WorldWideScience

Sample records for notron-gama dar meydanha-ye

  1. (DArT) markers

    Indian Academy of Sciences (India)

    wilt and sterility mosaic disease, etc.) stresses. Despite past. ∗For correspondence. E-mail: r.k.varshney@cgiar.org .... Shi Ying Yang et al. Table 2. Details on 466 polymorphic DArT markers. Female specific. Male specific. Total. 198. 268. Class I. 142. 203. Class II. 27. 16. Others. 29. 49. Mapped. 122. 172. Linkage mapping.

  2. (DArT) markers

    Indian Academy of Sciences (India)

    age groups of both maternal and paternal maps. The segre- gating markers were classified into two classes; for DArT class 1 consensus marker the selection criterion were of very high stringency parameters with clustering settings; Q >. 70; P > 75; call rate > 90, 100% reproducibility, no dis- cordance, and probability > 0.001 ...

  3. LiDAR for data efficiency.

    Science.gov (United States)

    2011-09-30

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

  4. 2015 Puget Sound LiDAR Consortium (PSLC) LiDAR: WA DNR Lands (P2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In June 2014, WSI, a Quantum Spatial Inc. (QSI) company, was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  5. 2014 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Willapa Valley (Delivery 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In January, 2014 WSI, a Quantum Spatial (QSI) company, was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data...

  6. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Saddle Mountain

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In October 2013, WSI, a Quantum Spatial Company (QSI), was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data...

  7. 2015 Puget Sound LiDAR Consortium (PSLC) LiDAR: WA DNR Lands (P1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In June 2014, WSI, a Quantum Spatial Inc. (QSI) company, was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  8. 2011 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Quinault River Basin

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data on the Quinault River Basin survey area for the Puget Sound LiDAR Consortium and...

  9. 2009 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Lewis County, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data for the Lewis County survey area for the Puget Sound LiDAR Consortium. This data...

  10. Infrastructure Investment Protection with LiDAR

    Science.gov (United States)

    2012-10-15

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

  11. Iowa LiDAR Mapping Project

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — This is collection level metadata for LAS and ASCII data files from the statewide Iowa Lidar Project. The Iowa Light Detection and Ranging (LiDAR) Project collects...

  12. Hawaii DAR Dealer Reporting System Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In 2000 January, the Hawaii Division of Aquatic Resources (DAR) implemented a computerized data processing system for fish dealer data collected state-wide. Hawaii...

  13. USGS Atchafalaya 2 LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Atchafalaya Basin project area. The entire survey area for Atchafalaya encompasses approximately...

  14. LiDAR data for the Delta Area of California

    Data.gov (United States)

    California Natural Resource Agency — LiDAR data for the Delta Area of California from the California Department of Water Resources. Bare earth grids from LiDAR.This data is in ESRI Grid format with 2...

  15. LiDAR data for the Delta Area of California

    Data.gov (United States)

    California Department of Resources — LiDAR data for the Delta Area of California from the California Department of Water Resources. Bare earth grids from LiDAR.This data is in ESRI Grid format with 2...

  16. Green vegetable supply in Dar es Salaam

    NARCIS (Netherlands)

    Wegerif, M.C.A.

    2015-01-01

    This article constructs a picture of green vegetable growing and supply in Dar es Salaam by looking at the lives and work of a small trader and an urban farmer. It reveals the importance of a range of distribution and trade networks and the integration of a wider city region, alongside urban and

  17. University of Dar es Salaam Library Journal

    African Journals Online (AJOL)

    The University of Dar es Salaam Library Journal publishes articles on all aspects of library and information science. These include organization and dissemination of information, library education and training, information technology and its application in libraries, book reviews and short communications. Journal Homepage ...

  18. municipal solid waste of dar es salaam

    African Journals Online (AJOL)

    methane yields decreased by 30-50%. The mixed waste category constituting a substrate concentration of 6 g VS [-1. F V was degraded by 65% and gave a yield of 428 ml CH4 per gram VS added. This study concludes that individual fractions of MSW of Dar es salaam city are suitable as feedstocks for biogas digesters.

