jordi; Gil, Emilio; Llorens, Jordi; Miranda-Fuentes, Antonio; Gallart, Montserrat

    2016-01-01

    Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with electronic methods difficult. Therefore, the accuracy of the terrestrial 2D LiDAR sensor is evaluated for determining canopy parameters related to volume and density and established useful correlations between manual and electronic parameters for leaf area estimation. Experiments were performed in three commercial tomato greenhouses with a paired plantation system. In the electronic characterization, a LiDAR sensor scanned the plant pairs from both sides. The canopy height, canopy width, canopy volume, and leaf area were obtained. From these, other important parameters were calculated, like the tree row volume, leaf wall area, leaf area index, and leaf area density. Manual measurements were found to overestimate the parameters compared with the LiDAR sensor. The canopy volume estimated with the scanner was found to be reliable for estimating the canopy height, volume, and density. Moreover, the LiDAR scanner could assess the high variability in canopy density along rows and hence is an important tool for generating canopy maps. PMID:27608025

  10. Ecosystem Mapping Approaches Based on Vegetation Structure Using NEON Prototype Airborne LiDAR and Field Data

    NASA Astrophysics Data System (ADS)

    Krause, K.; Emery, W. J.; Barnett, D.; Petroy, S. B.; Meier, C. L.; Wessman, C. A.

    2014-12-01

    Remote sensing is a powerful tool for measuring the current state of vegetation and monitoring changes over time with repeated data collections. Airborne Light Detection and Ranging (LiDAR) data is especially well suited for mapping 3D vegetation structure. In 2010, the National Ecological Observatory Network (NEON) contracted LiDAR and hyperspectral airborne data collections over the Ordway-Swisher Biological Station (OSBS). Ground truth campaigns were also conducted in 2010, 2011, and 2014 including structural measurements and generation of species lists for a set of ground validation plots. The vegetation communities at OSBS can be characterized by the Florida Natural Areas Inventory (FNAI) classification system, with a large area of the property belonging to the Sandhill community. For this study, classification algorithm training locations are hand selected for each FNAI community type using photo-interpretation. A series of LiDAR metrics are calculated on the discrete return point clouds and derived digital elevation (DEM) and canopy height models (CHM). A decision tree classification algorithm is run using R package "rpart". A main goal of the project is to relate the LiDAR metrics used by the decision tree to direct canopy structural quantities. For instance, the canopy 75th minus the 50th percentile height in the LiDAR point clouds are related to the uniformity and light penetration in the upper canopy. A prototype of the decision tree achieved a classification accuracy of 89% on the training data itself, suggesting that some locations in different FNAI vegetation communities have similar structure and could not be distinguished in the LiDAR metrics used. An improved decision tree is currently under development which will include more training locations and more LiDAR metrics as input features. Results from this improved model will be presenting using the NEON ground truth locations as an independent and quantitative validation measure of the decision tree

  11. Urban flood modelling combining top-view LiDAR data with ground-view SfM observations

    NASA Astrophysics Data System (ADS)

    Meesuk, Vorawit; Vojinovic, Zoran; Mynett, Arthur E.; Abdullah, Ahmad F.

    2015-01-01

    Remote Sensing technologies are capable of providing high-resolution spatial data needed to set up advanced flood simulation models. Amongst them, aerial Light Detection and Ranging (LiDAR) surveys or Airborne Laser Scanner (ALS) systems have long been used to provide digital topographic maps. Nowadays, Remote Sensing data are commonly used to create Digital Terrain Models (DTMs) for detailed urban-flood modelling. However, the difficulty of relying on top-view LiDAR data only is that it cannot detect whether passages for floodwaters are hidden underneath vegetated areas or beneath overarching structures such as roads, railroads, and bridges. Such (hidden) small urban features can play an important role in urban flood propagation. In this paper, a complex urban area of Kuala Lumpur, Malaysia was chosen as a study area to simulate the extreme flooding event that occurred in 2003. Three different DTMs were generated and used as input for a two-dimensional (2D) urban flood model. A top-view LiDAR approach was used to create two DTMs: (i) a standard LiDAR-DTM and (ii) a Filtered LiDAR-DTM taking into account specific ground-view features. In addition, a Structure from Motion (SfM) approach was used to detect hidden urban features from a sequence of ground-view images; these ground-view SfM data were then combined with top-view Filtered LiDAR data to create (iii) a novel Multidimensional Fusion of Views-Digital Terrain Model (MFV-DTM). These DTMs were then used as a basis for the 2D urban flood model. The resulting dynamic flood maps are compared with observations at six measurement locations. It was found that when applying only top-view DTMs as input data, the flood simulation results appear to have mismatches in both floodwater depths and flood propagation patterns. In contrast, when employing the top-ground-view fusion approach (MFV-DTM), the results not only show a good agreement in floodwater depth, but also simulate more correctly the floodwater dynamics around

  12. Application of High-resolution Aerial LiDAR Data in Calibration of a Two-dimensional Urban Flood Simulation

    NASA Astrophysics Data System (ADS)

    Piotrowski, J.; Goska, R.; Chen, B.; Krajewski, W. F.; Young, N.; Weber, L.

    2009-12-01

    In June 2008, the state of Iowa experienced an unprecedented flood event which resulted in an economic loss of approximately $2.88 billion. Flooding in the Iowa River corridor, which exceeded the previous flood of record by 3 feet, devastated several communities, including Coralville and Iowa City, home to the University of Iowa. Recognizing an opportunity to capture a unique dataset detailing the impacts of the historic flood, the investigators contacted the National Center for Airborne Laser Mapping (NCALM), which performed an aerial Light Detection and Ranging (LiDAR) survey along the Iowa River. The survey, conducted immediately following the flood peak, provided coverage of a 60-mile reach. The goal of the present research is to develop a process by which flood extents and water surface elevations can be accurately extracted from the LiDAR data set and to evaluate the benefit of such data in calibrating one- and two-dimensional hydraulic models. Whereas data typically available for model calibration include sparsely distributed point observations and high water marks, the LiDAR data used in the present study provide broad-scale, detailed, and continuous information describing the spatial extent and depth of flooding. Initial efforts were focused on a 10-mile, primarily urban reach of the Iowa River extending from Coralville Reservoir, a United States Army Corps of Engineers flood control project, downstream through the Coralville and Iowa City. Spatial extent and depth of flooding were estimated from the LiDAR data. At a given cross-sectional location, river channel and floodplain measurements were compared. When differences between floodplain and river channel measurements were less than a standard deviation of the vertical uncertainty in the LiDAR survey, floodplain measurements were classified as flooded. A flood water surface DEM was created using measurements classified as flooded. A two-dimensional, depth-averaged numerical model of a 10-mile reach of

  13. Reexamination of Faulting in the Tahoe Basin Using Airborne LiDAR Data and Seismic CHIRP Imagery

    NASA Astrophysics Data System (ADS)

    Schmauder, G. C.; Kent, G.; Smith, K. D.; Driscoll, N. W.; Maloney, J. M.

    2011-12-01

    Faulting across the Tahoe basin has been mapped using a combination of multibeam sonar, airborne Light Detection and Ranging (LiDAR), and high-resolution seismic CHIRP imagery. In August 2010, the Tahoe Regional Planning Agency (TRPA) collected 941 square kilometers of airborne LiDAR data in the Tahoe basin using a Leica ALS50 Phase II Laser system mounted on a Cessna Caravan 208B aircraft; our group was involved with data specification, selection of contractor and data QC. These data have a resolution of 11.82 points per square meter and a vertical accuracy of 3.5 centimeters. The high data resolution has allowed us to map with ease the many fault scarps associated with the three major active fault zones in the Tahoe basin, which include the West Tahoe-Dollar Point fault zone, the Stateline fault, and the Incline Village fault. By using the airborne LiDAR data, we were able to identify previously unmapped fault segments throughout the Tahoe basin. Future application of terrestrial LiDAR using an I-Site 4400 laser scanner at selected sites will provide better control and resolution of the fault scarp characteristics. This will allow us to not only ground truth the airborne LiDAR, but also look for subtle features that may be indicative of dextral motion on faults otherwise displaying predominantly normal displacement. Finally, to refine fault locations beneath Lake Tahoe, Fallen Leaf Lake and Cascade Lake, we collected additional CHIRP imagery using an Edgetech Subscan system, in some cases to groundtruth the new LiDAR fault data (i.e., Cascade Lake). By combining these images with the LiDAR, multibeam data and new multispectral imagery, we were able to link previously unknown segments of the faults and identify continuity in the individual fault systems. From our results, we have developed a much-improved model of the fault systems within the Lake Tahoe basin. Our model provides us with a better understanding of the tectonic environment of the basin and may help

  14. Measuring Hospital Productivity

    PubMed Central

    Ruchlin, Hirsch S.; Leveson, Irving

    1974-01-01

    This study presents a comprehensive method for quantifying hospital output and estimating hospital productivity. A number of less comprehensive productivity measures that can be quantified from data available from regional third-party payers and from the American Hospital Association are also developed and evaluated as proxies for the comprehensive measure, which is based on local area data. Methods are discussed for estimating the necessary variables on a regional or national level. PMID:4461703

  15. A gradient-constrained morphological filtering algorithm for airborne LiDAR

    NASA Astrophysics Data System (ADS)

    Li, Yong; Wu, Huayi; Xu, Hanwei; An, Ru; Xu, Jia; He, Qisheng

    2013-12-01

    This paper presents a novel gradient-constrained morphological filtering algorithm for bare-earth extraction from light detection and ranging (LiDAR) data. Based on the gradient feature points determined by morphological half-gradients, the potential object points are located prior to filtering. Innovative gradient-constrained morphological operations are created, which are executed only for the potential object points. Compared with the traditional morphological operations, the new operations reduce many meaningless operations for object removal and consequently decrease the possibility of losing terrain to a great extent. The applicability and reliability of this algorithm are demonstrated by evaluating the filtering performance for fifteen sample datasets in various complex scenes. The proposed algorithm is found to achieve a high level of accuracy compared with eight other filtering algorithms tested by the International Society for Photogrammetry and Remote Sensing. Moreover, the proposed algorithm has minimal error oscillation for different landscapes, which is important for quality control of digital terrain model generation.

  16. 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

  17. Urban mosquitoes, situational publics, and the pursuit of interspecies separation in Dar es Salaam

    PubMed Central

    KELLY, ANN H.; LEZAUN, JAVIER

    2014-01-01

    Recent work in anthropology points to the recognition of multispecies entanglements as the grounds for a more ethical politics. In this article, we examine efforts to control mosquitoes in Dar es Salaam, Tanzania, as an example of the laborious tasks of disentanglement that characterize public health interventions. The mosquito surveillance and larval elimination practices of an urban malaria control program offer an opportunity to observe how efforts to create distance between species relate to the physical and civic textures of the city. Seen in the particular context of the contemporary African metropolis, the work of public health appears less a matter of control than a commitment to constant urban maintenance and political mobilization. PMID:25429167

  18. 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

  19. Automated extraction of urban trees from mobile LiDAR point clouds

    NASA Astrophysics Data System (ADS)

    Fan, W.; Chenglu, W.; Jonathan, L.

    2016-03-01

    This paper presents an automatic algorithm to localize and extract urban trees from mobile LiDAR point clouds. First, in order to reduce the number of points to be processed, the ground points are filtered out from the raw point clouds, and the un-ground points are segmented into supervoxels. Then, a novel localization method is proposed to locate the urban trees accurately. Next, a segmentation method by localization is proposed to achieve objects. Finally, the features of objects are extracted, and the feature vectors are classified by random forests trained on manually labeled objects. The proposed method has been tested on a point cloud dataset. The results prove that our algorithm efficiently extracts the urban trees.

  20. Subtropical Forest Biomass Estimation Using Airborne LiDAR and Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Pang, Yong; Li, Zengyuan

    2016-06-01

    Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF's (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.

  1. Understanding Household Behavioral Risk Factors for Diarrheal Disease in Dar es Salaam: A Photovoice Community Assessment

    PubMed Central

    Badowski, Natalie; Castro, Cynthia M.; Montgomery, Maggie; Pickering, Amy J.; Mamuya, Simon; Davis, Jennifer

    2011-01-01

    Whereas Tanzania has seen considerable improvements in water and sanitation infrastructure over the past 20 years, the country still faces high rates of childhood morbidity from diarrheal diseases. This study utilized a qualitative, cross-sectional, modified Photovoice method to capture daily activities of Dar es Salaam mothers. A total of 127 photographs from 13 households were examined, and 13 interviews were conducted with household mothers. The photographs and interviews revealed insufficient hand washing procedures, unsafe disposal of wastewater, uncovered household drinking water containers, a lack of water treatment prior to consumption, and inappropriate toilets for use by small children. The interviews revealed that mothers were aware and knowledgeable of the risks of certain household practices and understood safer alternatives, yet were restricted by the perceived impracticality and financial constraints to make changes. The results draw attention to the real economic and behavioral challenges faced in reducing the spread of disease. PMID:21969836

  2. Joint Temperature-Lasing Mode Compensation for Time-of-Flight LiDAR Sensors

    PubMed Central

    Alhashimi, Anas; Varagnolo, Damiano; Gustafsson, Thomas

    2015-01-01

    We propose an expectation maximization (EM) strategy for improving the precision of time of flight (ToF) light detection and ranging (LiDAR) scanners. The novel algorithm statistically accounts not only for the bias induced by temperature changes in the laser diode, but also for the multi-modality of the measurement noises that is induced by mode-hopping effects. Instrumental to the proposed EM algorithm, we also describe a general thermal dynamics model that can be learned either from just input-output data or from a combination of simple temperature experiments and information from the laser’s datasheet. We test the strategy on a SICK LMS 200 device and improve its average absolute error by a factor of three. PMID:26690445

  3. 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

  4. Analysis of airborne LiDAR as a basis for digital soil mapping in Alpine areas

    NASA Astrophysics Data System (ADS)

    Kringer, K.; Tusch, M.; Geitner, C.; Meißl, G.; Rutzinger, M.

    2009-04-01

    Especially in mountainous regions like the Alps the formation of soil is highly influenced by relief characteristics. Among all factors included in Jenny's (1941) model for soil development, relief is the one most commonly used in approaches to create digital soil maps and to derive soil properties from secondary data sources (McBratney et al. 2003). Elevation data, first order (slope, aspect) and second order derivates (plan, profile and cross-sectional curvature) as well as complex morphometric parameters (various landform classifications, e.g., Wood 1996) and compound indices (e.g., topographic wetness indices, vertical distance to drainage network, insolation) can be calculated from digital elevation models (DEM). However, while being an important source of information for digital soil mapping on small map scales, "conventional" DEMs are of limited use for the design of large scale conceptual soil maps for small areas due to rather coarse raster resolutions with cell sizes ranging from 20 to 100 meters. Slight variations in elevation and small landform features might not be discernible even though they might have a significant effect to soil formation, e.g., regarding the influence of groundwater in alluvial soils or the extent of alluvial fans. Nowadays, Airborne LiDAR (Light Detection And Ranging) provides highly accurate data for the elaboration of high-resolution digital terrain models (DTM) even in forested areas. In the project LASBO (Laserscanning in der Bodenkartierung) the applicability of digital terrain models derived from LiDAR for the identification of soil-relevant geomorphometric parameter is investigated. Various algorithms which were initially designed for coarser raster data are applied on high-resolution DTMs. Test areas for LASBO are located in the region of Bruneck (Italy) and near the municipality of Kramsach in the Inn Valley (Austria). The freely available DTM for Bruneck has a raster resolution of 2.5 meters while in Kramsach a DTM with

  5. Fusion of terrestrial LiDAR and tomographic mapping data for 3D karst landform investigation

    NASA Astrophysics Data System (ADS)

    Höfle, B.; Forbriger, M.; Siart, C.; Nowaczinski, E.

    2012-04-01

    Highly detailed topographic information has gained in importance for studying Earth surface landforms and processes. LiDAR has evolved into the state-of-the-art technology for 3D data acquisition on various scales. This multi-sensor system can be operated on several platforms such as airborne LS (ALS), mobile LS (MLS) from moving vehicles or stationary on ground (terrestrial LS, TLS). In karst research the integral investigation of surface and subsurface components of solution depressions (e.g. sediment-filled dolines) is required to gather and quantify the linked geomorphic processes such as sediment flux and limestone dissolution. To acquire the depth of the different subsurface layers, a combination of seismic refraction tomography (SRT) and electrical resistivity tomography (ERT) is increasingly applied. This multi-method approach allows modeling the extension of different subsurface media (i.e. colluvial fill, epikarst zone and underlying basal bedrock). Subsequent fusion of the complementary techniques - LiDAR surface and tomographic subsurface data - first-time enables 3D prospection and visualization as well as quantification of geomorphometric parameters (e.g. depth, volume, slope and aspect). This study introduces a novel GIS-based method for semi-automated fusion of TLS and geophysical data. The study area is located in the Dikti Mountains of East Crete and covers two adjacent dolines. The TLS data was acquired with a Riegl VZ-400 scanner from 12 scan positions located mainly at the doline divide. The scan positions were co-registered using the iterative closest point (ICP) algorithm of RiSCAN PRO. For the digital elevation rasters a resolution of 0.5 m was defined. The digital surface model (DSM) of the study was derived by moving plane interpolation of all laser points (including objects) using the OPALS software. The digital terrain model (DTM) was generated by iteratively "eroding" objects in the DSM by minimum filter, which additionally accounts for

  6. Joint Temperature-Lasing Mode Compensation for Time-of-Flight LiDAR Sensors.

    PubMed

    Alhashimi, Anas; Varagnolo, Damiano; Gustafsson, Thomas

    2015-01-01

    We propose an expectation maximization (EM) strategy for improving the precision of time of flight (ToF) light detection and ranging (LiDAR) scanners. The novel algorithm statistically accounts not only for the bias induced by temperature changes in the laser diode, but also for the multi-modality of the measurement noises that is induced by mode-hopping effects. Instrumental to the proposed EM algorithm, we also describe a general thermal dynamics model that can be learned either from just input-output data or from a combination of simple temperature experiments and information from the laser's datasheet. We test the strategy on a SICK LMS 200 device and improve its average absolute error by a factor of three. PMID:26690445

  7. 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

    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)

  8. Assessing the potential for leaf-off LiDAR data to model canopy closure in temperate deciduous forests

    NASA Astrophysics Data System (ADS)

    Parent, Jason R.; Volin, John C.

    2014-09-01

    Estimates of canopy closure have many important uses in forest management and ecological research. Field measurements, however, are typically not practical to acquire over expansive areas or for large numbers of locations. This problem has been addressed, in recent years, through the use of airborne light detection and ranging (LiDAR) technology which has proven effective in modeling canopy closure remotely. The techniques developed to use LiDAR for this purpose have been designed and evaluated for datasets acquired during leaf-on conditions. However, a large number of LiDAR datasets are acquired during leaf-off conditions since their primary purpose is to generate bare-earth Digital Elevation Models. In this paper, we develop and evaluate techniques for leveraging small-footprint leaf-off LiDAR data to model leaf-on canopy closure in temperate deciduous forests. We evaluate three techniques for modeling canopy closure: (1) the canopy-to-total-return-ratio (CTRR), (2) the canopy-to-total-pixel-ratio (CTPR), and (3) the hemispherical-viewshed (HV). The first technique has been used widely, in various forms, and has been shown to be effective with leaf-on LiDAR datasets. The CTRR technique that we tested uses the first-return LiDAR data only. The latter two techniques are new contributions that we develop and present in this paper. These techniques use Canopy Height Models (CHM) to detect significant gaps in the forest canopy which are of primary importance in estimating closure. The techniques we tested each showed good promise for predicting canopy closure using leaf-off LiDAR data with the CTPR and HV models having particularly high correlations with closure estimates from hemispherical photographs. The CTRR model had performance on par with results from previous studies that used leaf-on LiDAR, although, with leaf-off data the model tended to be negatively biased with respect to species having simple and compound leaf types and positively biased for coniferous

  9. Central line infections - hospitals

    MedlinePlus

    ... infection; CVC - infection; Central venous device - infection; Infection control - central line infection; Nosocomial infection - central line infection; Hospital acquired infection - central line infection; Patient safety - central ...