  19. Excreta Disposal in Dar-es-salaam

    NARCIS (Netherlands)

    Chaggu, E.; Mashouri, D.; Buuren, van J.C.L.; Sanders, W.T.M.; Lettinga, G.

    2002-01-01

    The sociocultural and socioeconomic situation of sanitation in Dar-es-Salaam (Dsm), Tanzania, was studied with explicit emphasis on pit-latrines. Without considering the sociocultural conditions, the so-called best solution might not be the right one. Therefore, in order to achieve the intended

  20. Orienteerumiskaart vs. LiDAR / Marek Karm

    Index Scriptorium Estoniae

    Karm, Marek

    2012-01-01

    Bakalaureusetööst, mille eesmärk oli võrrelda orienteerumiskaardi reljeefi LiDAR-i andmete põhjal saadava reljeefimudeliga ning leida vastus küsimusele, kas o-kaart võib olla kasulik kooste- või kontrollmaterjal mistahes reljeefimudelile

  1. University of Dar es Salaam Library Journal

    African Journals Online (AJOL)

    The University of Dar es Salaam Library Journal publishes articles on all aspects of Library and Information Science. These include organization and dissemination of information, library education and training, information technology and its application in libraries, book reviews and short communications. Authors are in ...

  2. LiDAR utility for natural resource managers

    Science.gov (United States)

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

    2009-01-01

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

  3. 2000 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Kitsap Peninsula, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TerraPoint surveyed and created this data for the Puget Sound LiDAR Consortium under contract. The area surveyed is approximately 1,146 square miles and covers part...

  4. 2005 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Lewis County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint collected Light Detection and Ranging (LiDAR) data for the Lewis County project of 2005. The project site covered approximately 223 square miles, divided...

  5. 2005 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Olympic Peninsula

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint collected Light Detection and Ranging (LiDAR) data for the Olympic Peninsula project of 2005, totaling approximately 114.59 sq mi: 24.5 for Clallam...

  6. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Nooksack

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In July 2012, WSI (Watershed Sciences, Inc.) was contracted by the Puget Sound LiDARConsortium (PSLC) to collect Light Detection and Ranging (LiDAR) data on a...

  7. 2005 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: North Puget Sound Lowlands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint collected Light Detection and Ranging (LiDAR) data contributing to the Puget Sound Lowlands project of 2005. Arlington, City of Snohomish, Snohomish...

  8. 2012 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Upper Naches River, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data of the Upper Naches River Valley and Nile Slide area of interest on September 30th,...

  9. 2003 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Snohomish County, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TerraPoint surveyed and created this data for the Puget Sound LiDAR Consortium under contract. The area surveyed is approximately 167 square miles and covers a...

  10. 2009 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Snohomish River Estuary

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) co-acquired Light Detection and Ranging (LiDAR) data and Truecolor Orthophotographs of the Snohomish River Estuary, WA on July 20 &...

  11. 2009 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Douglas Co.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data of the Douglas County PUD area of interest (AOI) east of Wenatchee, WA on May 2nd -...

  12. 2014 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Cedar River Watershed (Delivery 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In September 2013, WSI, a Quantum Spatial company (QSI), was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  13. 2012 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Quinault River Watershed, Washington (Delivery 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data on the Quinault watershed survey area for the Puget Sound LiDAR Consortium. This...

  14. 2014 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Cedar River Watershed (Delivery 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In September 2013, WSI, a Quantum Spatial company (QSI), was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  15. Novel Methods for Measuring LiDAR

    Science.gov (United States)

    Ayrey, E.; Hayes, D. J.; Fraver, S.; Weiskittel, A.; Cook, B.; Kershaw, J.