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  11. Tracking geomorphic signatures of watershed suburbanization with multitemporal LiDAR

    NASA Astrophysics Data System (ADS)

    Jones, Daniel K.; Baker, Matthew E.; Miller, Andrew J.; Jarnagin, S. Taylor; Hogan, Dianna M.

    2014-08-01

    Urban development practices redistribute surface materials through filling, grading, and terracing, causing drastic changes to the geomorphic organization of the landscape. Many studies document the hydrologic, biologic, or geomorphic consequences of urbanization using space-for-time comparisons of disparate urban and rural landscapes. However, no previous studies have documented geomorphic changes from development using multiple dates of high-resolution topographic data at the watershed scale. This study utilized a time series of five sequential light detection and ranging (LiDAR) derived digital elevation models (DEMs) to track watershed geomorphic changes within two watersheds throughout development (2002-2008) and across multiple spatial scales (0.01-1 km2). Development-induced changes were compared against an undeveloped forested watershed during the same time period. Changes in elevations, slopes, hypsometry, and surface flow pathways were tracked throughout the development process to assess watershed geomorphic alterations. Results suggest that development produced an increase in sharp topographic breaks between relatively flat surfaces and steep slopes, replacing smoothly varying hillslopes and leading to greater variation in slopes. Examinations of flowpath distributions highlight systematic modifications that favor rapid convergence in unchanneled upland areas. Evidence of channel additions in the form of engineered surface conduits is apparent in comparisons of pre- and post-development stream maps. These results suggest that topographic modification, in addition to impervious surfaces, contributes to altered hydrologic dynamics observed in urban systems. This work highlights important considerations for the use of repeat LiDAR flights in analyzing watershed change through time. Novel methods introduced here may allow improved understanding and targeted mitigation of the processes driving geomorphic changes during development and help guide future

  12. Comparison of Morphometry of Active Landslides in Differing Geological Settings Using LiDAR-derived DEMs

    NASA Astrophysics Data System (ADS)

    Kasai, M.; Kuda, T.; Okuda, S.; Fujisawa, K.; Asahina, T.; Matsuda, M.

    2008-12-01

    Deep seated landslides develop fine-scale geomorphic forms such as cracks and internal scars, forming rough surfaces as they move. Because the data density of LiDAR measurement is of sufficient detail to extract these forms, DEM-derived surface fabric filters can be used to estimate their recent activity. To utilize LiDAR data for this purpose, it is first necessary to establish the relationships that exist between filter values and actual surface features, and slide activities. These relationships are expected to differ between sites, reflecting the local geological and topographic characteristics, and the resolution and grid size of DEMs. In this presentation, these relationships are investigated at three study sites in Japan. The major geologies were Tertiary Tuff at two sites and sheared Mesozoic sedimentary rocks at the other. DEM cell sizes ranged from 1 to 5 m. The eigenvalue ratio, which represents the 3-dimensional surface roughness, was calculated from the DEMs. The spatial pattern of cell values within landslide blocks was compared with local surface features and slide conditions observed in the field. Results suggest that similar surface features were likely to be expressed in a higher and wider range of eigenvalue ratios as DEM grid size increased. Change in grid size, however, did not greatly alter their spatial distribution patterns. Consequently, the different major hillslope processes could be highlighted by comparing the patterns of recently active blocks from each site. In the Mesozoic sedimentary rock site, active slides contained steep slope parts which were characterized by a higher proportion of cells with an eigenvalue ratio < 2.5, when compared with surrounding areas. These low values mostly represent cracks in bedrock outcrops and scars. In contrast, the softer underlying rocks at the Tuff sites, has allowed landslides to evolve with gentle slopes, while maintaining a slow but consistent downslope motion. Here, there were a high proportion

  13. Quantifying Urban Forest Structure Using Crown-Level Fusion of Imaging Spectroscopy and LiDAR

    NASA Astrophysics Data System (ADS)

    Alonzo, M.; Bookhagen, B.; McFadden, J. P.; Roberts, D. A.

    2013-12-01

    The magnitude and distribution of ecosystem services provided by urban trees depend largely on canopy fractional cover, leaf area index, and species. Most efforts to quantify the structure and function of urban forests have been limited to measuring canopy extent or extrapolation of forest structure and function from plot sample inventories. Hyperspectral remote sensing has shown promise as a means for discriminating tree species. However, in many urban settings, tree species diversity and within-class spectral variability are both high, resulting in low classification accuracies. Canopy structural variables derived from LiDAR can provide additional information, such as tree height and crown width, that do not duplicate the information contained in the spectral variables. In this research we use crown-level fusion of hyperspectral and airborne LiDAR data to map 29 common tree species in Santa Barbara, California. From a discretized, full-waveform lidar dataset, we isolate canopy and, using watershed segmentation, delineate individual crowns. The crown segments are overlaid on Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data and all suitable vegetation spectra are extracted. These same segments are used to extract lidar variables. The two datasets are fused at the crown-object level and classified using canonical discriminant analysis. Overall accuracy for the 29 species, based on correctly classified canopy area, is 83%. When including species outside of the training set, the overall classification accuracy to the tree type level was 90%. At the pixel level, using only spectral data, the classification accuracy of the trained species was 68%. These results indicate the potential for wall-to-wall mapping of an urban forest to the species or tree type level, depending on species diversity and availability of training data. Further, we find that imperfect segmentation is not an insurmountable obstacle to crown-level analysis.

  14. Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR

    USGS Publications Warehouse

    Jones, Benjamin M.; Stoker, Jason M.; Gibbs, Ann E.; Grosse, Guido; Romanovsky, Vladimir E.; Douglas, Thomas A.; Kinsman, Nichole E.M.; Richmond, Bruce M.

    2013-01-01

    Increases in air, permafrost, and sea surface temperature, loss of sea ice, the potential for increased wave energy, and higher river discharge may all be interacting to escalate erosion of arctic coastal lowland landscapes. Here we use airborne light detection and ranging (LiDAR) data acquired in 2006 and 2010 to detect landscape change in a 100 km2 study area on the Beaufort Sea coastal plain of northern Alaska. We detected statistically significant change (99% confidence interval), defined as contiguous areas (>10 m2) that had changed in height by at least 0.55 m, in 0.3% of the study region. Erosional features indicative of ice-rich permafrost degradation were associated with ice-bonded coastal, river, and lake bluffs, frost mounds, ice wedges, and thermo-erosional gullies. These features accounted for about half of the area where vertical change was detected. Inferred thermo-denudation and thermo-abrasion of coastal and river bluffs likely accounted for the dominant permafrost-related degradational processes with respect to area (42%) and volume (51%). More than 300 thermokarst pits significantly subsided during the study period, likely as a result of storm surge flooding of low-lying tundra (<1.4 m asl) as well as the lasting impact of warm summers in the late-1980s and mid-1990s. Our results indicate that repeat airborne LiDAR can be used to detect landscape change in arctic coastal lowland regions at large spatial scales over sub-decadal time periods.

  15. Genetic Map of Triticale Integrating Microsatellite, DArT and SNP Markers

    PubMed Central

    Tyrka, Mirosław; Tyrka, Dorota; Wędzony, Maria

    2015-01-01

    Triticale (×Triticosecale Wittm) is an economically important crop for fodder and biomass production. To facilitate the identification of markers for agronomically important traits and for genetic and genomic characteristics of this species, a new high-density genetic linkage map of triticale was constructed using doubled haploid (DH) population derived from a cross between cultivars ‘Hewo’ and ‘Magnat’. The map consists of 1615 bin markers, that represent 50 simple sequence repeat (SSR), 842 diversity array technology (DArT), and 16888 DArTseq markers mapped onto 20 linkage groups assigned to the A, B, and R genomes of triticale. No markers specific to chromosome 7R were found, instead mosaic linkage group composed of 1880 highly distorted markers (116 bins) from 10 wheat chromosomes was identified. The genetic map covers 4907 cM with a mean distance between two bins of 3.0 cM. Comparative analysis in respect to published maps of wheat, rye and triticale revealed possible deletions in chromosomes 4B, 5A, and 6A, as well as inversion in chromosome 7B. The number of bin markers in each chromosome varied from 24 in chromosome 3R to 147 in chromosome 6R. The length of individual chromosomes ranged between 50.7 cM for chromosome 2R and 386.2 cM for chromosome 7B. A total of 512 (31.7%) bin markers showed significant (P < 0.05) segregation distortion across all chromosomes. The number of 8 the segregation distorted regions (SDRs) were identified on 1A, 7A, 1B, 2B, 7B (2 SDRs), 5R and 6R chromosomes. The high-density genetic map of triticale will facilitate fine mapping of quantitative trait loci, the identification of candidate genes and map-based cloning. PMID:26717308

  16. Using LiDAR, RADAR, and Optical data to improve a NFMS in Kalimantan, Indonesia

    NASA Astrophysics Data System (ADS)

    Hagen, S. C.; Saatchi, S. S.; Braswell, B. H., Jr.; Palace, M. W.; Salas, W.; Walker, S.; Hoekman, D.; Ipsan, C.; Brown, S.; Sullivan, F.

    2014-12-01

    Around the world, governments are establishing national forest monitoring systems (NFMS) that use a combination of remote sensing and ground-based forest carbon inventory approaches to estimate anthropogenic forest-related greenhouse gas emissions and removals. The NFMS forms the link between historical assessments and current/future assessments of forests, enabling consistency in the data and information to support the implementation of REDD+ activities. The creation of a reliable, transparent, and comprehensive NFMS is currently limited by a dearth of relevant data that are accurate, low-cost, and spatially resolved at subnational scales. With funding from a 3-year NASA Carbon Monitoring System project beginning in September 2013, we are developing, evaluating, and validating several critical components of an NFMS in Kalimantan, Indonesia, focusing on the use of LiDAR and radar imagery for improved carbon stock and forest degradation information. Here, we present results from an initial analysis of a spatially extensive set of LiDAR data collected across the Indonesian provinces on the island of Borneo together with RADAR and optical data. Our objectives are to evaluate sensor and platform tradeoffs systematically against in situ investments, as well as provide detailed tracking and characterization of uncertainty in a cost-benefit framework. Kalimantan is an ideal area to evaluate the use of remote sensing methods because measuring forest carbon stocks and their human caused changes with a high degree of certainty on the ground can be difficult. While our work focuses at the subnational scale for Kalimantan, we are targeting these methods for applicability across broader geographies and for implementation at various scales.

  17. 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.

  18. Assessing and Correcting Topographic Effects on Forest Canopy Height Retrieval Using Airborne LiDAR Data

    PubMed Central

    Duan, Zhugeng; Zhao, Dan; Zeng, Yuan; Zhao, Yujin; Wu, Bingfang; Zhu, Jianjun

    2015-01-01

    Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs). Normalized canopy height was calculated by subtracting the elevation of centres of gravity from the elevation of point cloud. First, individual tree crown boundaries are obtained by carrying out segmentation on the DOM. Second, point clouds of the individual trees are extracted based on the boundaries. Third, precise DEM is derived from the point cloud which is classified by a multi-scale curvature classification algorithm. Finally, a height weighted correction method is applied to correct the topological effects. The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots. The results show that the terrain impacts the canopy height of individual trees in that the downslope side of the tree trunk is elevated and the upslope side is depressed. This further affects the extraction of the location and crown of individual trees. A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively. PMID:26016907

  19. Assessing and correcting topographic effects on forest canopy height retrieval using airborne LiDAR data.

    PubMed

    Duan, Zhugeng; Zhao, Dan; Zeng, Yuan; Zhao, Yujin; Wu, Bingfang; Zhu, Jianjun

    2015-01-01

    Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs). Normalized canopy height was calculated by subtracting the elevation of centres of gravity from the elevation of point cloud. First, individual tree crown boundaries are obtained by carrying out segmentation on the DOM. Second, point clouds of the individual trees are extracted based on the boundaries. Third, precise DEM is derived from the point cloud which is classified by a multi-scale curvature classification algorithm. Finally, a height weighted correction method is applied to correct the topological effects. The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots. The results show that the terrain impacts the canopy height of individual trees in that the downslope side of the tree trunk is elevated and the upslope side is depressed. This further affects the extraction of the location and crown of individual trees. A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively. PMID:26016907

  20. Data Archiving and Distribution of LiDAR and Derived Datasets in the Philippines

    NASA Astrophysics Data System (ADS)

    Tupas, M. E. A.; Lat, S. C.; Magturo, R. A.

    2016-06-01

    LiDAR programs in the Philippines have been generating valuable resource and hazard information for most of the country at a substantial rate since 2012. Significant progress have been made due to the programs design of engaging 16 Universities and research institutions spatially distributed across the country. Because of this, data has been accumulating at a brisk rate which poses significant technical and logistic issues. While a central node, the University of the Philippines, Diliman, handles data acquisition, pre-processing, and quality checking, processing and ground validation are devolved to the various nodes. For this setup to be successful, an efficient data access and distribution system should be in place. In this paper, we discuss the spatial data infrastructure and data access protocols implemented by the program. At the center of the data access and distribution operations is LiPAD or our LiDAR portal for archiving and distribution. LiPAD is built on open source technologies, established web standards, and protocols. At its back-end a central data archive has been established using state of the art Object Storage technology to store both raw, processed Lidar and derived data sets. Catalog of available data sets ranging from data acquisition foot prints, to DEM coverages, to derived products such as flood hazard, and crop suitability are viewable and accessible on the main site based on the popular GeoNode application. Data exchange is performed using varying protocols to address various logistical problems. Given the various challenges the program is successful in distributing data sets not just to partner processing nodes but to other stakeholders where main requesters include national agencies and general research and academic institutions.

  1. 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.

  2. Open-Source Digital Elevation Model (DEMs) Evaluation with GPS and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Khalid, N. F.; Din, A. H. M.; Omar, K. M.; Khanan, M. F. A.; Omar, A. H.; Hamid, A. I. A.; Pa'suya, M. F.

    2016-09-01

    Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model (ASTER GDEM), Shuttle Radar Topography Mission (SRTM), and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) are freely available Digital Elevation Model (DEM) datasets for environmental modeling and studies. The quality of spatial resolution and vertical accuracy of the DEM data source has a great influence particularly on the accuracy specifically for inundation mapping. Most of the coastal inundation risk studies used the publicly available DEM to estimated the coastal inundation and associated damaged especially to human population based on the increment of sea level. In this study, the comparison between ground truth data from Global Positioning System (GPS) observation and DEM is done to evaluate the accuracy of each DEM. The vertical accuracy of SRTM shows better result against ASTER and GMTED10 with an RMSE of 6.054 m. On top of the accuracy, the correlation of DEM is identified with the high determination of coefficient of 0.912 for SRTM. For coastal zone area, DEMs based on airborne light detection and ranging (LiDAR) dataset was used as ground truth data relating to terrain height. In this case, the LiDAR DEM is compared against the new SRTM DEM after applying the scale factor. From the findings, the accuracy of the new DEM model from SRTM can be improved by applying scale factor. The result clearly shows that the value of RMSE exhibit slightly different when it reached 0.503 m. Hence, this new model is the most suitable and meets the accuracy requirement for coastal inundation risk assessment using open source data. The suitability of these datasets for further analysis on coastal management studies is vital to assess the potentially vulnerable areas caused by coastal inundation.

  3. Tracking geomorphic signatures of watershed suburbanization with multi-temporal LiDAR

    USGS Publications Warehouse

    Jones, Daniel K.; Baker, Matthew E.; Miller, Andrew J.; Jarnagin, S. Taylor; Hogan, Dianna M.

    2014-01-01

    Urban development practices redistribute surface materials through filling, grading, and terracing, causing drastic changes to the geomorphic organization of the landscape. Many studies document the hydrologic, biologic, or geomorphic consequences of urbanization using space-for-time comparisons of disparate urban and rural landscapes. However, no previous studies have documented geomorphic changes from development using multiple dates of high-resolution topographic data at the watershed scale. This study utilized a time series of five sequential light detection and ranging (LiDAR) derived digital elevation models (DEMs) to track watershed geomorphic changes within two watersheds throughout development (2002–2008) and across multiple spatial scales (0.01–1 km2). Development-induced changes were compared against an undeveloped forested watershed during the same time period. Changes in elevations, slopes, hypsometry, and surface flow pathways were tracked throughout the development process to assess watershed geomorphic alterations. Results suggest that development produced an increase in sharp topographic breaks between relatively flat surfaces and steep slopes, replacing smoothly varying hillslopes and leading to greater variation in slopes. Examinations of flowpath distributions highlight systematic modifications that favor rapid convergence in unchanneled upland areas. Evidence of channel additions in the form of engineered surface conduits is apparent in comparisons of pre- and post-development stream maps. These results suggest that topographic modification, in addition to impervious surfaces, contributes to altered hydrologic dynamics observed in urban systems. This work highlights important considerations for the use of repeat LiDAR flights in analyzing watershed change through time. Novel methods introduced here may allow improved understanding and targeted mitigation of the processes driving geomorphic changes during development and help guide future

  4. Assessing and correcting topographic effects on forest canopy height retrieval using airborne LiDAR data.

    PubMed

    Duan, Zhugeng; Zhao, Dan; Zeng, Yuan; Zhao, Yujin; Wu, Bingfang; Zhu, Jianjun

    2015-05-26

    Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs). Normalized canopy height was calculated by subtracting the elevation of centres of gravity from the elevation of point cloud. First, individual tree crown boundaries are obtained by carrying out segmentation on the DOM. Second, point clouds of the individual trees are extracted based on the boundaries. Third, precise DEM is derived from the point cloud which is classified by a multi-scale curvature classification algorithm. Finally, a height weighted correction method is applied to correct the topological effects. The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots. The results show that the terrain impacts the canopy height of individual trees in that the downslope side of the tree trunk is elevated and the upslope side is depressed. This further affects the extraction of the location and crown of individual trees. A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively.

  5. 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.

  6. Evaluating dryland ecological and river restoration using repeat LiDAR and hydrological monitoring

    NASA Astrophysics Data System (ADS)

    Henderson, W. M.; DeLong, S.

    2012-12-01

    Recent improvements in the collection of multitemporal, high-resolution topographic data such as Light Detection and Ranging (LiDAR) have done a great deal to increase our ability to quantify the details of landscape change. Both Terrestrial Laser Scanning (TLS) and Airborne Laser Swath Mapping (ALSM) can be used to easily assess how Earth surface processes affect landscape form to a level of precision that was previously more difficult to attain. A comprehensive approach using ALSM, TLS-TLS comparison, and hydrological monitoring is being used to assess the effectiveness of a large scale ecological and river restoration effort by the Cuenca los Ojos Foundation at San Bernardino Ranch near Agua Prieta, Sonora, Mexico. In the study area, historical arroyo cutting and changes in land use led to the abandonment of a ciénega wetland and resulted in widespread ecological destruction. The current land managers have employed engineering methods in order to restore stream and ciénega ecology, including the installation of large rock gabions, earthen berms, and concrete spillways along channels. Our goal is to test the hypothesis that the use of dam and gabion structures leads to stream aggradation, flash flood dampening, and ultimately, increased available water and reestablishment of historic wetland plant and animal communities. We present results from LiDAR change detection that includes 2007-2011 ALSM to TLS change, and several 2011-2012 TLS-TLS comparisons. We also present results from streamflow monitoring, field observation, and monitoring of shallow groundwater and soil moisture conditions. Preliminary results show that channel aggradation occurs rapidly upstream of engineered structures. However, the apparent dampening of sediment transport by the structures leads to less aggradation and even incision immediately downstream of structures. Peak flood flows are decreased by the reservoirs formed behind large earthen berms. After several years of water retention

  7. Terrestrial LiDAR monitoring of rock slope-channel coupling

    NASA Astrophysics Data System (ADS)

    Bell, R.; Blöthe, J. H.; Meyer, N. K.; Hoffmann, T.; Hoffert, H.; Kreiner, D.; Elverfeldt, K. V.

    2009-04-01

    In steep terrain, various types of landslides (e.g. rock falls, debris flows and slides) are important erosional processes which often have a major impact on fluvial systems. On the one hand, they may divert river channels to opposite slopes or even block entire river channels, leading to the formation of landslide-dammed lakes. On the other hand, rivers prepare or even trigger landslides by undercutting slopes, which again will have an impact on the river channel. Our focus is on two study areas. One of them, the Schlichem Valley, is located in the Swabian Alb (SW-Germany), a lower mountain range consisting of Jurassic sedimentary rocks forming a cuesta landscape. There, the focus is on a larger landslide complex which blocked the river Schlichem three times during the 18th century and which is still active. Recent activity, especially at the location where the landslide enters the fluvial system, is investigated using Terrestrial LiDAR monitoring. The second study area is located in the Gesaeuse National Park in the Austrian Alps. There, various geomorphic environments are investigated by Terrestrial LiDAR including a vertical rock face in Dachstein limestone, which talus slope is directly coupled to the river Enns. The talus slope is built up by rock fall deposits, eroded mainly through smaller debris flow events. Furthermore, the talus slope is undercut by flood events of the river Enns. In this study a concept and first results are presented. They suggest how rock slope processes and their interactions with river channels can be monitored.

  8. Deconstructing a Polygenetic Landscape Using LiDAR and Multi-Resolution Analysis

    NASA Astrophysics Data System (ADS)

    Houser, C.; Barrineau, C. P.; Dobreva, I. D.; Bishop, M. P.

    2015-12-01

    In many earth surface systems characteristic morphologies are associated with various regimes both past and present. Aeolian systems contain a variety of features differentiated largely by morphometric differences, which in turn reflect age and divergent process regimes. Using quantitative analysis of high-resolution elevation data to generate detailed information regarding these characteristic morphometries enables geomorphologists to effectively map process regimes from a distance. Combined with satellite imagery and other types of remotely sensed data, the outputs can even help to delineate phases of activity within aeolian systems. The differentiation of regimes and identification of relict features together enables a greater level of rigor to analyses leading to field-based investigations, which are highly dependent on site-specific historical contexts that often obscure distinctions between separate process-form regimes. We present results from a Principal Components Analysis (PCA) performed on a LiDAR-derived elevation model of a largely stabilized aeolian system in South Texas. The resulting components are layered and classified to generate a map of aeolian morphometric signatures for a portion of the landscape. Several of these areas do not immediately appear to be aeolian in nature in satellite imagery or LiDAR-derived models, yet field observations and historical imagery reveal the PCA did in fact identify stabilized and relict dune features. This methodology enables researchers to generate a morphometric classification of the land surface. We believe this method is a valuable and innovative tool for researchers identifying process regimes within a study area, particularly in field-based investigations that rely heavily on site-specific context.

  9. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

    USGS Publications Warehouse

    Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

  10. Genetic Map of Triticale Integrating Microsatellite, DArT and SNP Markers.

    PubMed

    Tyrka, Mirosław; Tyrka, Dorota; Wędzony, Maria

    2015-01-01

    Triticale (×Triticosecale Wittm) is an economically important crop for fodder and biomass production. To facilitate the identification of markers for agronomically important traits and for genetic and genomic characteristics of this species, a new high-density genetic linkage map of triticale was constructed using doubled haploid (DH) population derived from a cross between cultivars 'Hewo' and 'Magnat'. The map consists of 1615 bin markers, that represent 50 simple sequence repeat (SSR), 842 diversity array technology (DArT), and 16888 DArTseq markers mapped onto 20 linkage groups assigned to the A, B, and R genomes of triticale. No markers specific to chromosome 7R were found, instead mosaic linkage group composed of 1880 highly distorted markers (116 bins) from 10 wheat chromosomes was identified. The genetic map covers 4907 cM with a mean distance between two bins of 3.0 cM. Comparative analysis in respect to published maps of wheat, rye and triticale revealed possible deletions in chromosomes 4B, 5A, and 6A, as well as inversion in chromosome 7B. The number of bin markers in each chromosome varied from 24 in chromosome 3R to 147 in chromosome 6R. The length of individual chromosomes ranged between 50.7 cM for chromosome 2R and 386.2 cM for chromosome 7B. A total of 512 (31.7%) bin markers showed significant (P < 0.05) segregation distortion across all chromosomes. The number of 8 the segregation distorted regions (SDRs) were identified on 1A, 7A, 1B, 2B, 7B (2 SDRs), 5R and 6R chromosomes. The high-density genetic map of triticale will facilitate fine mapping of quantitative trait loci, the identification of candidate genes and map-based cloning. PMID:26717308

  11. Improving the efficiency and accuracy of individual tree crown delineation from high-density LiDAR data

    NASA Astrophysics Data System (ADS)

    Hu, Baoxin; Li, Jili; Jing, Linhai; Judah, Aaron

    2014-02-01

    Canopy height model (CHM) derived from LiDAR (Light Detection And Ranging) data has been commonly used to generate segments of individual tree crowns for forest inventory and sustainable management. However, branches, tree crowns, and tree clusters usually have similar shapes and overlapping sizes, which cause current individual tree crown delineation methods to work less effectively on closed canopy, deciduous or mixedwood forests. In addition, the potential of 3-dimentional (3-D) LiDAR data is not fully realized by CHM-oriented methods. In this study, a framework was proposed to take advantage of the simplicity of a CHM-oriented method, detailed vertical structures of tree crowns represented in high-density LiDAR data, and any prior knowledge of tree crowns. The efficiency and accuracy of ITC delineation can be improved. This framework consists of five steps: (1) determination of dominant crown sizes; (2) generation of initial tree segments using a multi-scale segmentation method; (3) identification of “problematic” segments; (4) determination of the number of trees based on the 3-D LiDAR points in each of the identified segments; and (5) refinement of the “problematic” segments by splitting and merging operations. The proposed framework was efficient, since the detailed examination of 3-D LiDAR points was not applied to all initial segments, but only to those needed further evaluations based on prior knowledge. It was also demonstrated to be effective based on an experiment on natural forests in Ontario, Canada. The proposed framework and specific methods yielded crown maps having a good consistency with manual and visual interpretation. The automated method correctly delineated about 74% and 72% of the tree crowns in two plots with mixedwood and deciduous trees, respectively.

  12. A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

    NASA Technical Reports Server (NTRS)

    Jung, Jinha; Pasolli, Edoardo; Prasad, Saurabh; Tilton, James C.; Crawford, Melba M.

    2014-01-01

    Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

  13. 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

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

    PubMed

    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.

  15. Hospital benefit segmentation.

    PubMed

    Finn, D W; Lamb, C W

    1986-12-01

    Market segmentation is an important topic to both health care practitioners and researchers. The authors explore the relative importance that health care consumers attach to various benefits available in a major metropolitan area hospital. The purposes of the study are to test, and provide data to illustrate, the efficacy of one approach to hospital benefit segmentation analysis.

  16. [Music in the hospital].

    PubMed

    Bouteloup, Philippe

    2010-01-01

    Occasional events, regular workshops, concerts, shows, artists in residence, cultural outings...Hospital does not necessarily have to be a place of silence and sadness. But this situation has not always been so straightforward as on the face of it, nothing is more incompatible with a hospital environment than music, which, by definition, is festive and noisy. PMID:20684389

  17. Hospitality Occupations. Curriculum Guide.

    ERIC Educational Resources Information Center

    California State Dept. of Education, Sacramento. Bureau of Homemaking Education.

    This curriculum guide on the hospitality occupations was developed to help secondary and postsecondary home economics teachers prepare individuals for entry-level jobs in the hospitality industry. The content is in seven sections. The first section presents organizational charts of a medium-size hotel, food and beverage division, housekeeping and…

  18. Hospitality Services Reference Book.

    ERIC Educational Resources Information Center

    Texas Tech Univ., Lubbock. Home Economics Curriculum Center.

    This reference book provides information needed by employees in hospitality services occupations. It includes 29 chapters that cover the following topics: the hospitality services industry; professional ethics; organization and management structures; safety practices and emergency procedures; technology; property maintenance and repair; purchasing…

  19. Library Services in Hospitals.

    ERIC Educational Resources Information Center

    Department of Health and Social Security, London (England).

    The memorandum gives guidance to the provision and organization of library services at hospitals both for staff and for patients. It also draws attention to the assistance available from outside sources towards the development and maintenance of these services so hospital authorities may make the most effective use of the available facilities.…

  20. Hospitals are dangerous places.

    PubMed

    de Richemond, Albert L

    2010-01-01

    Hospital fire dangers are real, widespread, and ever present, the article demonstrates, spelling out the locations, conditions, and ignition potentials which exist in such a setting. Knowledge of codes and standards, good maintenance practices, and frequent drills in fire prevention and suppression are among the practices recommended for keeping a hospital fire from becoming a disaster, the author says. PMID:20873506

  1. Smaller hospitals accept advertising.

    PubMed

    Mackesy, R

    1988-07-01

    Administrators at small- and medium-sized hospitals gradually have accepted the role of marketing in their organizations, albeit at a much slower rate than larger institutions. This update of a 1983 survey tracks the increasing competitiveness, complexity and specialization of providing health care and of advertising a small hospital's services. PMID:10288550

  2. Hospitality services generate revenue.

    PubMed

    Bizouati, S

    1993-01-01

    An increasing number of hospitals are undertaking external revenue-generating activities to supplement their shrinking budgets. Written at the request of Leadership, this article outlines an example of a successful catering service -- a money-generating business that more Canadian hospitals could profitably consider.

  3. Hospitality Services. Curriculum Guide.

    ERIC Educational Resources Information Center

    Texas Tech Univ., Lubbock. Home Economics Curriculum Center.

    This guide, which was developed as part of Texas' home economics education program, is intended to assist teachers of a hospitality services course focusing on the food and lodging segments of the hospitality and tourism industry. The first 40% of the approximately 600-page guide consists of strategies for teaching each of 29 essential…

  4. Hospital 360°.

    PubMed

    Giraldo Valencia, Juan Carlos; Delgado, Liliana Claudia

    2015-01-01

    There are forces that are greater than the individual performance of each hospital institution and of the health system structural of each country. The world is changing and to face up to the future in the best possible way, we need to understand how contexts and emerging trends link up and how they affect the hospital sector. The Columbian Association of Hospitals and Clinics, ACHC, has thus come up with the Hospital 360° concept which uses hospitals capable of anticipating changing contexts by means of the transition between present and future and takes on board the experience of global, socio-economic, demographic, political, environmental and technological fields as its model. Hospital 360° is an invitation to reinvent processes and institution themselves allowing them to adapt and incorporate a high degree of functional flexibility. Hospital 360° purses goals of efficiency, effectiveness and relevance, but also of impact and sustainability, and is coherent with the internal needs of hospital institutions and society for long-term benefits. PMID:26521380

  5. Mental hospitals in India.

    PubMed

    Krishnamurthy, K; Venugopal, D; Alimchandani, A K

    2000-04-01

    This review traces the history of the mental hospital movement, initially on the world stage, and later in India, in relation to advances in psychiatric care. Mental hospitals have played a significant role in the evolution of psychiatry to its present statusThe earliest hospital in India were established during the British colonial rule. They served as a means to isolate mentally ill persons from the societal mainstream and provide treatments that were in vogue at the time. Following India's independence, there has been a trend towards establishing general hospital psychiatry units and deinstitutionalization, while at the same time improving conditions in the existing mental hospitals.Since 1947, a series of workshops of superintendents was conducted to review the prevailing situations in mental hospitals and to propose recommendations to improve the same. Implementation of the Mental Health Act, 1987, and grovernmental focus upon mental hospital reform have paved way for a more specific and futuristic role for mental hospitals in planning psychiatric services for the new millenium, especially for severe mental illnesses. PMID:21407925

  6. [Music in the hospital].

    PubMed

    Bouteloup, Philippe

    2010-01-01

    Occasional events, regular workshops, concerts, shows, artists in residence, cultural outings...Hospital does not necessarily have to be a place of silence and sadness. But this situation has not always been so straightforward as on the face of it, nothing is more incompatible with a hospital environment than music, which, by definition, is festive and noisy.

  7. Handbook on Hospital Television.

    ERIC Educational Resources Information Center

    Prynne, T. A.

    Designed for both hospital personnel interested in television and audiovisual personnel entering the medical field, this handbook is a verbal and pictorial survey of what is being done with TV within the medical profession. After an introduction which answers technical questions about medical TV posed during the American Hospital Association's…

  8. Designing sustainable acute hospitals.

    PubMed

    Cory, Alistair

    2008-01-01

    The need to provide sustainable hospitals lies in the fact that we have an obligation to act responsibly towards good stewardship of our environment and the world's precious resources, ensuring a healthy future for coming generations. As such, a sustainable hospital must sit squarely in a sustainable society, and the global and local context should be considered when designing a sustainable health facility.

  9. Hospitality services generate revenue.

    PubMed

    Bizouati, S

    1993-01-01

    An increasing number of hospitals are undertaking external revenue-generating activities to supplement their shrinking budgets. Written at the request of Leadership, this article outlines an example of a successful catering service -- a money-generating business that more Canadian hospitals could profitably consider. PMID:10127850

  10. [Hospital medicine in Chile].

    PubMed

    Eymin, Gonzalo; Jaffer, Amir K

    2013-03-01

    After 15 years of development of Hospital Medicine in Chile, there are several benefits of this discipline. Among others, a reduction in the length of hospital stay, readmissions, costs, and improved medical teaching of students, residents and fellows have been observed. However, in South América there are only isolated groups dedicated to Hospital Medicine in Chile, Argentina and Brazil, with a rather slow growth. The unjustified fear of competition from sub specialists, and the fee for service system of payment in our environment may be important factors to understand this phenomenon. The aging of the population makes imperative to improve the safety of our patients and to optimize processes and resources within the hospital, to avoid squandering healthcare resources. The following is a detailed and evidence-based article, on how hospital medicine might benefit both the public and prívate healthcare systems in Chile. PMID:23900327

  11. Damage Assessment for Disaster Relief Efforts in Urban Areas Using Optical Imagery and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Bahr, Thomas

    2014-05-01

    Imagery combined with LiDAR data and LiDAR-derived products provides a significant source of geospatial data which is of use in disaster mitigation planning. Feature rich building inventories can be constructed from tools with 3D rooftop extraction capabilities, and two dimensional outputs such as DSMs and DTMs can be used to generate layers to support routing efforts in Spatial Analyst and Network Analyst workflows. This allows us to leverage imagery and LiDAR tools for disaster mitigation or other scenarios. Software such as ENVI, ENVI LiDAR, and ArcGIS® Spatial and Network Analyst can therefore be used in conjunction to help emergency responders route ground teams in support of disaster relief efforts. This is exemplified by a case study against the background of the magnitude 7.0 earthquake that struck Haiti's capital city of Port-au-Prince on January 12, 2010. Soon after, both LiDAR data and an 8-band WorldView-2 scene were collected to map the disaster zone. The WorldView-2 scene was orthorectified and atmospherically corrected in ENVI prior to use. ENVI LiDAR was used to extract the DSM, DTM, buildings, and debris from the LiDAR data point cloud. These datasets provide a foundation for the 2D portion of the analysis. As the data was acquired over an area of dense urbanization, the majority of ground surfaces are roads, and standing buildings and debris are actually largely separable on the basis of elevation classes. To extract the road network of Port-au-Prince, the LiDAR-based feature height information was fused with the WorldView-2 scene, using ENVI's object-based feature extraction approach. This road network was converted to a network dataset for further analysis by the ArcGIS Network Analyst. For the specific case of Haiti, the distribution of blue tarps, used as accommodations for refugees, provided a spectrally distinct target. Pure blue tarp pixel spectra were selected from the WorldView-2 scene and input as a reference into ENVI's Spectral Angle

  12. 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

  13. Hospitality as an Environmental Metaphor.

    ERIC Educational Resources Information Center

    Horwood, Bert

    1991-01-01

    Compares stewardship and hospitality as they relate to the biosphere. Traces the origin of the word "hospitality," discusses cultural traditions of hospitality, and applies the concept of hospitality to the natural world. Considers forms of symbiosis in nature: commensals, mutualism, and parasitism. Hospitality promotes respect, humility, and…

  14. Uncertainty estimation in integrated LiDAR- and radar-derived biomass maps at key national-level map scales

    NASA Astrophysics Data System (ADS)

    Joshi, N.; Fensholt, R.; Saatchi, S. S.; Mitchard, E. T.

    2013-12-01

    The international Reducing Emissions from Deforestation and Degradation (REDD) program requires accurate and cost-effective techniques of national-level mapping of above-ground biomass (AGB) and ground-sampling strategies. This paper explores a multi-sensor (radar and low-density airborne LiDAR) integration approach for country-wide AGB estimation and mapping in Denmark, selected as a test-country due to the unique availability of country-wide remote sensing and forest inventory data. We assess the potential use of ALOS PALSAR L-band radar and ENVISAT ASAR C-band radar in prediction and mapping of AGB with accuracies similar to LiDAR-derived AGB estimates at different map scales. We start by creating a LiDAR-based ';ground truth' map, using LiDAR-derived 95th Percentile of heights >1 m weighted by the Canopy Density ratio, together with 113 AGB plots to map AGB at a 0.25 ha resolution across the country. A leave-20%-out cross-validation indicates that the AGB estimates have a mean absolute error of 41 Mg ha-1 and a negative mean bias error of 1.7 Mg ha-1. Though the LiDAR model appears to have an overall species-specific bias for conifers and broadleaf (-5.2 Mg ha-1 and +12.3 Mg ha-1 respectively), these are found to be insignificant (p>0.05) when accounting for species sampling bias and the under-prediction of plots containing high-biomass (> 350 Mg ha-1). Using the LiDAR-derived biomass map as a ';truth-map', biomass-backscatter relations will be quantified at three map scales (0.25 ha, 1 ha and 100 ha) and using three spatial sampling frameworks (full-dataset, stratified random sampling equally representing low and high biomass pixels, clustered sampling). The approach aims to derive a minimal-sampling and mapping strategy for L- and C-band radar that achieves at least 20% accuracy in AGB estimation, along with quantified sources of error from ground-AGB estimates, scaling and sampling. It is expected that mapping techniques, uncertainty quantification and

  15. Quantifying Soil Carbon Change from Wildfires in Peatland Ecosystems of the Eastern United States Using Repeat LiDAR

    NASA Astrophysics Data System (ADS)

    Reddy, A.; Hawbaker, T. J.; Zhu, Z.; Ward, S.; Wurster, F.; Newcomb, D.