    2017-12-01

    The estimation of forest biometrics from airborne LiDAR data has become invaluable for quantifying forest carbon stocks, forest and wildlife ecology research, and sustainable forest management. The area-based approach is arguably the most common method for developing enhanced forest inventories from LiDAR. It involves taking a series of vertical height measurements of the point cloud, then using those measurements with field measured data to develop predictive models. Unfortunately, there is considerable variation in methodology for collecting point cloud data, which can vary in pulse density, seasonality, canopy penetrability, and instrument specifications. Today there exists a wealth of public LiDAR data, however the variation in acquisition parameters makes forest inventory prediction by traditional means unreliable across the different datasets. The goal of this project is to test a series of novel point cloud measurements developed along a conceptual spectrum of human interpretability, and then to use the best measurements to develop regional enhanced forest inventories on Northern New England's and Atlantic Canada's public LiDAR. Similarly to a field-based inventory, individual tree crowns are being segmented, and summary statistics are being used as covariates. Established competition and structural indices are being generated using each tree's relationship to one another, whilst existing allometric equations are being used to estimate diameter and biomass of each tree measured in the LiDAR. Novel metrics measuring light interception, clusteredness, and rugosity are also being measured as predictors. On the other end of the human interpretability spectrum, convolutional neural networks are being employed to directly measure both the canopy height model, and the point clouds by scanning each using two and three dimensional kernals trained to identify features useful for predicting biological attributes such as biomass. Predictive models will be trained and

  16. LiDAR Application for WInd Energy Efficiency : Final report

    NARCIS (Netherlands)

    Boorsma, K; Wagenaar, J.W.; Savenije, F.J.; Boquet, M.; Bierbooms, W.A.A.M.; Giyanani, A.H.; Rutteman, R.

    2016-01-01

    ECN with its partners TU DelŌ, Avent LiDAR Technologies and XEMC Darwind executed the four-year TKI Wind op Zee project LAWINE (LiDAR ApplicaƟon for WInd Energy Efficiency). In this project the applica Ɵon of LiDAR technology has been developed and validated so that it can be used to improve the

  17. 2004 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Portland, Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The all returns ASCII files contain the X,Y,Z values of all the LiDAR returns collected during the survey mission. In addition each return also has a time stamp,...

  18. 'Dar' + gerund in Ecuadorian Highland Spanish: contact-induced grammaticalization?

    NARCIS (Netherlands)

    Olbertz, H.

    2008-01-01

    The benefactive construction dar + gerund is used in the North Andean region only and is unknown elsewhere in the Spanish-speaking world. Based on the analysis of spontaneous data from Ecuadorian Highland Spanish, this paper provides a linguististic description of dar + gerund and of the social and

  19. of Sediment Deposition into the Dar es Salaam Harbour

    African Journals Online (AJOL)

    The University of Dar es Salaam, Institute of Marine Sciences, P. O. Box 668 Zanzibar, Tanzania. Key words: Dar es Salaam harbour, sediment deposition, entrance channel. Abstract: The ..... Harbour Transportation, Fishing Ports, Sediment. Transport, Geomorphology, Inlets, and Dredging. Gulf Publishing Company, Book ...

  20. Liquid waste management: The case of Bahir Dar, Ethiopia ...

    African Journals Online (AJOL)

    Background: Human beings pollute the environment with their industrial and domestic wastes. In Bahir Dar Town there is no conventional municipal waste water collection and treatment system. Objective: The aim of this study was to describe the liquid waste disposal practices of the residents of Bahir Dar Town and to ...

  1. 2006 OSIP OGRIP: Upland Counties LiDAR Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2006 OSIP digital LiDAR data was collected during the months of March and May (leaf-off conditions). The LiDAR covers the entire land area of the northern tier...

  2. Liquid waste management: The case of Bahir Dar, Ethiopia

    African Journals Online (AJOL)

    admin

    Abstract. Background: Human beings pollute the environment with their industrial and domestic wastes. In Bahir Dar Town there is no conventional municipal waste water collection and treatment system. Objective: The aim of this study was to describe the liquid waste disposal practices of the residents of Bahir Dar Town.

  3. Assessing LiDAR elevation data for KDOT applications.

    Science.gov (United States)

    2013-02-01

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

  4. Analysis of inflow parameters using LiDARs

    NARCIS (Netherlands)

    Giyanani, A.H.; Bierbooms, W.A.A.M.; Van Bussel, G.J.W.