    2013-12-01

    Wildfires are an increasing concern in peatland ecosystems along the coastal plains of the Eastern US. Human- and climate-induced changes to the ecosystems' hydrology can leave the soils, heavy with organic matter, susceptible to combustion in wildfires. This results in large losses of carbon that took many years to accumulate. However, accurately quantifying carbon losses in peatlands from wildfires is challenging because field data collection over extensive areas is difficult. For this study, our first objective was to evaluate the use of pre- and post-fire LiDAR data to quantify changes in surface elevations and soil carbon stocks for the 2011 Lateral West fire, which occurred in the Great Dismal Swamp National Wildlife Refuge (GDSNWR), Virginia, USA. Our second objective was to use a Monte Carlo approach to estimate how the vertical error in LiDAR points affected our calculation of soil carbon emissions. Bare-earth LiDAR points from 2010 and 2012 were obtained for GDSNWR with densities of 2 pulses/m2 and vertical elevation RMSE of 9 and 7 cm, respectively. Monte Carlo replicates were used to perturb individual bare-earth LiDAR points and generate probability distributions of elevation change within 10 m grid cells. Change in soil carbon were calculated within the Monte Carlo replicates by multiplying the LiDAR-derived volume of soil loss by depth-specific published values of soil bulk density, organic matter content, and carbon content. The 5th, 50th and 95th percentiles of the elevation and carbon change distributions were outputted as raster layers. Loss in soil volume ranged from 10,820,000 to 13,190,000 m3 based on vertical error. Carbon loss within the entire area burned by the Lateral West fire perimeter (32.1 km2), based on the 5th, 50th and 95th percentiles was 0.64, 0.96, and 1.33 Tg C, respectively. Our study demonstrated a method to use LiDAR data to quantify carbon loss following fires in peatland ecosystems and incorporate elevation errors to

  16. Effects of the D1 Dopamine Receptor Agonist Dihydrexidine (DAR-0100A) on Working Memory in Schizotypal Personality Disorder

    PubMed Central

    Rosell, Daniel R; Zaluda, Lauren C; McClure, Margaret M; Perez-Rodriguez, M Mercedes; Strike, K Sloan; Barch, Deanna M; Harvey, Philip D; Girgis, Ragy R; Hazlett, Erin A; Mailman, Richard B; Abi-Dargham, Anissa; Lieberman, Jeffrey A; Siever, Larry J

    2015-01-01

    Pharmacological enhancement of prefrontal D1 dopamine receptor function remains a promising therapeutic approach to ameliorate schizophrenia-spectrum working memory deficits, but has yet to be rigorously evaluated clinically. This proof-of-principle study sought to determine whether the active enantiomer of the selective and full D1 receptor agonist dihydrexidine (DAR-0100A) could attenuate working memory impairments in unmedicated patients with schizotypal personality disorder (SPD). We performed a randomized, double-blind, placebo-controlled trial of DAR-0100A (15 mg/150 ml of normal saline administered intravenously over 30 min) in medication-free patients with SPD (n=16) who met the criteria for cognitive impairment (ie, scoring below the 25th percentile on tests of working memory). We employed two measures of verbal working memory that are salient to schizophrenia-spectrum cognitive deficits, and that clinical data implicate as being associated with prefrontal D1 availability: (1) the Paced Auditory Serial Addition Test (PASAT); and (2) the N-back test (ratio of 2-back:0-back scores). Study procedures occurred over four consecutive days, with working memory testing on Days 1 and 4, and DAR-0100A/placebo administration on Days 2–4. Treatment with DAR-0100A was associated with significantly improved PASAT performance relative to placebo, with a very large effect size (Cohen's d=1.14). Performance on the N-back ratio was also significantly improved; however, this effect rested on both a non-significant enhancement and diminution of 2-back and 0-back performance, respectively; therefore interpretation of this finding is more complicated. DAR-0100A was generally well tolerated, with no serious medical or psychiatric adverse events; common side effects were mild to moderate and transient, consisting mainly of sedation, lightheadedness, tachycardia, and hypotension; however, we were able to minimize these effects, without altering the dose, with supportive

  17. Effects of the D1 dopamine receptor agonist dihydrexidine (DAR-0100A) on working memory in schizotypal personality disorder.

    PubMed

    Rosell, Daniel R; Zaluda, Lauren C; McClure, Margaret M; Perez-Rodriguez, M Mercedes; Strike, K Sloan; Barch, Deanna M; Harvey, Philip D; Girgis, Ragy R; Hazlett, Erin A; Mailman, Richard B; Abi-Dargham, Anissa; Lieberman, Jeffrey A; Siever, Larry J

    2015-01-01

    Pharmacological enhancement of prefrontal D1 dopamine receptor function remains a promising therapeutic approach to ameliorate schizophrenia-spectrum working memory deficits, but has yet to be rigorously evaluated clinically. This proof-of-principle study sought to determine whether the active enantiomer of the selective and full D1 receptor agonist dihydrexidine (DAR-0100A) could attenuate working memory impairments in unmedicated patients with schizotypal personality disorder (SPD). We performed a randomized, double-blind, placebo-controlled trial of DAR-0100A (15 mg/150 ml of normal saline administered intravenously over 30 min) in medication-free patients with SPD (n=16) who met the criteria for cognitive impairment (ie, scoring below the 25th percentile on tests of working memory). We employed two measures of verbal working memory that are salient to schizophrenia-spectrum cognitive deficits, and that clinical data implicate as being associated with prefrontal D1 availability: (1) the Paced Auditory Serial Addition Test (PASAT); and (2) the N-back test (ratio of 2-back:0-back scores). Study procedures occurred over four consecutive days, with working memory testing on Days 1 and 4, and DAR-0100A/placebo administration on Days 2-4. Treatment with DAR-0100A was associated with significantly improved PASAT performance relative to placebo, with a very large effect size (Cohen's d=1.14). Performance on the N-back ratio was also significantly improved; however, this effect rested on both a non-significant enhancement and diminution of 2-back and 0-back performance, respectively; therefore interpretation of this finding is more complicated. DAR-0100A was generally well tolerated, with no serious medical or psychiatric adverse events; common side effects were mild to moderate and transient, consisting mainly of sedation, lightheadedness, tachycardia, and hypotension; however, we were able to minimize these effects, without altering the dose, with supportive

  18. 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

  19. Hospital diversification: evaluating alternatives.

    PubMed

    Hammer, L

    1987-05-01

    The appropriateness of diversification as a growth strategy for hospitals is discussed, and planning for diversification is described. Because new forms of health-care delivery are now in direct competition with hospitals, many hospitals are confronting environmental pressures and preparing for future survival through diversification. To explore the potential risks and benefits of diversification, the hospital must identify opportunities for new business ventures. Diversification can be "related," through an expansion of the primary product line (health care), or "unrelated," into areas not directly associated with health care. The hospital must establish specific criteria for evaluating each diversification alternative, and the two or three most attractive options should be analyzed further through a financial feasibility study. The hospital should also seek legal advice to determine the implications of diversification for maintenance of tax status, antitrust limitations, and applicability of certificate of need. Although diversification may not be appropriate for every institution, hospitals should consider it as a strategy for increasing their revenue base, confronting environmental pressures, and securing future survival. PMID:3300300

  20. Philanthropy and hospital financing.

    PubMed Central

    Smith, D G; Clement, J P; Wheeler, J R

    1995-01-01

    OBJECTIVE. This study explores the relationships among donations to not-for-profit hospitals, the returns provided by these hospitals, and fund-raising efforts. It tests a model of hospital behavior and addresses an earlier debate regarding the supply price of donations. DATA SOURCES. The main data source is the California Office of Statewide Health Planning data tapes of hospital financial disclosure reports for fiscal years 1980/1981 through 1986/1987. Complete data were available for 160 hospitals. STUDY DESIGN. Three structural equations (donations, returns, and fund-raising) are estimated as a system using a fixed-effects, pooled cross-section, time-series least squares regression. PRINCIPAL FINDINGS. Estimation results reveal the expected positive relation between donations and returns. The reverse relation between returns and donations is insignificant. The estimated effect of fund-raising on donations is insignificantly different from zero, and the effect of donations on fund-raising is negative. Fund-raising and returns are negatively associated with one another. CONCLUSION. The empirical results presented here suggest a positive donations-returns relations and are consistent with a positive supply price for donations. Hospitals appear to view a trade-off between providing returns and soliciting donations, but donors do not respond equally to these two activities. Attempts to increase free cash flow through expansion of community returns or fund-raising activity, at least in the short run, are not likely to be highly successful financing strategies for many hospitals. PMID:8537223

  1. Hospitals' Internal Accountability

    PubMed Central

    Kraetschmer, Nancy; Jass, Janak; Woodman, Cheryl; Koo, Irene; Kromm, Seija K.; Deber, Raisa B.

    2014-01-01

    This study aimed to enhance understanding of the dimensions of accountability captured and not captured in acute care hospitals in Ontario, Canada. Based on an Ontario-wide survey and follow-up interviews with three acute care hospitals in the Greater Toronto Area, we found that the two dominant dimensions of hospital accountability being reported are financial and quality performance. These two dimensions drove both internal and external reporting. Hospitals' internal reports typically included performance measures that were required or mandated in external reports. Although respondents saw reporting as a valuable mechanism for hospitals and the health system to monitor and track progress against desired outcomes, multiple challenges with current reporting requirements were communicated, including the following: 58% of survey respondents indicated that performance-reporting resources were insufficient; manual data capture and performance reporting were prevalent, with the majority of hospitals lacking sophisticated tools or technology to effectively capture, analyze and report performance data; hospitals tended to focus on those processes and outcomes with high measurability; and 53% of respondents indicated that valuable cross-system accountability, performance measures or both were not captured by current reporting requirements. PMID:25305387

  2. Hospital diversification: evaluating alternatives.

    PubMed

    Hammer, L

    1987-05-01

    The appropriateness of diversification as a growth strategy for hospitals is discussed, and planning for diversification is described. Because new forms of health-care delivery are now in direct competition with hospitals, many hospitals are confronting environmental pressures and preparing for future survival through diversification. To explore the potential risks and benefits of diversification, the hospital must identify opportunities for new business ventures. Diversification can be "related," through an expansion of the primary product line (health care), or "unrelated," into areas not directly associated with health care. The hospital must establish specific criteria for evaluating each diversification alternative, and the two or three most attractive options should be analyzed further through a financial feasibility study. The hospital should also seek legal advice to determine the implications of diversification for maintenance of tax status, antitrust limitations, and applicability of certificate of need. Although diversification may not be appropriate for every institution, hospitals should consider it as a strategy for increasing their revenue base, confronting environmental pressures, and securing future survival.

  3. Hospitals' internal accountability.

    PubMed

    Kraetschmer, Nancy; Jass, Janak; Woodman, Cheryl; Koo, Irene; Kromm, Seija K; Deber, Raisa B

    2014-09-01

    This study aimed to enhance understanding of the dimensions of accountability captured and not captured in acute care hospitals in Ontario, Canada. Based on an Ontario-wide survey and follow-up interviews with three acute care hospitals in the Greater Toronto Area, we found that the two dominant dimensions of hospital accountability being reported are financial and quality performance. These two dimensions drove both internal and external reporting. Hospitals' internal reports typically included performance measures that were required or mandated in external reports. Although respondents saw reporting as a valuable mechanism for hospitals and the health system to monitor and track progress against desired outcomes, multiple challenges with current reporting requirements were communicated, including the following: 58% of survey respondents indicated that performance-reporting resources were insufficient; manual data capture and performance reporting were prevalent, with the majority of hospitals lacking sophisticated tools or technology to effectively capture, analyze and report performance data; hospitals tended to focus on those processes and outcomes with high measurability; and 53% of respondents indicated that valuable cross-system accountability, performance measures or both were not captured by current reporting requirements. PMID:25305387

  4. How Well Can We Predict Salmonid Spawning Habitat with LiDAR?

    NASA Astrophysics Data System (ADS)

    Pfeiffer, A.; Finnegan, N. J.; Hayes, S.

    2013-12-01

    Suitable salmonid spawning habitat is, to a great extent, determined by physical, landscape driven characteristics such as channel morphology and grain size. Identifying reaches with high-quality spawning habitat is essential to restoration efforts in areas where salmonid species are endangered or threatened. While both predictions of suitable habitat and observations of utilized habitat are common in the literature, they are rarely combined. Here we exploit a unique combination of high-resolution LiDAR data and seven years of 387 individually surveyed Coho and Steelhead redds in Scott Creek, a 77 km2 un-glaciated coastal California drainage in the Santa Cruz Mountains, to both make and test predictions of spawning habitat. Using a threshold channel assumption, we predict grain size throughout Scott Creek via a shear stress model that incorporates channel width, instead of height, using Manning's equation (Snyder et al., 2013). Slope and drainage area are computed from a LiDAR-derived DEM, and channel width is calculated via hydraulic modeling. Our results for median grain size predictions closely match median grain sizes (D50) measured in the field, with the majority of sites having predicted D50's within a factor of two of the observed values, especially for reaches with D50 > 0.02m. This success suggests that the threshold model used to predict grain size is appropriate for un-glaciated alluvial channel systems. However, it appears that grain size alone is not a strong predictor of salmon spawning. Reaches with a high (>0.1m) average predicted D50 do have lower redd densities, as expected based on spawning gravel sizes in the literature. However, reaches with lower (<0.1m) predicted D50 have a wide range of redd densities, suggesting that reach-average grain size alone cannot explain spawning site selection in the finer-grained reaches of Scott Creek. We turn to analysis of bedform morphology in order to explain the variation in redd density in the low

  5. Financial sustainability in municipal solid waste management – Costs and revenues in Bahir Dar, Ethiopia

    SciTech Connect

    Lohri, Christian Riuji Camenzind, Ephraim Joseph Zurbrügg, Christian

    2014-02-15

    Highlights: • Cost-revenue analysis over 2 years revealed insufficient cost-recovery. • Expenses for motorized secondary collection increased by 82% over two years. • Low fee collection rate and reliance on only one revenue stream are problematic. • Different options for cost reduction and enhanced revenue streams are recommended. • Good public–private alliance is crucial to plan and implement improvement measures. - Abstract: Providing good solid waste management (SWM) services while also ensuring financial sustainability of the system continues to be a major challenge in cities of developing countries. Bahir Dar in northwestern Ethiopia outsourced municipal waste services to a private waste company in 2008. While this institutional change has led to substantial improvement in the cleanliness of the city, its financial sustainability remains unclear. Is the private company able to generate sufficient revenues from their activities to offset the costs and generate some profit? This paper presents a cost-revenue analysis, based on data from July 2009 to June 2011. The analysis reveals that overall costs in Bahir Dar’s SWM system increased significantly during this period, mainly due to rising costs related to waste transportation. On the other hand, there is only one major revenue stream in place: the waste collection fee from households, commercial enterprises and institutions. As the efficiency of fee collection from households is only around 50%, the total amount of revenues are not sufficient to cover the running costs. This results in a substantial yearly deficit. The results of the research therefore show that a more detailed cost structure and cost-revenue analysis of this waste management service is important with appropriate measures, either by the privates sector itself or with the support of the local authorities, in order to enhance cost efficiency and balance the cost-revenues towards cost recovery. Delays in mitigating the evident

  6. Hospitalized Patients and Fungal Infections

    MedlinePlus

    ... but can also be caused by fungi. Hospital construction. Hospital staff do everything they can to prevent ... patients staying at hospitals where there is ongoing construction or renovation. 5 This is thought to be ...

  7. Geomorphic mapping of the southern Maacama fault based on LiDAR data

    NASA Astrophysics Data System (ADS)

    Hoeft, J. S.; Sowers, J. M.; Kelsey, H. M.; Prentice, C. S.; Frankel, K. L.

    2008-12-01

    The Maacama fault is an active strike slip fault, and a potentially significant seismic source, within the San Andreas transform system. The fault is located east of and parallel to the San Andreas fault in Sonoma and Mendocino counties, California and is divided into a northern and southern section based on a NW to NNW change in strike. The southern segment comprises 54 km of the fault's 144 km total length and is primarily located in an upland area traversing mountainous terrain. Strain is thought to transfer northward from the East Bay fault zone along the Rodgers Creek fault and, through a right step, to the Maacama fault. LiDAR data collected in a 1-km-wide swath along the southern Maacama fault, as part of the GeoEarthscope project, were used to produce a bare-earth digital elevation model, from which hillshade, topographic contour, slope, and curvature maps with 0.5- to 1-m-resolution were derived. Mapping was primarily conducted digitally in a GIS environment, and interpretation of LiDAR data was supplemented with aerial photograph interpretation and field inspection. Primary, Holocene-age fault-related geomorphic features, consisting of scarps and dextrally offset drainages, define the southern Maacama. These features are sparsely distributed and comprise less than 20% of the fault length. The fault scarps define a sequence of left-stepping, en echelon fault segments with an average segment length of 230 m. By contrast, the northern Maacama fault is better defined geomorphically. The poor expression of the southern Maacama is likely due to the presence of active hillslope processes and low levels of seismicity. Seismicity along the southern segment is lower than that of the northern segment. The Coast Range uplands, primarily composed of Franciscan Complex, is characterized by numerous landslides and experiences annual precipitation of 75 to 180 cm. There is approximately 30 km of overlap between the northern end of the Rodgers Creek fault and the southern

  8. Ecological Characterization Of An Intact Tropical Peat Forest Using Airborne Small Footprint LiDAR

    NASA Astrophysics Data System (ADS)

    Nguyen, H. T.; Hutyra, L.; Raciti, S. M.; Hardiman, B. S.

    2014-12-01

    Tropical peat forests in Southeast Asia have been experiencing climatic and anthropogenic disturbances in the form of drought, fire, deforestation and drainage at an increasing pace and with an increasing extent throughout the past two decades. In this project we aim to improve our understanding of the structural dynamics of tropical peat swamps and the effect of deforestation on the forest structure by (i) characterizing the forest structural parameters (stem density, stem height, crown area, crown roughness, gap size and frequency) of an intact peat dome and (ii) comparing with those from a nearby deforested peat dome. Both are located in Northwestern Borneo. We combine field sampling of 0.8 hectare of forest in 2014 and 84km2 of airborne, small footprint, discrete returns LiDAR acquired in 2010 to extract the parameters of interest. We first process LiDAR data to produce to a Digital Elevation Model (DEM) and a Canopy Height Model (CHM) of the area. Individual canopy stems are extracted through local maxima filtering with varying size and shape of search windows. Canopy crowns are segmented from the CHM via K-means clustering using stem positions as fixed cluster centroids. Canopy crown height and stem density are calibrated with field survey in order to upscale stem density to the whole peat dome. Crown roughness is defined as standard deviation of each cluster (crown). Finally, gaps were delineated from the CHM with 30m as vertical threshold and 40m2 as minimum area. The entire procedure is then repeated for the deforested peat dome. Across the intact peat dome, we find an increase in stem density but a decrease in canopy stem height, canopy crown area and canopy crown roughness as a function of a 5m elevational change. Gap size frequency follows a Gamma distribution with higher variance in gap percentage for areas closer to the dome center. As a function of canopy stem height, aboveground biomass decreases towards the dome center. For the deforested peat dome

  9. Mapping Forest Carbon by Fusing Terrestrial and Airborne LiDAR Datasets

    NASA Astrophysics Data System (ADS)

    Stovall, A. E.

    2015-12-01

    The storage and flux of terrestrial carbon (C) is one of the largest and most uncertain components of the global C budget, the vast majority of which is held within the biomass of the world's forests. However, the spatial distribution and quantification of forest C remains difficult to measure on a large scale. Remote sensing of forests with airborne LiDAR has proven to be an extremely effective method of bridging the gap between data from plot-level forestry mensuration and landscape-scale C storage estimates, but the standard method of assessing forest C is typically based on national or regional-scale allometric equations that are often not representative on the local-scale. Improvement of these measurements is necessary in order for collaborative multi-national carbon monitoring programs such as REDD implemented by the UNFCCC to be successful in areas, such as tropical forests, with tree species that have insufficiently documented allometric relationships. The primary goal of this study is to set forth a pipeline for precise non-destructive monitoring of C storage by: 1) determining C storage on 15 1/10th ha plots in a 25.6 ha Virginia temperate forest using the recently updated national allometric equations from Chojnacky et. al 2014, 2) comparing these estimates to non-destructively determined individual tree biomass using several semi-automated approaches of three-dimensionally analyzing the point cloud from a high-precision Terrestrial Laser Scanner (TLS), and 3) creating a predictive model of forest C storage by fusing airborne LiDAR data to the plot-level TLS measurements. Our findings align with several other studies, indicating a strong relationship between allometrically-derived C estimates and TLS-derived C measurements (R2=0.93, n=30) using relatively few individuals, suggesting the potential application of these methods to species that are understudied or are without allometric relationships. Voxel based C storage was estimated on the plot level and

  10. Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval

    NASA Astrophysics Data System (ADS)

    Chen, Yi-Chen; Lin, Chao-Hung

    2016-06-01

    With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority

  11. Sediment Yields Revealed and Fluid Modelling by Twice LiDAR Surveys in Active Tectonics Area

    NASA Astrophysics Data System (ADS)

    Hsieh, Y.; Chan, Y.; Hu, J.; Lin, C.

    2010-12-01

    LiDAR technique allows rapid acquisition of high resolution and high precision topographic data. The technique has found considerable use in the earth sciences, for example for fluvial morphology and flood modelling. These developments have offered new opportunities for investigating spatial and temporal patterns of morphological change in gravel-bed river and have contributed to develop in two points: (1)morphometric estimates of sediment transport and sediment yields ;(2)boundary conditions for numerical models, including computational fluid dynamics and modelling. This topographic research funded by the Taiwan Central Geological Survey, surveyed the terrain of the Lanyang River before and after the typhoon season using Airborne LiDAR technique, and computed the terrain variations. The Lanyang River is one of main rivers in Taiwan and often suffers the influence of typhoon during summer. Most of sediments generated from slump and soil erosion into river were transported from the upstream watershed and resulted in the riverbed changes during the typhoon season. In 2008, there are four significant typhoon events influencing this area, including the Kalmaegi, Fung-wong, Sinlaku, and Jangmi typhoons. At present, sediment yield calculation often used empirical or theoretical formula as well as data collected at hydrological stations, and rarely had the actual measured value through high-resolution topography. The variations of the terrain on the riverbed may be regarded as the sediment yield of the bed load transported during the typhoon season. This research used high-resolution terrain models to compute sediment yield of the bed load, and further discussed volumes of sediment yield in watershed during the typhoon season. In the Lanyang River we discovered that the upstream and midstream channel still had the characteristics of erosion and transportation during the typhoon season. The results imply significant sediment yield and transportation from the upstream

  12. LiDAR-based characterization of the Mt Shasta debris avalanche deposit

    NASA Astrophysics Data System (ADS)

    Tortini, R.; Carn, S. A.; van Wyk de Vries, B.

    2013-12-01

    The failure of destabilized volcano flanks, due either to tectonic activity on basement structures underlying the volcanic edifice, magmatic intrusion or external forcing (e.g. weather events), is a likely occurrence during the lifetime of a stratovolcano. Flank failure can generate large debris avalanches, and the significant hazards associated with volcanic debris avalanches in the Cascade range were demonstrated by the collapse of Mt St Helens (WA, USA), which triggered its devastating explosive eruption in May 1980. Mt Shasta is a 4,317 m high, snow-capped, steep-sloped stratovolcano located in Northern California. The most voluminous of the Cascade volcanoes, the current edifice began forming on the remnants of an ancestral Mt Shasta that collapsed approximately 300,000 to 380,000 years ago producing one of the largest debris avalanches known on Earth. The debris avalanche deposit (DAD) covers a surface of 450 km2 across the Shasta valley, for a total volume of approximately 26 km3. A LiDAR point cloud and orthophoto of the Shasta DAD surveyed by the NCALM consortium provides a new topographic dataset of the area with unprecedented resolution. This will permit the identification of subtle topographic features of the Shasta DAD not apparent in the field or in coarser resolution datasets. Statistical measures of the LiDAR-derived digital elevation model, such as surface texture, will be used to detect and characterize the hummock topography, differentiate between various DAD facies and geomorphic units, and extract the morphological parameters for subsequent analogue and numerical modeling of the debris avalanche. This work aims to improve our understanding of the Mt Shasta DAD morphology and its dynamics, and provide insight into the cause, timing of events and mode of emplacement of the DAD. The Cascade range includes numerous large extinct, dormant or active stratovolcanoes, and knowledge of the link between basement structures and the Mt Shasta DAD will

  13. 2011 Japan tsunami current and flow velocity measurements from survivor videos using LiDAR

    NASA Astrophysics Data System (ADS)

    Fritz, H. M.; Phillips, D. A.; Okayasu, A.; Shimozono, T.; Liu, H.; Mohammed, F.; Skanavis, V.; Synolakis, C.; Takahashi, T.

    2011-12-01

    On March 11, 2011, a magnitude Mw 9.0 earthquake occurred off the coast of Japan's Tohoku region causing catastrophic damage and loss of life. Numerous tsunami reconnaissance trips were conducted in Japan (Tohoku Earthquake and Tsunami Joint Survey Group). This report focuses on the surveys at 9 tsunami eyewitness video recording locations in Yoriisohama, Kesennuma, Kamaishi and Miyako along Japan's Sanriku coast and the subsequent video image calibration, processing and tsunami flow velocity analysis. Selected tsunami video recording sites were visited, eyewitnesses interviewed and some ground control points recorded during the initial tsunami reconnaissance from April 9 to 25. A follow-up survey from June 9 to 15, 2011 focused on terrestrial laser scanning (TLS) at locations with previously identified high quality eyewitness videos. We acquired precise topographic data using TLS at nine video sites with multiple scans acquired from different instrument positions at each site. These ground-based LiDAR measurements produce a 3-dimensional "point cloud" dataset. Digital photography from a scanner-mounted camera yields photorealistic 3D images. Integrated GPS measurements allow accurate georeferencing of the TLS data in an absolute reference frame such as WGS84. We deployed a Riegl VZ-400 scanner (1550 nm wavelength laser, 42,000 measurements/second, <600 meter max range) and peripheral equipment from the UNAVCO instrument pool. The original full length videos recordings were recovered from eyewitnesses and the Japanese Coast Guard (JCG). Multiple videos were synchronized and referenced in time (UTC). The analysis of the tsunami videos follows a four step procedure developed for the analysis of 2004 Indian Ocean tsunami videos at Banda Aceh, Indonesia (Fritz et al., 2006). The first step requires the calibration of the sector of view present in the eyewitness video recording based on visually identifiable ground control points measured in the LiDAR point cloud data

  14. 2011 Japan tsunami survivor video based hydrograph and flow velocity measurements using LiDAR

    NASA Astrophysics Data System (ADS)

    Fritz, H. M.; Phillips, D. A.; Okayasu, A.; Shimozono, T.; Liu, H.; Mohammed, F.; Skanavis, V.; Synolakis, C. E.; Takahashi, T.

    2012-04-01

    On March 11, 2011, a magnitude Mw 9.0 earthquake occurred off the coast of Japan's Tohoku region causing catastrophic damage and loss of life. Numerous tsunami reconnaissance trips were conducted in Japan (Tohoku Earthquake and Tsunami Joint Survey Group). This report focuses on the surveys at 9 tsunami eyewitness video recording locations in Yoriisohama, Kesennuma, Kamaishi and Miyako along Japan's Sanriku coast and the subsequent video image calibration, processing, tsunami hydrograph and flow velocity analysis. Selected tsunami video recording sites were visited, eyewitnesses interviewed and some ground control points recorded during the initial tsunami reconnaissance from April 9 to 25. A follow-up survey from June 9 to 15, 2011 focused on terrestrial laser scanning (TLS) at locations with previously identified high quality eyewitness videos. We acquired precise topographic data using TLS at nine video sites with multiple scans acquired from different instrument positions at each site. These ground-based LiDAR measurements produce a 3-dimensional "point cloud" dataset. Digital photography from a scanner-mounted camera yields photorealistic 3D images. Integrated GPS measurements allow accurate georeferencing of the TLS data in an absolute reference frame such as WGS84. We deployed a Riegl VZ-400 scanner (1550 nm wavelength laser, 42,000 measurements/second, <600 meter max range) and peripheral equipment from the UNAVCO instrument pool. The original full length videos recordings were recovered from eyewitnesses and the Japanese Coast Guard (JCG). Multiple videos were synchronized and referenced in time (UTC). The analysis of the tsunami videos follows a four step procedure developed for the analysis of 2004 Indian Ocean tsunami videos at Banda Aceh, Indonesia (Fritz et al., 2006). The first step requires the calibration of the sector of view present in the eyewitness video recording based on visually identifiable ground control points measured in the LiDAR point

  15. Simultaneous Multiple Footprint and Multiple Field of View LiDAR for Submerged Topographic Mapping (Invited)

    NASA Astrophysics Data System (ADS)

    Wright, C. W.

    2013-12-01

    Charles Wayne Wright USGS, Coastal and Marine Science Center St. Petersburg, Fla. The Experimental Advanced Research LiDAR[a] (EAARL) has been designed to map sub aerial and submerged topography in and near shallow water environments. The system optically divides each 532 nanometer, 700 picosecond 420 uJ laser pulse into three distinct and divergent 133 uJ pulsed 1 milliradian beamlets which travel to the surface environment where they illuminate three distinct surface spots approximately 30cm in diameter and 1.3 meters apart from a nominal flight altitude of 300 meters. The system incorporates three spatially separated logarithmic response photomultiplier tube detectors coaligned with each of the 133 uJ laser beamlets. Each of the 133 uJ detectors views a 2 milliradian (2mr) field-of-view enabling fine scale near beam-C like time resolved backscattered waveforms. These three 2mr waveforms provide independent fine scale elevation measurement and water column discrimination over the range to zero to approximately 5 meters of water depth. The 2mr channels provide good surface reflection to bottom reflection resolution even over the very short time intervals associated with shallow water on the order of 50 cm water depth. Below 50cm of depth, the resulting pulse from the convolved surface, water column, and bottom reflection provide a means to measure depths between zero and 50 cm. The 2mr channel signals are susceptible to even very small amounts of suspended sediment in the water column. This characteristic seriously limits the useful measured depth from the 2mr channels. This sensor instrument incorporates a fourth 18mr wide detector channel to reduce susceptibility to suspended sediment, beam spreading due to irregular surface refraction and greatly extend the depth measuring capability of the instrument. The 18mr field-ofview (FOV) is configured to only detect laser light which is scattered outside the central 2mr FOV regions. The 2mr and the 18mr detectors

  16. LiDAR altimetry and hyperspectral imaging: New technologies for geological and mineralogical mapping

    NASA Astrophysics Data System (ADS)

    Wallace, Juliet Ann

    This thesis comprises several studies which use the relatively recently available commercial technologies of airborne LiDAR altimetry and hyperspectral imaging to investigate methods of lithological and mineralogical mapping. The study area covers approximately 3Q km2 near the City of Sudbury, Ontario, Canada. At the extreme northeast and southwest corners of this area are the Frood-Stobie mine and the Murray Mine respectively. Frood-Stobie is an active mine with current underground extraction of nickel ore. The Murray Mine, which was also worked for its nickel content, is now decommissioned. Both sites include waste rock piles which accommodate material extracted from nearby open pits. A digital elevation model was created from LiDAR altimetry data and used for lithological studies. Discriminating lithology from elevation relies on recognizing lithological signatures inherent in the topography. Lithological studies are confined to the relatively undisturbed areas between the mines. Quantitative differences between lithologies in the study area have been established on the basis of morphometric and fractal analyses. Three geological units present in the study area exhibit topographic signatures which are sufficiently distinct and are discriminated by the morphometric measures of slope and curvatures. The unit most resistant to erosion, the granitic Murray Pluton, exhibits the steepest slopes and curvatures while the other two units, a norite and a gabbro, which are more erodable, have lower slopes and curvatures. In addition, fractal analysis, which characterizes the 'roughness' of the landscape, distinguishes between the units with the measure of fractal dimension (D). These analyses have recognized differences in the values of D as well as identified anisotropy in the landscape resulting from the different lithologies. On a more detailed scale of mapping, one study has identified a northeast-southwest trend of topographic ridgelines. This correlates with a

  17. Stabilization of the photogrammetric system for a gyrocopter in terms of the LiDAR data quality. (Polish Title: Stabilizacja systemu pomiarowego dla wiatrakowca w aspekcie jakości danych LiDAR)

    NASA Astrophysics Data System (ADS)

    Kolecki, J.; Prochaska, M.; Piątek, P.; Baranowski, J.; Kurczyński, Z.

    2015-12-01

    The definition of the quality parameters of a point cloud acquired using the airborne laser scanning is the element of almost every terms of reference involving airborne spatial data acquisition. The quality of the LiDAR data should not be identified only with accuracy and should be examined in a wider aspect taking into account other parameters of the point cloud that was acquired as a result of a flight. For instance the Polish legal regulations provide the requirements concerning the coverage of the strips and the point density. The above mentioned parameters of the LiDAR data can be influenced to some extent by many factors concerning the flight itself such as a varying speed as well as the horizontal and vertical deflections from the planned flight line. However, vibrations and angular deflections seem to influence the point cloud quality to the highest extent. LiDAR data acquisition without required stabilizing system makes keeping the required quality parameters very hard. Within the research project which aimed to develop the prototype of the ultralight, stabilized mapping platform for the gyrocopter, a number of analyses concerning the optimal stabilization scenario were carried out. Tools including scripts and computer programs for analyzing the impact of the deflections on the data quality have been developed. The proper stabilization variant has been established taking into account three separate deflection components, i.e.: roll, pitch and yaw.

  18. A quasi-rigorous model based on improved ICP algorithm in the application of auto-calibration of airborne LiDAR system

    NASA Astrophysics Data System (ADS)

    Li, Lelin; Jiang, San

    2015-12-01

    The purpose of the airborne LiDAR system calibration is to eliminate the influence of system error and improve the precision of the original point cloud data. In certain hypothesis of flight conditions, the directly positioning model for LiDAR can be reduced to a quasi-rigorous model, and the dependence on the original observation data for the system calibration model is reduced too. In view of the shortcoming of human interaction way to establish corresponding relationship between strips, an improved ICP method which considering the object features in point clouds is proposed to get the transform relationship between strips, and the automatic calibration procedures of LiDAR system is established in this paper. Taking with the real LiDAR data in Baotou test field, experiment results show that the proposed system calibration procedures can greatly eliminate the influence of system error.

  19. What is the effect of LiDAR-derived DEM resolution on large-scale watershed model results?

    SciTech Connect

    Ping Yang; Daniel B. Ames; Andre Fonseca; Danny Anderson; Rupesh Shrestha; Nancy F. Glenn; Yang Cao

    2014-08-01

    This paper examines the effect of raster cell size on hydrographic feature extraction and hydrological modeling using LiDAR derived DEMs. LiDAR datasets for three experimental watersheds were converted to DEMs at various cell sizes. Watershed boundaries and stream networks were delineated from each DEM and were compared to reference data. Hydrological simulations were conducted and the outputs were compared. Smaller cell size DEMs consistently resulted in less difference between DEM-delineated features and reference data. However, minor differences been found between streamflow simulations resulted for a lumped watershed model run at daily simulations aggregated at an annual average. These findings indicate that while higher resolution DEM grids may result in more accurate representation of terrain characteristics, such variations do not necessarily improve watershed scale simulation modeling. Hence the additional expense of generating high resolution DEM's for the purpose of watershed modeling at daily or longer time steps may not be warranted.

  20. Quantification, analysis and modelling of soil erosion on steep slopes using LiDAR and UAV photographs

    NASA Astrophysics Data System (ADS)

    Neugirg, F.; Kaiser, A.; Schmidt, J.; Becht, M.; Haas, F.

    2015-03-01

    Steep hill slopes in the Bavarian Alps and at an artificial waste dump on the Island of Elba are subject to soil erosion through geomorphological processes. Long-term high-resolution terrestrial LiDAR data are available and have been analysed for both areas. The analysis indicated different erosion patterns on the slopes that could be the result of different geomorphological processes. Additionally, both study sites show a good agreement between the annual erosion rates and the size of the hydrological catchment as a proxy for the sediment contributing area. The results presented in this study represent the first analysis of hill slope erosion measured with LiDAR and UAV systems. The hill slope erosion will be subject to measurements using a higher temporal resolution during future years in order to identify different erosion processes throughout the annual time step.

  1. A high intensity H2 + multicusp ion source for the isotope decay-at-rest experiment, IsoDAR

    NASA Astrophysics Data System (ADS)

    Axani, S.; Winklehner, D.; Alonso, J.; Conrad, J. M.

    2016-02-01

    The Isotope Decay-At-Rest (IsoDAR) experimental program aims to decisively test the sterile neutrino hypothesis. In essence, it is a novel cyclotron based neutrino factory that will improve the frontiers in both high-intensity cyclotrons and electron flavor anti-neutrino sources. By using a source in which the usual H- ions are replaced with the more tightly bound H2 + ions, we can negate the effects of Lorentz stripping in a cyclotron, reduce the overall perveance due to the space-charge effect, and deliver twice the number of protons per nuclei on target. To produce the H2 + , we are currently developing a dedicated multicusp ion source, MIST-1 (generation-1 Multicusp Ion Source Technologies at MIT), and a low-energy beam transport system for the IsoDAR cyclotron. This will increase the overall H2 + current leading up to the cyclotron and improve the emittance of the beam injected into the cyclotron.

  2. Hospital free cash flow.

    PubMed

    Kauer, R T; Silvers, J B

    1991-01-01

    Hospital managers may find it difficult to admit their investments have been suboptimal, but such investments often lead to poor returns and less future cash. Inappropriate use of free cash flow produces large transaction costs of exit. The relative efficiency of investor-owned and tax-exempt hospitals in the product market for hospital services is examined as the free cash flow theory is used to explore capital-market conditions of hospitals. Hypotheses concerning the current competitive conditions in the industry are set forth, and the implications of free cash flow for risk, capital-market efficiency, and the cost of capital to tax-exempt institution is compared to capital-market norms.

  3. Critical Access Hospitals (CAH)

    MedlinePlus

    ... CAH Conditions of Participation . What are the location requirements for CAH status? Critical Access Hospitals must be ... clinic that does not meet the CAH distance requirements? As of January 1, 2008, all CAHs, including ...

  4. Objections to hospital philosophers.

    PubMed Central

    Ruddick, W; Finn, W

    1985-01-01

    Like morally sensitive hospital staff, philosophers resist routine simplification of morally complex cases. Like hospital clergy, they favour reflective and principled decision-making. Like hospital lawyers, they refine and extend the language we use to formulate and defend our complex decisions. But hospital philosophers are not redundant: they have a wider range of principles and categories and a sharper eye for self-serving presuppositions and implicit contradictions within our practices. As semi-outsiders, they are often best able to take an 'external point of view,' unburdened by routine, details, and departmental loyalties. Their clarifications can temporarily disrupt routine, but can eventually improve staff morale, hence team practice and patient welfare. PMID:3981573

  5. Practice Hospital Bed Safety

    MedlinePlus

    ... Bed? Todd says that there is no standard definition for hospital beds, a fact that consumers shopping ... in retail stores that don’t meet the definition of medical devices under the law, but which ...

  6. Hospital free cash flow.

    PubMed

    Kauer, R T; Silvers, J B

    1991-01-01

    Hospital managers may find it difficult to admit their investments have been suboptimal, but such investments often lead to poor returns and less future cash. Inappropriate use of free cash flow produces large transaction costs of exit. The relative efficiency of investor-owned and tax-exempt hospitals in the product market for hospital services is examined as the free cash flow theory is used to explore capital-market conditions of hospitals. Hypotheses concerning the current competitive conditions in the industry are set forth, and the implications of free cash flow for risk, capital-market efficiency, and the cost of capital to tax-exempt institution is compared to capital-market norms. PMID:1743965

  7. Home versus hospital confinement

    PubMed Central

    Barry, C. N.