    2014-01-01

    Remote sensing of the atmospheric variables with the use of LiDAR is a relatively new technique for wind resource assessment and oncoming wind prediction in wind energy. The validation of LiDAR measurements and comparisons with other sensing elements thus, is of high importance for further

  5. Object Classification Using Airborne Multispectral LiDAR Data

    Directory of Open Access Journals (Sweden)

    PAN Suoyan

    2018-02-01

    Full Text Available Airborne multispectral LiDAR system,which obtains surface geometry and spectral data of objects,simultaneously,has become a fast effective,large-scale spatial data acquisition method.Multispectral LiDAR data are characteristics of completeness and consistency of spectrum and spatial geometric information.Support vector machine (SVM,a machine learning method,is capable of classifying objects based on small samples.Therefore,by means of SVM,this paper performs land cover classification using multispectral LiDAR data. First,all independent point cloud with different wavelengths are merged into a single point cloud,where each pixel contains the three-wavelength spectral information.Next,the merged point cloud is converted into range and intensity images.Finally,land-cover classification is performed by means of SVM.All experiments were conducted on the Optech Titan multispectral LiDAR data,containing three individual point cloud collected by 532 nm,1024 nm,and 1550 nm laser beams.Experimental results demonstrate that ①compared to traditional single-wavelength LiDAR data,multispectral LiDAR data provide a promising solution to land use and land cover applications;②SVM is a feasible method for land cover classification of multispectral LiDAR data.

  6. TENSOR MODELING BASED FOR AIRBORNE LiDAR DATA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    N. Li

    2016-06-01

    Full Text Available 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.

  7. No sólo dar, sino darse

    OpenAIRE

    Rodríguez, Pedro

    2012-01-01

    El amor es darse, decimos. El que ama «no se conforma con dar: se da». ¿Pero se puede dar sin recibir? ¿Por qué languidece el amor, o incluso muere, cuando se da sin recibir o cuando se recibe sin dar? ¿No es necesario que el amor sea correspondido? Haremos aquí una consideración teológica sobre esta triple cuestión, en referencia particular al amor matrimonial.

  8. 47 CFR 25.401 - Satellite DARS applications subject to competitive bidding.

    Science.gov (United States)

    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 DARS...

  9. Elevation - LiDAR Survey Minnehaha Creek, MN Watershed

    Data.gov (United States)

    Army Corps of Engineers, Department of the Army, Department of Defense — LiDAR Bare-Earth Grid - Minnehaha Creek Watershed District. The Minnehaha Creek watershed is located primarily in Hennepin County, Minnesota. The watershed covers...

  10. Dar es Salaam Land Use and Informal Settlement Data Set

    Data.gov (United States)

    National Aeronautics and Space Administration — The Dar es Salaam Land Use and Informal Settlement Data Set represents urban land use and consolidation of informal settlements for the years 1982, 1992, 1998, and...

  11. 2009 PSLC-USGS Topographic LiDAR: Wenatchee

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data of the Wenatchee USGS area of interest (AOI) east of Wenatchee, WA on May 1nd - May...

  12. Connecticut Statewide LiDAR 2016 - Blocks 1-7

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata record describes the Classified Point Cloud (LAS) for the 2016 Connecticut LiDAR project covering approximately 5240 square miles in seven blocks. The...

  13. LiDAR (Terrain), THURSTON COUNTY, WASHINGTON, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Fugro EarthData Company furnished the collection, processing, and development of LiDAR for 825 square miles in Washington (805 square miles of Thurston County and 20...

  14. LiDAR error estimation with WAsP engineering

    DEFF Research Database (Denmark)

    Bingöl, Ferhat; Mann, Jakob; Foussekis, D.

    2008-01-01

    The LiDAR measurements, vertical wind profile in any height between 10 to 150m, are based on assumption that the measured wind is a product of a homogenous wind. In reality there are many factors affecting the wind on each measurement point which the terrain plays the main role. To model LiDAR me...... data is compared with the model results. The model results are acceptable and very close for one site while the more complex one is returning higher errors at higher positions and in some wind directions.......DAR measurements and predict possible error in different wind directions for a certain terrain we have analyzed two experiment data sets from Greece. In both sites LiDAR and met. mast data have been collected and the same conditions are simulated with Riso/DTU software, WAsP Engineering 2.0. Finally measurement...

  15. Shipborne LiDAR system for coastal change monitoring

    Science.gov (United States)

    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.

  16. Extraction of Rooftops from LiDAR and Multispectral Imagery

    OpenAIRE

    Kim, Angela M.; Kruse, Fred A.; Olsen, Richard C.; Clasen, Chris C.