    1980-01-01

    The case for hospital rather than home delivery has been powerfully argued, especially in and since the Report of the Peel Committee. Nevertheless, evidence of comparison with other countries, notably the Netherlands, suggests the choice is not necessarily simple. Some general practitioner units are now reporting perinatal mortality rates which are consistently lower than those of specialist units, and recent statistical analyses suggest that the presence of more high risk cases in consultant units does not explain this. The only big controlled home-versus-hospital trial did not lead to a significantly lower perinatal mortality rate in the hospital group. The onus of proof now seems to lie with those who advocate 100 per cent hospital confinement. PMID:7373581

  8. An energy minimization approach to automated extraction of regular building footprints from airborne LiDAR data

    NASA Astrophysics Data System (ADS)

    He, Y.; Zhang, C.; Fraser, C. S.

    2014-08-01

    This paper presents an automated approach to the extraction of building footprints from airborne LiDAR data based on energy minimization. Automated 3D building reconstruction in complex urban scenes has been a long-standing challenge in photogrammetry and computer vision. Building footprints constitute a fundamental component of a 3D building model and they are useful for a variety of applications. Airborne LiDAR provides large-scale elevation representation of urban scene and as such is an important data source for object reconstruction in spatial information systems. However, LiDAR points on building edges often exhibit a jagged pattern, partially due to either occlusion from neighbouring objects, such as overhanging trees, or to the nature of the data itself, including unavoidable noise and irregular point distributions. The explicit 3D reconstruction may thus result in irregular or incomplete building polygons. In the presented work, a vertex-driven Douglas-Peucker method is developed to generate polygonal hypotheses from points forming initial building outlines. The energy function is adopted to examine and evaluate each hypothesis and the optimal polygon is determined through energy minimization. The energy minimization also plays a key role in bridging gaps, where the building outlines are ambiguous due to insufficient LiDAR points. In formulating the energy function, hard constraints such as parallelism and perpendicularity of building edges are imposed, and local and global adjustments are applied. The developed approach has been extensively tested and evaluated on datasets with varying point cloud density over different terrain types. Results are presented and analysed. The successful reconstruction of building footprints, of varying structural complexity, along with a quantitative assessment employing accurate reference data, demonstrate the practical potential of the proposed approach.

  9. Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models

    NASA Astrophysics Data System (ADS)

    Abayowa, Bernard O.; Yilmaz, Alper; Hardie, Russell C.

    2015-08-01

    This paper presents a framework for automatic registration of both the optical and 3D structural information extracted from oblique aerial imagery to a Light Detection and Ranging (LiDAR) point cloud without prior knowledge of an initial alignment. The framework employs a coarse to fine strategy in the estimation of the registration parameters. First, a dense 3D point cloud and the associated relative camera parameters are extracted from the optical aerial imagery using a state-of-the-art 3D reconstruction algorithm. Next, a digital surface model (DSM) is generated from both the LiDAR and the optical imagery-derived point clouds. Coarse registration parameters are then computed from salient features extracted from the LiDAR and optical imagery-derived DSMs. The registration parameters are further refined using the iterative closest point (ICP) algorithm to minimize global error between the registered point clouds. The novelty of the proposed approach is in the computation of salient features from the DSMs, and the selection of matching salient features using geometric invariants coupled with Normalized Cross Correlation (NCC) match validation. The feature extraction and matching process enables the automatic estimation of the coarse registration parameters required for initializing the fine registration process. The registration framework is tested on a simulated scene and aerial datasets acquired in real urban environments. Results demonstrates the robustness of the framework for registering optical and 3D structural information extracted from aerial imagery to a LiDAR point cloud, when co-existing initial registration parameters are unavailable.

  10. Genetic Structure, Linkage Disequilibrium and Signature of Selection in Sorghum: Lessons from Physically Anchored DArT Markers

    PubMed Central

    Bouchet, Sophie; Pot, David; Deu, Monique; Rami, Jean-François; Billot, Claire; Perrier, Xavier; Rivallan, Ronan; Gardes, Laëtitia; Xia, Ling; Wenzl, Peter; Kilian, Andrzej; Glaszmann, Jean-Christophe

    2012-01-01

    Population structure, extent of linkage disequilibrium (LD) as well as signatures of selection were investigated in sorghum using a core sample representative of worldwide diversity. A total of 177 accessions were genotyped with 1122 informative physically anchored DArT markers. The properties of DArTs to describe sorghum genetic structure were compared to those of SSRs and of previously published RFLP markers. Model-based (STRUCTURE software) and Neighbor-Joining diversity analyses led to the identification of 6 groups and confirmed previous evolutionary hypotheses. Results were globally consistent between the different marker systems. However, DArTs appeared more robust in terms of data resolution and bayesian group assignment. Whole genome linkage disequilibrium as measured by mean r2 decreased from 0.18 (between 0 to 10 kb) to 0.03 (between 100 kb to 1 Mb), stabilizing at 0.03 after 1 Mb. Effects on LD estimations of sample size and genetic structure were tested using i. random sampling, ii. the Maximum Length SubTree algorithm (MLST), and iii. structure groups. Optimizing population composition by the MLST reduced the biases in small samples and seemed to be an efficient way of selecting samples to make the best use of LD as a genome mapping approach in structured populations. These results also suggested that more than 100,000 markers may be required to perform genome-wide association studies in collections covering worldwide sorghum diversity. Analysis of DArT markers differentiation between the identified genetic groups pointed out outlier loci potentially linked to genes controlling traits of interest, including disease resistance genes for which evidence of selection had already been reported. In addition, evidence of selection near a homologous locus of FAR1 concurred with sorghum phenotypic diversity for sensitivity to photoperiod. PMID:22428056

  11. 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.

  12. Integrating airborne LiDAR dataset and photographic images towards the construction of 3D building model

    NASA Astrophysics Data System (ADS)

    Idris, R.; Latif, Z. A.; Hamid, J. R. A.; Jaafar, J.; Ahmad, M. Y.

    2014-02-01

    A 3D building model of man-made objects is an important tool for various applications such as urban planning, flood mapping and telecommunication. The reconstruction of 3D building models remains difficult. No universal algorithms exist that can extract all objects in an image successfully. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) technology have changed the conventional method of topographic mapping and increased the interest of these valued datasets towards 3D building model construction. Airborne LiDAR has proven accordingly that it can provide three dimensional (3D) information of the Earth surface with high accuracy. In this study, with the availability of open source software such as Sketch Up, LiDAR datasets and photographic images could be integrated towards the construction of a 3D building model. In order to realize the work an area comprising residential areas situated at Putrajaya in the Klang Valley region, Malaysia, covering an area of two square kilometer was chosen. The accuracy of the derived 3D building model is assessed quantitatively. It is found that the difference between the vertical height (z) of the 3D building models derived from LiDAR dataset and ground survey is approximately ± 0.09 centimeter (cm). For the horizontal component (RMSExy), the accuracy estimates derived for the 3D building models were ± 0.31m. The result also shows that the qualitative assessment of the 3D building models constructed seems feasible for the depiction in the standard of LOD 3 (Level of details).

  13. Assessment of seismic loading on structures based on airborne LiDAR data from the Kalochori urban area (N. Greece)

    NASA Astrophysics Data System (ADS)

    Rovithis, Emmanouil; Kirtas, Emmanouil; Marini, Eleftheria; Bliziotis, Dimitris; Maltezos, Evangelos; Pitilakis, Dimitris; Makra, Konstantia; Savvaidis, Alexandros

    2016-08-01

    Airborne LiDAR monitoring integrated with field data is employed to assess the fundamental period and the seismic loading of structures composing an urban area under prescribed earthquake scenarios. Α piecewise work-flow is adopted by combining geometrical data of the building stock derived from a LiDAR-based 3D city model, structural data from in-situ inspections on representative city blocks and results of soil response analyses. The procedure is implemented in the residential area of Kalochori, (west of Thessaloniki in Northern Greece). Special attention is paid to the in-situ inspection of the building stock in order to discriminate recordings between actual buildings and man-made constructions that do not conform to seismic design codes and to acquire additional building stock data on structural materials, typologies and number of stories which is not feasible by the LiDAR process. The processed LiDAR and field data are employed to compute the fundamental period of each building by means of code-defined formulas. Knowledge of soil conditions in the Kalochoti area allows for soil response analyses to obtain free-field at ground surface under earthquake scenarios with varying return period. Upon combining the computed vibrational characteristics of the structures with the free-field response spectra, the seismic loading imposed on the structures of the urban area under investigation is derived for each one of the prescribed seismic motions. Results are presented in GIS environment in the form of spatially distributed spectral accelerations with direct implications in seismic vulnerability studies of an urban area.

  14. Approach to voxel-based carbon stock quanticiation using LiDAR data in tropical rainforest, Brunei

    NASA Astrophysics Data System (ADS)

    Kim, Eunji; Piao, Dongfan; Lee, Jongyeol; Lee, Woo-Kyun; Yoon, Mihae; Moon, Jooyeon

    2016-04-01

    Forest is an important means to adapt climate change as the only carbon sink recognized by the international community (KFS 2009). According to the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), Agriculture, Forestry, and Other Land Use (AFOLU) sectors including forestry contributed 24% of total anthropogenic emissions in 2010 (IPCC 2014; Tubiello et al. 2015). While all sectors excluding AFOLU have increased Greenhouse Gas (GHG) emissions, land use sectors including forestry remains similar level as before due to decreasing deforestation and increasing reforestation. In earlier researches, optical imagery has been applied for analysis (Jakubowski et al. 2013). Optical imagery collects spectral information in 2D. It is difficult to effectively quantify forest stocks, especially in dense forest (Cui et al. 2012). To detect individual trees information from remotely sensed data, Light detection and ranging (LiDAR) has been used (Hyyppäet al. 2001; Persson et al. 2002; Chen et al. 2006). Moreover, LiDAR has the ability to actively acquire vertical tree information such as tree height using geo-registered 3D points (Kwak et al. 2007). In general, however, geo-register 3D point was used with a raster format which contains only 2D information by missing all the 3D data. Therefore, this research aimed to use the volumetric pixel (referred as "voxel") approach using LiDAR data in tropical rainforest, Brunei. By comparing the parameters derived from voxel based LiDAR data and field measured data, we examined the relationships between them for the quantification of forest carbon. This study expects to be more helpful to take advantage of the strategic application of climate change adaption.

  15. Managing diversity in hospitals.

    PubMed

    Schwartz, R H; Sullivan, D B

    1993-01-01

    Hospital work force diversity, although potentially a source of creativity and improved problem solving, is often a source of political strife and the mistreatment of people based on their identification with one or another of the diverse groups that are employed in hospitals. Factors linked to these phenomena are discussed and are the basis for suggestions about how administrators can deal with the organizational pathologies that are often associated with unmanaged work force diversity.

  16. [Hospital organizational structure].

    PubMed

    Bittar, O J

    1994-01-01

    The basic point for an Institution to work is the existence of a definite organizational structure that puts together similar areas allowing decisions and the operationalization of different tasks. Knowledge and analysis of structures of private and public hospitals and a bibliography review about the issue is the purpose of this paper. Suggestions are given about the elaboration of small structures and the utilization of matrix management in order to accomplish the hospitals objectives.

  17. Organizational leadership in hospitals.

    PubMed

    Longest, B B; Darr, K; Rakich, J S

    1993-01-01

    Hospitals face very dynamic environments and must meet diverse needs in the communities they serve and respond to multiple expectations imposed by their stakeholders. Coupled with these variables, the fact that leadership in these organizations is a shared phenomenon makes organizational leadership in them very complicated. An integrative overview of the organizational leadership role of CEOs in hospitals is presented, and determinants of success in playing this role are discussed.

  18. “Can’t you initiate me here?”: Challenges to timely initiation on antiretroviral therapy among methadone clients in Dar es Salaam, Tanzania

    PubMed Central

    Saleem, Haneefa T.; Mushi, Dorothy; Hassan, Saria; Bruce, R. Douglas; Cooke, Alexis; Mbwambo, Jessie; Lambdin, Barrot H.

    2016-01-01

    Background Despite dramatic improvement in antiretroviral therapy (ART) access globally, people living with HIV who inject drugs continue to face barriers that limit their access to treatment. This paper explores barriers and facilitators to ART initiation among clients attending a methadone clinic in Dar es Salaam, Tanzania. Methods We interviewed 12 providers and 20 clients living with HIV at the Muhimbili National Hospital methadone clinic between January and February 2015. We purposively sampled clients based on sex and ART status and providers based on job function. To analyze interview transcripts, we adopted a content analysis approach. Results Participants identified several factors that hindered timely ART initiation for clients at the methadone clinic. These included delays in CD4 testing and receiving CD4 test results; off-site HIV clinics; stigma operating at the individual, social and institutional levels; insufficient knowledge of the benefits of early ART initiation among clients; treatment breakdown at the clinic level possibly due to limited staff; and initiating ART only once one feels physically ill. Participants perceived social support as a buffer against stigma and facilitator of HIV treatment. Some clients also reported that persistent monitoring and follow-up on their HIV care and treatment by methadone clinic providers led them to initiate ART. Conclusion Health system factors, stigma and limited social support pose challenges for methadone clients living with HIV to initiate ART. Our findings suggest that on-site point-of-care CD4 testing, a peer support system, and trained HIV treatment specialists who are able to counsel HIV-positive clients and initiate them on ART at the methadone clinic could help reduce barriers to timely ART initiation for methadone clients. PMID:26831364

  19. Near Field Deformation of the Mw 6.0 24 August, 2014 South Napa Earthquake Estimated by Airborne Light Detection and Ranging (LiDAR) Change Detection Techniques

    NASA Astrophysics Data System (ADS)

    Lyda, A. W.; Zhang, X.; Glennie, C. L.; Hudnut, K. W.; Brooks, B. A.

    2015-12-01

    We examine surface deformation caused by the Mw 6.0 24 August, 2014 South Napa Earthquake using high-resolution pre and post event airborne LiDAR (Light Detection and Ranging) observations. Temporally spaced LiDAR surveys taken before and after an earthquake can provide decimeter-level, 3D near-field estimates of deformation. These near-field deformation estimates can help constrain fault slip and rheology of shallow seismogenic zones. We compare and contrast estimates of deformation obtained from pre and post-event LiDAR data sets of the 2014 South Napa Earthquake using two change detection techniques, Iterative Control Point (ICP) and Particle Image Velocimetry (PIV). The ICP algorithm has been and still is the primary technique for acquiring three dimensional deformations from airborne LiDAR data sets. It conducts a rigid registration of pre-event data points to post event data points via iteratively matching data points with the smallest Euclidian distances between data sets. PIV is a technique derived from fluid mechanics that measures the displacement of a particle between two images of known time. LiDAR points act as the particles within the point cloud images so that their movement represents the horizontal deformation of the surface. The results from these change detection techniques are presented and further analyzed for differences between the techniques, the effects of temporal spacing between LiDAR collections, and the use of permanent LiDAR scatterers to constrain deformation estimates. The airborne LiDAR results will also be compared with far field deformations from space based geodetic techniques (InSAR and GNSS) and field observations of surface displacement.

  20. Cogeneration for hospitals

    SciTech Connect

    Not Available

    1985-01-01

    With health care costs on the rise, hospitals are looking for ways to reduce operating expenses-especially utility bills. But hospitals, more than anyone else, need a continuous source of electricity, heating and air conditioning. They cannot turn off medical equipment or climate control systems in the name of energy conservation. Hospital Corporation of America (HCA), with the help of the Gas Research Institute (GRI), has found a way to supply affordable and efficient power to a mid-size hospital in Houston, Texas. A 500-kilowatt (kw) gasfired cogeneration system, sold as a package, is now being field-tested at the Medical Center Del Oro, a 258-bed hospital facility. The cogeneration system, which began operating last month, will supply the medical center with 145 tons of cooling (or 2.3 MMBtu/hour space heating) and 500,000 Btu/hour for water heating, in addition to the 500 kw of electricity. A Caterpillar continuous-duty turbocharged gas-fueled engine serves as the prime mover, and heat is recovered from its exhaust and from water used to cool the engine. A Trane single-effect absorption chiller supplies chilled water for air conditioning the hospital.

  1. Financing hospital disaster preparedness.

    PubMed

    De Lorenzo, Robert A

    2007-01-01

    Disaster preparedness and response have gained increased attention in the United States as a result of terrorism and disaster threats. However, funding of hospital preparedness, especially surge capacity, has lagged behind other preparedness priorities. Only a small portion of the money allocated for national preparedness is directed toward health care, and hospitals receive very little of that. Under current policy, virtually the entire funding stream for hospital preparedness comes from general tax revenues. Medical payers (e.g., Medicare, Medicaid, and private insurance) directly fund little, if any, of the current bill. Funding options to improve preparedness include increasing the current federal grants allocated to hospitals, using payer fees or a tax to subsidize preparedness, and financing other forms of expansion capability, such as mobile hospitals. Alternatively, the status quo of marginal preparedness can be maintained. In any event, achieving higher levels of preparedness likely will take the combined commitment of the hospital industry, public and private payers, and federal, state, and local governments. Ultimately, the costs of preparedness will be borne by the public in the form of taxes, higher healthcare costs, or through the acceptance of greater risk.

  2. Sisters in Dutch hospitals.

    PubMed

    van den Bergh-Braam, A H

    1985-11-01

    This study focuses on hospital sisters in 30 Dutch hospitals. The so-called role-set approach has been adopted. In this approach the sisters are the focal persons. Direct superiors, specialists, registered nurses and student nurses acted as role-senders. The possible number of respondents is 600 (120 of each group). The response of hospital sisters is 100%, that of role-senders 88%. The study started out as an attempt to collect background information on the causes of wastage of sisters. High wastage rates are generally regarded as an indication of an unfavourable working environment. Since hospital sisters occupy a key position in hospitals, the ward problems will be studied from their angle. Although wastage rates have dropped recently, it does not necessarily follow that the working environment has improved. Wastage is known to act as a safety valve, thus allowing tensions to resolve. The threat of unemployment clogs this outlet, which increases the tensions on the hospital ward. Data from the study show that work overload is one of the major stress factors for sisters. Analyses demonstrated that there exists a relationship between work overload and tensions with the management and direct superiors, tensions in job execution, irritableness on the ward, low self-esteem, health complaints and psychological condition. Sisters with an excessive job involvement refer to work overload more often than their moderate colleagues. There is a relationship between an unfavourable working environment and irritableness of sisters.

  3. Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography

    USGS Publications Warehouse

    Poppenga, Sandra K.; Gesch, Dean B.; Worstell, Bruce B.

    2013-01-01

    The 1:24,000-scale high-resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time-relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR-derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.

  4. Intergration of LiDAR Data with Aerial Imagery for Estimating Rooftop Solar Photovoltaic Potentials in City of Cape Town

    NASA Astrophysics Data System (ADS)

    Adeleke, A. K.; Smit, J. L.

    2016-06-01

    Apart from the drive to reduce carbon dioxide emissions by carbon-intensive economies like South Africa, the recent spate of electricity load shedding across most part of the country, including Cape Town has left electricity consumers scampering for alternatives, so as to rely less on the national grid. Solar energy, which is adequately available in most part of Africa and regarded as a clean and renewable source of energy, makes it possible to generate electricity by using photovoltaics technology. However, before time and financial resources are invested into rooftop solar photovoltaic systems in urban areas, it is important to evaluate the potential of the building rooftop, intended to be used in harvesting the solar energy. This paper presents methodologies making use of LiDAR data and other ancillary data, such as high-resolution aerial imagery, to automatically extract building rooftops in City of Cape Town and evaluate their potentials for solar photovoltaics systems. Two main processes were involved: (1) automatic extraction of building roofs using the integration of LiDAR data and aerial imagery in order to derive its' outline and areal coverage; and (2) estimating the global solar radiation incidence on each roof surface using an elevation model derived from the LiDAR data, in order to evaluate its solar photovoltaic potential. This resulted in a geodatabase, which can be queried to retrieve salient information about the viability of a particular building roof for solar photovoltaic installation.

  5. An Integrated Method for Mapping Impervious and Pervious Areas in Urban Environments Using Hyperspectral and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Hashemi Beni, L.; McArdle, S.; Khayer, Y.

    2014-11-01

    As urbanization continues to increase and extreme climatic events become more prevalent, urban planners and engineers are actively implementing adaptive measures to protect urban assets and communities. To support the urban planning adaptation process, mapping of impervious and pervious areas is essential to understanding the hydrodynamic environment within urban areas for flood risk planning. The application of advance geospatial data and analytical techniques using remote sensing and GIS can improve land surface characterization to better quantify surface run-off and infiltration. This study presents a method to combine airborne hyperspectral and LiDAR data for classifying pervious (e.g. vegetation, gravel, and soil) and impervious (e.g. asphalt and concrete) areas within road allowance areas for the City of Surrey, British Columbia, Canada. Hyperspectral data was acquired using the Compact Airborne Spectrographic Imager (CASI) at 1 m ground spatial resolution, consisting of 72 spectral bands, and LiDAR data acquired from Leica Airborne LiDAR system at a density of 20 points/m2. A spectral library was established using 10 cm orthophotography and GIS data to identify surface features. In addition to spectral functions such as mean and standard deviation, several spectral indices were developed to discriminate between asphalt, concrete, gravel, vegetation, and shadows respectively. A spectral analysis of selected endmembers was conducted and an initial classification technique was applied using Spectral Angle Mapper (SAM). The classification results (i.e. shadows) were improved by integrating LIDAR data with the hyperspectral data.

  6. Mapping standing dead trees (snags) in the aftermath of the 2013 Rim Fire using airborne LiDAR data.

    NASA Astrophysics Data System (ADS)

    Casas Planes, Á.; Garcia-Alonso, M.; Koltunov, A.; Ustin, S.; Falk, M.; Ramirez, C.; Siegel, R.

    2014-12-01

    Abundance and spatial distribution of standing dead trees (snags) are key indicators of forest biodiversity and ecosystem health and represent a critical component of habitat for various wildlife species, including the great grey owl and the black-backed woodpecker. In this work we assess the potential of light detection and ranging (LiDAR) to discriminate snags from the live trees and map their distribution. The study area encompasses the burn perimeter of the Rim Fire, the third largest wildfire in California's recorded history (~104.000 ha) and represents a heterogeneous mosaic of mixed conifer forests, hardwood, and meadows. The snags mapping procedure is based on a 3D single tree detection using a Watershed algorithm and the extraction of height and intensity metrics within each segment. Variables selected using Gaussian processes form a feature space for a classifier to distinguish between dead trees and live trees. Finally, snag density and snag diameter classes that are relevant for avian species are mapped. This work shows the use of LiDAR metrics to quantify ecological variables related to the vertical heterogeneity of the forest canopy that are important in the identification of snags, for example, fractional cover. We observed that intensity-related variables are critical to the successful identification of snags and their distribution. Our study highlights the importance of high-density LiDAR for characterizing the forest structural variables that contribute to the assessment of wildlife habitat suitability.

  7. Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification.

    PubMed

    Gong, Wei; Sun, Jia; Shi, Shuo; Yang, Jian; Du, Lin; Zhu, Bo; Song, Shalei

    2015-09-02

    The abilities of multispectral LiDAR (MSL) as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%-39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image.

  8. Quantifying erosion and deposition patterns using airborne LiDAR following the 2012 High Park Fire and 2013 Colorado Flood

    NASA Astrophysics Data System (ADS)

    Brogan, D. J.; Nelson, P. A.; MacDonald, L. H.

    2015-12-01

    Quantifying and predicting geomorphic change over large spatial scales is increasingly feasible and of growing interest as repeat high resolution topography becomes available. We began detailed field studies of channel geomorphic change using RTK-GPS in two 15 km2 watersheds following the 2012 High Park Fire; the watersheds were then subjected to a several-hundred year flood in September 2013. During this time a series of airborne LiDAR datasets were collected, and the objectives of this study were to: 1) determine and compare the spatial variability in channel and valley erosion and deposition over time from the LiDAR; and 2) determine if the observed changes can be predicted from channel and valley bottom characteristics. Data quality issues in the initial LiDAR required us to rotate and translate flight lines in order to co-register ground-classified point clouds between successive datasets; uncertainty was then estimated using our RTK-GPS field measurements. Topographic changes were calculated using the Multiscale Model to Model Cloud Comparison (M3C2) algorithm. Results indicate that the 2013 flood mobilized much more sediment than was mobilized due to the fire alone; unfortunately the uncertainty in differencing is still frequently greater than the observed changes, especially within transfer reaches. Valley expansion and constriction are major controls on spatial patterns of erosion and deposition, suggesting that topographic metrics such as longitudinal distributions of channel slope and valley confinement may provide quasi-physically based estimates of sediment deposition and delivery potential.

  9. Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification.

    PubMed

    Gong, Wei; Sun, Jia; Shi, Shuo; Yang, Jian; Du, Lin; Zhu, Bo; Song, Shalei

    2015-01-01

    The abilities of multispectral LiDAR (MSL) as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%-39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image. PMID:26340630

  10. Exploring Germplasm Diversity to Understand the Domestication Process in Cicer spp. Using SNP and DArT Markers

    PubMed Central

    Roorkiwal, Manish; von Wettberg, Eric J.; Upadhyaya, Hari D.; Warschefsky, Emily; Rathore, Abhishek; Varshney, Rajeev K.

    2014-01-01

    To estimate genetic diversity within and between 10 interfertile Cicer species (94 genotypes) from the primary, secondary and tertiary gene pool, we analysed 5,257 DArT markers and 651 KASPar SNP markers. Based on successful allele calling in the tertiary gene pool, 2,763 DArT and 624 SNP markers that are polymorphic between genotypes from the gene pools were analyzed further. STRUCTURE analyses were consistent with 3 cultivated populations, representing kabuli, desi and pea-shaped seed types, with substantial admixture among these groups, while two wild populations were observed using DArT markers. AMOVA was used to partition variance among hierarchical sets of landraces and wild species at both the geographical and species level, with 61% of the variation found between species, and 39% within species. Molecular variance among the wild species was high (39%) compared to the variation present in cultivated material (10%). Observed heterozygosity was higher in wild species than the cultivated species for each linkage group. Our results support the Fertile Crescent both as the center of domestication and diversification of chickpea. The collection used in the present study covers all the three regions of historical chickpea cultivation, with the highest diversity in the Fertile Crescent region. Shared alleles between different gene pools suggest the possibility of gene flow among these species or incomplete lineage sorting and could indicate complicated patterns of divergence and fusion of wild chickpea taxa in the past. PMID:25010059

  11. Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification

    PubMed Central

    Gong, Wei; Sun, Jia; Shi, Shuo; Yang, Jian; Du, Lin; Zhu, Bo; Song, Shalei

    2015-01-01

    The abilities of multispectral LiDAR (MSL) as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%–39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image. PMID:26340630

  12. Modeling spatiotemporal patterns of understory light intensity using airborne laser scanner (LiDAR)

    NASA Astrophysics Data System (ADS)

    Peng, Shouzhang; Zhao, Chuanyan; Xu, Zhonglin

    2014-11-01

    This study described a spatiotemporally explicit 3D raytrace model to provide spatiotemporal patterns of understory light (light intensity in the forest floor and along the vertical gradient). The model was built based on voxels derived from LiDAR and field investigation data, geographical information (elevation and location), and solar position (azimuth and altitude angles). We calculated the distance (L, in meters) traveled by solar ray in the crowns based on the model, and then calibrated and verified the light attenuation function using L based on Beer's law. L and the ratio of below canopy light intensity to above canopy light intensity showed obviously exponential relationship, with R2 = 0.94 and P < 0.05. Estimated and observed understory light intensities were obviously positively correlated, with R2 = 0.92 and P < 0.01, and the estimated values were slightly lower than the observed values. The spatiotemporal patterns of the light intensity in the forest floor were mapped with the respect to the solar position, and these patterns represented the variations in the forest-shaded area. The spatial patterns of the light intensity along vertical gradient were also mapped, and they showed strong variations. We concluded that L could account for the complex patterns of understory light environment with respect to the geographical and solar position variations. The 3D raytrace model can be integrated with ecological or hydrological models to resolve several issues, such as plant succession and competition, soil evaporation, plant transpiration, and snowmelt in the forest.

  13. Taking Stock of Circumboreal Forest Carbon With Ground Measurements, Airborne and Spaceborne LiDAR

    NASA Technical Reports Server (NTRS)

    Neigh, Christopher S. R.; Nelson, Ross F.; Ranson, K. Jon; Margolis, Hank A.; Montesano, Paul M.; Sun, Guoqing; Kharuk, Viacheslav; Naesset, Erik; Wulder, Michael A.; Andersen, Hans-Erik

    2013-01-01

    The boreal forest accounts for one-third of global forests, but remains largely inaccessible to ground-based measurements and monitoring. It contains large quantities of carbon in its vegetation and soils, and research suggests that it will be subject to increasingly severe climate-driven disturbance. We employ a suite of ground-, airborne- and space-based measurement techniques to derive the first satellite LiDAR-based estimates of aboveground carbon for the entire circumboreal forest biome. Incorporating these inventory techniques with uncertainty analysis, we estimate total aboveground carbon of 38 +/- 3.1 Pg. This boreal forest carbon is mostly concentrated from 50 to 55degN in eastern Canada and from 55 to 60degN in eastern Eurasia. Both of these regions are expected to warm >3 C by 2100, and monitoring the effects of warming on these stocks is important to understanding its future carbon balance. Our maps establish a baseline for future quantification of circumboreal carbon and the described technique should provide a robust method for future monitoring of the spatial and temporal changes of the aboveground carbon content.

  14. Multispectral airborne laser scanning - a new trend in the development of LiDAR technology

    NASA Astrophysics Data System (ADS)

    Bakuła, K.

    2015-12-01

    Airborne laser scanning (ALS) is the one of the most accurate remote sensing techniques for data acquisition where the terrain and its coverage is concerned. Modern scanners have been able to scan in two or more channels (frequencies of the laser) recently. This gives the rise to the possibility of obtaining diverse information about an area with the different spectral properties of objects. The paper presents an example of a multispectral ALS system - Titan by Optech - with the possibility of data including the analysis of digital elevation models accuracy and data density. As a result of the study, the high relative accuracy of LiDAR acquisition in three spectral bands was proven. The mean differences between digital terrain models (DTMs) were less than 0.03 m. The data density analysis showed the influence of the laser wavelength. The points clouds that were tested had average densities of 25, 23 and 20 points per square metre respectively for green (G), near-infrared (NIR) and shortwave-infrared (SWIR) lasers. In this paper, the possibility of the generation of colour composites using orthoimages of laser intensity reflectance and its classification capabilities using data from airborne multispectral laser scanning for land cover mapping are also discussed and compared with conventional photogrammetric techniques.

  15. The prevalence of lameness and associated risk factors in cart mules in Bahir Dar, Ethiopia.

    PubMed

    Ali, Alina; Orion, Solomon; Tesfaye, Tewodros; Zambriski, Jennifer A

    2016-10-01

    Ethiopia has 7.1 million donkeys and mules, the majority of which are used as pack animals. Factors such as poor harness quality, long-distance traveling, and heavy cartloads have been linked to reduced work efficiency. Addressing the health and welfare of working equids is imperative not only for the animals but also for the households dependent upon them for livelihood. In developing countries, 75 % of working equids have gait or limb abnormalities, but the relationship between workload and prevalence of lameness is unknown. We examined 450 cart mules in Bahir Dar, Ethiopia. Lameness and workload were assessed through use of a survey and lameness exam. We found that 26.8 % of cart mules were lame, and acute lameness of the forelimb was the most common. Animals with poor harness quality were 2.5 times more likely to have sores and 1.6 times more likely to be lame. Lameness tended to be associated with cartloads >700 kg (P = 0.09), and there was a significant association between multiple-leg lameness and cartload weight (P = 0.03). The presence of sores was the best predictor of lameness (P = 0.001). Possible areas of intervention may include education to reduce average daily workload and improving harness design.

  16. Investigating sediment budgets and pathways using LiDAR DEMs of difference and a geomorphological map

    NASA Astrophysics Data System (ADS)

    Hilger, Ludwig; Becht, Michael; Heckmann, Tobias

    2014-05-01

    In alpine catchments sediment is moved from one landform to another as long as they are coupled by the activity of geomorphic processes. The spatial and functional interaction of these processes forms sediment cascades reaching from sediment sources or stores to sediment sinks, and ultimately to the catchment outlet. In study presented here, multitemporal high-resolution LiDAR datasets are used to establish morphological sediment budgets. These can be calculated on the raster cell scale, i.e. by differencing digital elevation models (DEM), and on the landform scale, by establishing the net balance of eroded and accumulated material; in the latter case, the spatial unit is a polygon identifying a particular landform on a detailed geomorphological map. The flow of mobilised sediment can be estimated on a DEM using a variety of flow routing algorithms, and the net balance (sediment eroded - sediment deposited) is accumulated along specific pathways. The results of landform-based sediment budgets can be used to validate the flow routing algorithms and to assess functional connectivity between landforms that are arranged along a toposequence. Graph theory is used to store and investigate resulting sediment pathways on different aggregation levels. The incorporation of the geomorphological map highlights potential advantages of object-based over pixel-based approaches to generating graph nodes and analysing sediment cascades.

  17. Automated As-Built Model Generation of Subway Tunnels from Mobile LiDAR Data.

    PubMed

    Arastounia, Mostafa

    2016-01-01

    This study proposes fully-automated methods for as-built model generation of subway tunnels employing mobile Light Detection and Ranging (LiDAR) data. The employed dataset is acquired by a Velodyne HDL 32E and covers 155 m of a subway tunnel containing six million points. First, the tunnel's main axis and cross sections are extracted. Next, a preliminary model is created by fitting an ellipse to each extracted cross section. The model is refined by employing residual analysis and Baarda's data snooping method to eliminate outliers. The final model is then generated by applying least squares adjustment to outlier-free data. The obtained results indicate that the tunnel's main axis and 1551 cross sections at 0.1 m intervals are successfully extracted. Cross sections have an average semi-major axis of 7.8508 m with a standard deviation of 0.2 mm and semi-minor axis of 7.7509 m with a standard deviation of 0.1 mm. The average normal distance of points from the constructed model (average absolute error) is also 0.012 m. The developed algorithm is applicable to tunnels with any horizontal orientation and degree of curvature since it makes no assumptions, nor does it use any a priori knowledge regarding the tunnel's curvature and horizontal orientation. PMID:27649172

  18. Monitoring changes in the Platte River riparian corridor with serial LiDAR surveys

    USGS Publications Warehouse

    Kinzel, Paul J.; Nelson, Jonathan M.; Wright, C. Wayne

    2006-01-01

    The Platte River in central Nebraska is a wide, sand-bedded river that provides habitat for migratory water birds along the North American flyway. The central Platte River functions as critical habitat for the endangered whooping crane (Grus americana) and also is an important habitat for the endangered least tern (Sterna antillarum) and the threatened piping plover (Charadrius melodus). Upstream water-resource development over the last century has decreased the water and sediment supplied to the central Platte River. This has resulted in vegetation encroachment and narrowing of Platte River channels. The National Academy of Sciences' National Research Council, in a recent review of these critical habitat designations, concluded that the current morphology of Platte River channels is limiting the recovery of the endangered and threatened avian species. Habitat-enhancement efforts along the Platte River currently (2006) are focused on the clearing of vegetation from in-channel and riparian areas, whereas future plans propose the release of water from upstream dams as a means to prevent vegetation from encroaching on the active river channel. For this reason, monitoring the physical response of the river channel to these management treatments is an important component of a proposed habitat recovery program. Understanding the effects of management strategies on Platte River riparian habitat also is a key objective of the U.S. Geological Survey's Platte River Priority Ecosystem Program (http://mcmcweb.er.usgs.gov/platte/). This fact sheet describes applications of LiDAR to monitor changes in the Platte River riparian corridor.

  19. Mapping of ice, snow and water using aircraft-mounted LiDAR

    NASA Astrophysics Data System (ADS)

    Church, Philip; Matheson, Justin; Owens, Brett

    2016-05-01

    Neptec Technologies Corp. has developed a family of obscurant-penetrating 3D laser scanners (OPAL 2.0) that are being adapted for airborne platforms for operations in Degraded Visual Environments (DVE). The OPAL uses a scanning mechanism based on the Risley prism pair. Data acquisition rates can go as high as 200kHz for ranges within 240m and 25kHz for ranges exceeding 240m. The scan patterns are created by rotating two prisms under independent motor control producing a conical Field-Of-View (FOV). An OPAL laser scanner with 90° FOV was installed on a Navajo aircraft, looking down through an aperture in the aircraft floor. The rotation speeds of the Risley prisms were selected to optimize a uniformity of the data samples distribution on the ground. Flight patterns simulating a landing approach over snow and ice in an unprepared Arctic environment were also performed to evaluate the capability of the OPAL LiDAR to map snow and ice elevation distribution in real-time and highlight potential obstacles. Data was also collected to evaluate the detection of wires when flying over water, snow and ice. Main results and conclusions obtained from the flight data analysis are presented.

  20. Petroleum potential of the Amu Dar`ya Province, Western Uzbekistan and Eastern Turkmenistan

    SciTech Connect

    Clarke, J.W.

    1995-05-01

    The Amu Dar`ya gas-oil province coincides with a Mesozoic and Cenozoic sag basin that developed on an intermontane depression filled largely by Permian-Triassic redbeds and volcanics. The stratigraphic section of the basin is divided into two parts by an extensive evaporite deposit of Kimmeridgian age. The section below the evaporite consists of Lower-Middle Jurassic clastic rocks overlain by reef-bearing carbonate rocks of Callovian and Oxfordian age. The upper Jurassic and Cretaceous-Paleogene section consists largely of clastic rocks. Structurally the province is a mosaic of highs and lows controlled by basement faults. The Kimmeridgian evaporite is a regional seal for numerous pools in the Callovian-Oxfordian carbonate rocks. In the border areas of the province where the evaporite is not present, the hydrocarbons have migrated farther upward to collect in Lower Cretaceous traps. Prospects for further discovery are excellent in most parts of the province, but are particularly favorable in carbonate reef buildups in the southeastern part of the province. 18 refs., 6 figs.

  1. Using airborne LiDAR to investigated the bedrock incision in the Tsaoling Landslide surface, Taiwan

    NASA Astrophysics Data System (ADS)

    Hou, Chin-Shyong; Chen, Yi-Zhong; Hsieh, Yu-Chung; Chen, Rou-Fei; Wu, Ruo-Ying

    2014-05-01

    In recent decades, a great number of studies have investigated the tectonic topographic evolution and development of active orogenic belts that cause the dynamics related to a variety of terrain features. In particular, the incision of bedrock via erosion by rivers plays a crucial research role. Erosion gullies reflect the incision of bedrock by rivers during the tectonic and topographic evolution of active orogenic zones; however, a limited amount of measurement data is currently available. Therefore, this study explored the incision erosion rate of different lithologies in the collapsed surface of a landslide induced by the 1999 Chi-chi earthquake in the Tsaoling area. This study uses the 1 m high-resolution DEM established by the Central Geological Survey via airborne LiDAR, organized by the Ministry of Economic Affairs (MOEA. In this study, we investigated the distribution of erosion gullies produced in different rock formations by the Tsaoling landslide based on an openness analysis using a red relief image map (RRIM) and calculated the bedrock incision rate for the Cholan Formation and Chishui Shale for 1999, 2011 and 2012, which was 30-40 cm/yr and 54-90 cm/yr on average, respectively. These results indicated that the Cholan Formation has a higher resistance to erosion than the Chishui Shale, where the erosion was more serious.

  2. Automated As-Built Model Generation of Subway Tunnels from Mobile LiDAR Data

    PubMed Central

    Arastounia, Mostafa

    2016-01-01

    This study proposes fully-automated methods for as-built model generation of subway tunnels employing mobile Light Detection and Ranging (LiDAR) data. The employed dataset is acquired by a Velodyne HDL 32E and covers 155 m of a subway tunnel containing six million points. First, the tunnel’s main axis and cross sections are extracted. Next, a preliminary model is created by fitting an ellipse to each extracted cross section. The model is refined by employing residual analysis and Baarda’s data snooping method to eliminate outliers. The final model is then generated by applying least squares adjustment to outlier-free data. The obtained results indicate that the tunnel’s main axis and 1551 cross sections at 0.1 m intervals are successfully extracted. Cross sections have an average semi-major axis of 7.8508 m with a standard deviation of 0.2 mm and semi-minor axis of 7.7509 m with a standard deviation of 0.1 mm. The average normal distance of points from the constructed model (average absolute error) is also 0.012 m. The developed algorithm is applicable to tunnels with any horizontal orientation and degree of curvature since it makes no assumptions, nor does it use any a priori knowledge regarding the tunnel’s curvature and horizontal orientation. PMID:27649172

  3. Prevalence of helmet use among motorcycle users in Dar Es Salaam, Tanzania

    PubMed Central

    Kauky, Cosmas George; Kishimba, Rogath Saika; Urio, Loveness John; Abade, Ahmed Mohammed; Mghamba, Janneth Maridadi

    2015-01-01

    Introduction The purpose of this study was to determine prevalence of helmet use among motorcyclists as one of the preventive measures for road traffic injuries. Methods A cross sectional observational survey was conducted in the 3 Districts (Kinondoni, Ilala and Temeke) that make Dar es Salaam. Tanzania. A standardized line-listing form and checklist were used to record the drivers and passengers use of helmet as observed by study investigators. Data for helmet use was collected on one weekday and one weekend day. Time for observation was during the rush hour in the morning, noon and evening. Then data were entered into Epi Info 3.5.1 analysis Results A total of 7,678 motorcycle drivers and 4,328 passengers observed in this study. Drivers were almost male (98.8%) and 73.2% of all passengers were males. The prevalence use of helmet use among motorcyclist's riders was 82.1% and among passengers was 22.5%. Proportion of helmet use in drivers and passengers observed were relatively similar during weekday and weekend day and time of observation. Conclusion This study showed the relative high helmet use among motorcyclist riders though very low in passengers. This study recommends increased community awareness on helmet use among passengers and enforcement and revival of road safety laws of passengers and motorcyclists on helmet use. PMID:26309470

  4. Automated delineation of karst sinkholes from LiDAR-derived digital elevation models

    NASA Astrophysics Data System (ADS)

    Wu, Qiusheng; Deng, Chengbin; Chen, Zuoqi

    2016-08-01

    Sinkhole mapping is critical for understanding hydrological processes and mitigating geological hazards in karst landscapes. Current methods for identifying sinkholes are primarily based on visual interpretation of low-resolution topographic maps and aerial photographs with subsequent field verification, which is labor-intensive and time-consuming. The increasing availability of high-resolution LiDAR-derived digital elevation data allows for an entirely new level of detailed delineation and analyses of small-scale geomorphologic features and landscape structures at fine scales. In this paper, we present a localized contour tree method for automated extraction of sinkholes in karst landscapes. One significant advantage of our automated approach for sinkhole extraction is that it may reduce inconsistencies and alleviate repeatability concerns associated with visual interpretation methods. In addition, the proposed method has contributed to improving the sinkhole inventory in several ways: (1) detection of non-inventoried sinkholes; (2) identification of previously inventoried sinkholes that have been filled; (3) delineation of sinkhole boundaries; and (4) characterization of sinkhole morphometric properties. We applied the method to Fillmore County in southeastern Minnesota, USA, and identified three times as many sinkholes as the existing database for the same area. The results suggest that previous visual interpretation method might significantly underestimate the number of potential sinkholes in the region. Our method holds great potential for creating and updating sinkhole inventory databases at a regional scale in a timely manner.

  5. Extracting Urban Ground Object Information from Images and LiDAR Data

    NASA Astrophysics Data System (ADS)

    Yi, Lina; Zhao, Xuesheng; Li, Luan; Zhang, Guifeng

    2016-06-01

    To deal with the problem of urban ground object information extraction, the paper proposes an object-oriented classification method using aerial image and LiDAR data. Firstly, we select the optimal segmentation scales of different ground objects and synthesize them to get accurate object boundaries. Then, this paper uses ReliefF algorithm to select the optimal feature combination and eliminate the Hughes phenomenon. Eventually, the multiple classifier combination method is applied to get the outcome of the classification. In order to validate the feasible of this method, this paper selects two experimental regions in Stuttgart and Germany (Region A and B, covers 0.21 km2 and 1.1 km2 respectively). The aim of the first experiment on the Region A is to get the optimal segmentation scales and classification features. The overall accuracy of the classification reaches to 93.3 %. The purpose of the experiment on region B is to validate the application-ability of this method for a large area, which is turned out to be reaches 88.4 % overall accuracy. In the end of this paper, the conclusion shows that the proposed method can be performed accurately and efficiently in terms of urban ground information extraction and be of high application value.

  6. Deconstructing a polygenetic landscape using LiDAR and multi-resolution analysis

    NASA Astrophysics Data System (ADS)

    Barrineau, Patrick; Dobreva, Iliyana; Bishop, Michael P.; Houser, Chris

    2016-04-01

    It is difficult to deconstruct a complex polygenetic landscape into distinct process-form regimes using digital elevation models (DEMs) and fundamental land-surface parameters. This study describes a multi-resolution analysis approach for extracting geomorphological information from a LiDAR-derived DEM over a stabilized aeolian landscape in south Texas that exhibits distinct process-form regimes associated with different stages in landscape evolution. Multi-resolution analysis was used to generate average altitudes using a Gaussian filter with a maximum radius of 1 km at 20 m intervals, resulting in 50 generated DEMs. This multi-resolution dataset was analyzed using Principal Components Analysis (PCA) to identify the dominant variance structure in the dataset. The first 4 principal components (PC) account for 99.9% of the variation, and classification of the variance structure reveals distinct multi-scale topographic variation associated with different process-form regimes and evolutionary stages. Our results suggest that this approach can be used to generate quantitatively rigorous morphometric maps to guide field-based sedimentological and geophysical investigations, which tend to use purposive sampling techniques resulting in bias and error.

  7. Exploring full-waveform LiDAR parameters for tree species classification

    NASA Astrophysics Data System (ADS)

    Heinzel, Johannes; Koch, Barbara

    2011-02-01

    Precise tree species classification with high density full-waveform LiDAR data is a key research topic for automated forest inventory. Most approaches constrain to geometric features and only a few consider intensity values. Since full-waveform data offers a much larger amount of deducible information this study explores a high number of parameter and feature combinations. Those variables having the highest impact on species differentiation are determined. To handle the large amount of airborne full-waveform data and to extract a comprehensive number of variable combinations an improved algorithm was developed. The full-waveform point parameters amplitude, width, range corrected intensity and total number of targets within a beam are transferred into raster covering a test site of 10 km 2. It was possible to isolate the three most important variables based on the intensity, the width and the total number of targets. Up to six tree species were classified with an overall accuracy of 57%, limiting to the four main species accuracy was improved to 78% and constraining just to conifers and broadleaved trees even 91% could be classified correctly.

  8. An automated algorithm for extracting road edges from terrestrial mobile LiDAR data

    NASA Astrophysics Data System (ADS)

    Kumar, Pankaj; McElhinney, Conor P.; Lewis, Paul; McCarthy, Timothy

    2013-11-01

    Terrestrial mobile laser scanning systems provide rapid and cost effective 3D point cloud data which can be used for extracting features such as the road edge along a route corridor. This information can assist road authorities in carrying out safety risk assessment studies along road networks. The knowledge of the road edge is also a prerequisite for the automatic estimation of most other road features. In this paper, we present an algorithm which has been developed for extracting left and right road edges from terrestrial mobile LiDAR data. The algorithm is based on a novel combination of two modified versions of the parametric active contour or snake model. The parameters involved in the algorithm are selected empirically and are fixed for all the road sections. We have developed a novel way of initialising the snake model based on the navigation information obtained from the mobile mapping vehicle. We tested our algorithm on different types of road sections representing rural, urban and national primary road sections. The successful extraction of road edges from these multiple road section environments validates our algorithm. These findings and knowledge provide valuable insights as well as a prototype road edge extraction tool-set, for both national road authorities and survey companies.

  9. A temperature inversion-induced air pollution process as analyzed from Mie LiDAR data.

    PubMed

    Wu, Wanning; Zha, Yong; Zhang, Jiahua; Gao, Jay; He, Junliang

    2014-05-01

    A severe air pollution event in the Xianlin District of Nanjing City, China during 23-24 December 2012 was analyzed in terms of aerosol extinction coefficient and AOT retrieved from Mie scattering LiDAR data, in conjunction with in situ particulate concentrations measured near the Earth's surface, and the Weather Research Forecast-derived meteorological conditions. Comprehensive analyses of temperature, humidity, wind direction and velocity, and barometric pressure led to the conclusion that this pollution event was caused by advection inversion. In the absence of temperature inversion, the atmosphere at a height of 0.15 km has a relatively large extinction coefficient. In situ measured particulates exhibited a very large diurnal range. However, under the influence of turbulences, AOT was rather stable with a value <0.2 at an altitude below 0.8 km. Advection inversion appeared at 9:00 AM on 24 December, and did not dissipate until 22:00 PM. This temperature inversion, to some degree, inhibited the dispersion of near-surface particulates. Affected by this temperature inversion, the atmospheric extinction coefficient near the surface became noticeably larger. Near-surface particulates hardly varied at a concentration around 0.2mg/m(3). AOT at an altitude below 0.8 km rose to 0.31. PMID:24556291

  10. The health-related microbiological quality of bottled drinking water sold in Dar es Salaam, Tanzania.

    PubMed

    Kassenga, Gabriel R

    2007-03-01

    The consumption of bottled and plastic-bagged drinking water in Tanzania has increased largely because of the deteriorating quality of tap water. It is uncertain whether these water products are safe for drinking. In this study, the microbiological quality of bottled and plastic-bagged drinking water sold in Dar es Salaam, Tanzania, was investigated. One hundred and thirty samples representing 13 brands of bottled water collected from shops, supermarkets and street vendors were analysed for total coliform and faecal coliform organisms as well as heterotrophic bacteria. These were compared with 61 samples of tap water. Heterotrophic bacteria were detected in 92% of the bottled water samples analysed. Total and faecal coliform bacteria were present in 4.6% and 3.6%, respectively, of samples analysed with a tendency for higher contamination rates in plastic-bagged drinking water. Microbiological quality of tap water was found to be worse compared with bottled water, with 49.2% and 26.2% of sampling points showing the presence of total coliform and faecal coliform organisms, respectively. The results suggest caution and vigilance to avert outbreaks of waterborne diseases from these types of drinking water.

  11. A temperature inversion-induced air pollution process as analyzed from Mie LiDAR data.

    PubMed

    Wu, Wanning; Zha, Yong; Zhang, Jiahua; Gao, Jay; He, Junliang

    2014-05-01

    A severe air pollution event in the Xianlin District of Nanjing City, China during 23-24 December 2012 was analyzed in terms of aerosol extinction coefficient and AOT retrieved from Mie scattering LiDAR data, in conjunction with in situ particulate concentrations measured near the Earth's surface, and the Weather Research Forecast-derived meteorological conditions. Comprehensive analyses of temperature, humidity, wind direction and velocity, and barometric pressure led to the conclusion that this pollution event was caused by advection inversion. In the absence of temperature inversion, the atmosphere at a height of 0.15 km has a relatively large extinction coefficient. In situ measured particulates exhibited a very large diurnal range. However, under the influence of turbulences, AOT was rather stable with a value <0.2 at an altitude below 0.8 km. Advection inversion appeared at 9:00 AM on 24 December, and did not dissipate until 22:00 PM. This temperature inversion, to some degree, inhibited the dispersion of near-surface particulates. Affected by this temperature inversion, the atmospheric extinction coefficient near the surface became noticeably larger. Near-surface particulates hardly varied at a concentration around 0.2mg/m(3). AOT at an altitude below 0.8 km rose to 0.31.

  12. Medicalization and morality in a weak state: health, hygiene and water in Dar Es Salaam, Tanzania.

    PubMed

    Obrist, Brigit

    2004-04-01

    Inspired by Foucault, many studies have examined the medicalization of everyday life in Western societies. This paper reconsiders potentials and limitations of this concept in an African city. Grounded in ethnographic research in Dar es Salaam, Tanzania, it concentrates on cleanliness, health and water in a lower middle-class neighbourhood. The findings show that women are familiar with professional health development discourses emphasizing cleanliness as a high value linked to bodily and domestic health. These discourses have been diffused in schools, clinics and other institutions during the colonial and socialist period. Women not only refer to these discourses, they try to reproduce them in daily practice and even demand them. This coercive yet voluntary nature of institutionalized discourses points to 'paradoxes of medicalization' also found in Western societies. It acquires, however, different meanings in a weak state like contemporary Tanzania which hardly manages to institutionalize medicalization through professional practice. Under such conditions, women who choose to follow health development discourses suffer a heavier practical, intellectual and emotional burden than those who are less committed. This may at least partly explain why many women assume a pragmatic stance towards the medicalization of everyday life.

  13. Description of durum wheat linkage map and comparative sequence analysis of wheat mapped DArT markers with rice and Brachypodium genomes

    PubMed Central

    2013-01-01

    Background The importance of wheat to the world economy, together with progresses in high-throughput next-generation DNA sequencing, have accelerated initiatives of genetic research for wheat improvement. The availability of high density linkage maps is crucial to identify genotype-phenotype associations, but also for anchoring BAC contigs to genetic maps, a strategy followed for sequencing the wheat genome. Results Here we report a genetic linkage map in a durum wheat segregating population and the study of mapped DArT markers. The linkage map consists of 126 gSSR, 31 EST-SSR and 351 DArT markers distributed in 24 linkage groups for a total length of 1,272 cM. Through bioinformatic approaches we have analysed 327 DArT clones to reveal their redundancy, syntenic and functional aspects. The DNA sequences of 174 DArT markers were assembled into a non-redundant set of 60 marker clusters. This explained the generation of clusters in very small chromosome regions across genomes. Of these DArT markers, 61 showed highly significant (Expectation < E-10) BLAST similarity to gene sequences in public databases of model species such as Brachypodium and rice. Based on sequence alignments, the analysis revealed a mosaic gene conservation, with 54 and 72 genes present in rice and Brachypodium species, respectively. Conclusions In the present manuscript we provide a detailed DArT markers characterization and the basis for future efforts in durum wheat map comparing. PMID:24304553

  14. Identification, Characterization, and Structure Analysis of the Cyclic di-AMP-binding PII-like Signal Transduction Protein DarA*

    PubMed Central

    Gundlach, Jan; Dickmanns, Achim; Schröder-Tittmann, Kathrin; Neumann, Piotr; Kaesler, Jan; Kampf, Jan; Herzberg, Christina; Hammer, Elke; Schwede, Frank; Kaever, Volkhard; Tittmann, Kai; Stülke, Jörg; Ficner, Ralf

    2015-01-01

    The cyclic dimeric AMP nucleotide c-di-AMP is an essential second messenger in Bacillus subtilis. We have identified the protein DarA as one of the prominent c-di-AMP receptors in B. subtilis. Crystal structure analysis shows that DarA is highly homologous to PII signal transducer proteins. In contrast to PII proteins, the functionally important B- and T-loops are swapped with respect to their size. DarA is a homotrimer that binds three molecules of c-di-AMP, each in a pocket located between two subunits. We demonstrate that DarA is capable to bind c-di-AMP and with lower affinity cyclic GMP-AMP (3′3′-cGAMP) but not c-di-GMP or 2′3′-cGAMP. Consistently the crystal structure shows that within the ligand-binding pocket only one adenine is highly specifically recognized, whereas the pocket for the other adenine appears to be promiscuous. Comparison with a homologous ligand-free DarA structure reveals that c-di-AMP binding is accompanied by conformational changes of both the fold and the position of the B-loop in DarA. PMID:25433025

  15. Identification, characterization, and structure analysis of the cyclic di-AMP-binding PII-like signal transduction protein DarA.

    PubMed

    Gundlach, Jan; Dickmanns, Achim; Schröder-Tittmann, Kathrin; Neumann, Piotr; Kaesler, Jan; Kampf, Jan; Herzberg, Christina; Hammer, Elke; Schwede, Frank; Kaever, Volkhard; Tittmann, Kai; Stülke, Jörg; Ficner, Ralf

    2015-01-30

    The cyclic dimeric AMP nucleotide c-di-AMP is an essential second messenger in Bacillus subtilis. We have identified the protein DarA as one of the prominent c-di-AMP receptors in B. subtilis. Crystal structure analysis shows that DarA is highly homologous to PII signal transducer proteins. In contrast to PII proteins, the functionally important B- and T-loops are swapped with respect to their size. DarA is a homotrimer that binds three molecules of c-di-AMP, each in a pocket located between two subunits. We demonstrate that DarA is capable to bind c-di-AMP and with lower affinity cyclic GMP-AMP (3'3'-cGAMP) but not c-di-GMP or 2'3'-cGAMP. Consistently the crystal structure shows that within the ligand-binding pocket only one adenine is highly specifically recognized, whereas the pocket for the other adenine appears to be promiscuous. Comparison with a homologous ligand-free DarA structure reveals that c-di-AMP binding is accompanied by conformational changes of both the fold and the position of the B-loop in DarA. PMID:25433025

  16. Automated Detection of Geomorphic Features in LiDAR Point Clouds of Various Spatial Density

    NASA Astrophysics Data System (ADS)

    Dorninger, Peter; Székely, Balázs; Zámolyi, András.; Nothegger, Clemens

    2010-05-01

    LiDAR, also referred to as laser scanning, has proved to be an important tool for topographic data acquisition. Terrestrial laser scanning allows for accurate (several millimeter) and high resolution (several centimeter) data acquisition at distances of up to some hundred meters. By contrast, airborne laser scanning allows for acquiring homogeneous data for large areas, albeit with lower accuracy (decimeter) and resolution (some ten points per square meter) compared to terrestrial laser scanning. Hence, terrestrial laser scanning is preferably used for precise data acquisition of limited areas such as landslides or steep structures, while airborne laser scanning is well suited for the acquisition of topographic data of huge areas or even country wide. Laser scanners acquire more or less homogeneously distributed point clouds. These points represent natural objects like terrain and vegetation and artificial objects like buildings, streets or power lines. Typical products derived from such data are geometric models such as digital surface models representing all natural and artificial objects and digital terrain models representing the geomorphic topography only. As the LiDAR technology evolves, the amount of data produced increases almost exponentially even in smaller projects. This means a considerable challenge for the end user of the data: the experimenter has to have enough knowledge, experience and computer capacity in order to manage the acquired dataset and to derive geomorphologically relevant information from the raw or intermediate data products. Additionally, all this information might need to be integrated with other data like orthophotos. In all theses cases, in general, interactive interpretation is necessary to determine geomorphic structures from such models to achieve effective data reduction. There is little support for the automatic determination of characteristic features and their statistical evaluation. From the lessons learnt from automated

  17. Mapping tropical forest biomass with radar and spaceborne LiDAR: overcoming problems of high biomass and persistent cloud

    NASA Astrophysics Data System (ADS)

    Mitchard, E. T. A.; Saatchi, S. S.; White, L. J. T.; Abernethy, K. A.; Jeffery, K. J.; Lewis, S. L.; Collins, M.; Lefsky, M. A.; Leal, M. E.; Woodhouse, I. H.; Meir, P.

    2011-08-01

    Spatially-explicit maps of aboveground biomass are essential for calculating the losses and gains in forest carbon at a regional t