    2012-01-01

    Imaging and Applied Optics Technical Digest, 2012 A rooftop extraction scheme based on statistical analysis of the LiDAR point cloud is presented. Spectral data are incorporated to reduce false alarms due to vegetation and to provide spectral discrimination of rooftop materials. This research was partially supported by the Science and Technology Directorate, USA Department of Homeland Security (DHS). The LiDAR data were provided by the Association of Monterey Bay Area Governments (AM...

  17. 2012 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Chehalis River Watershed Area, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data for the Chehalis River Watershed study area on January 28th, February 2nd-7th,...

  18. 2002 Puget Sound LiDAR Consortium (PSLC) Unclassified Topographic LiDAR: Puget Sound Lowlands Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TerraPoint surveyed and created this data for the Puget Sound LiDAR Consortium under contract. The area surveyed is approximately 730 square miles and covers the...

  19. 2006 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Eastern Washington and River Corridors

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data in eastern Washington, eastern Oregon, and southern Canada in October and November,...

  20. 2012-2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Hoh River Watershed, Washington (Deliveries 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data on the Hoh River watershed survey area for the Puget Sound LiDAR Consortium and the...

  1. Agrotóxico: que nome dar?

    Directory of Open Access Journals (Sweden)

    Márcia Gomide

    Full Text Available Os trabalhadores, de um modo geral, estão sempre expostos a maiores ou menores intensidades de risco. Os agricultores, em particular, também estão expostos e de forma bastante estabelecida. Contudo, trabalhos têm mostrado que existe um código coletivo de proteção para lhes permitir dar continuidade às suas atividades, uma vez que, em sua maioria, os próprios donos do cultivo fazem parte do processo produtivo e, portanto, precisam garantir a sua safra aplicando os agrotóxicos. Este trabalho apresenta uma pesquisa desenvolvida com agricultores de dois municípios do sudeste do Piauí, utilizando uma abordagem qualitativa, com o intuito de compreender os mecanismos de proteção destes agricultores com a sua atividade. Os resultados apontaram para práticas defensivas tais como consumo de bebida alcoólica, a sublocação do serviço aos mais jovens e a existência de um certo grau de compreensão do risco à saúde com a utilização dos agrotóxicos. A partir daí, se discute a importância da denominação dada ao agrotóxico, como um fator de proteção que deveria ser mais valorizado para maximizar a proteção do agricultor, em vez de se manter a estratégia de aumento de informação e controle de EPI (Equipamento de Proteção Individual.

  2. LiDAR Vegetation Investigation and Signature Analysis System (LVISA)

    Science.gov (United States)

    Höfle, Bernhard; Koenig, Kristina; Griesbaum, Luisa; Kiefer, Andreas; Hämmerle, Martin; Eitel, Jan; Koma, Zsófia

    2015-04-01

    Our physical environment undergoes constant changes in space and time with strongly varying triggers, frequencies, and magnitudes. Monitoring these environmental changes is crucial to improve our scientific understanding of complex human-environmental interactions and helps us to respond to environmental change by adaptation or mitigation. The three-dimensional (3D) description of the Earth surface features and the detailed monitoring of surface processes using 3D spatial data have gained increasing attention within the last decades, such as in climate change research (e.g., glacier retreat), carbon sequestration (e.g., forest biomass monitoring), precision agriculture and natural hazard management. In all those areas, 3D data have helped to improve our process understanding by allowing quantifying the structural properties of earth surface features and their changes over time. This advancement has been fostered by technological developments and increased availability of 3D sensing systems. In particular, LiDAR (light detection and ranging) technology, also referred to as laser scanning, has made significant progress and has evolved into an operational tool in environmental research and geosciences. The main result of LiDAR measurements is a highly spatially resolved 3D point cloud. Each point within the LiDAR point cloud has a XYZ coordinate associated with it and often additional information such as the strength of the returned backscatter. The point cloud provided by LiDAR contains rich geospatial, structural, and potentially biochemical information about the surveyed objects. To deal with the inherently unorganized datasets and the large data volume (frequently millions of XYZ coordinates) of LiDAR datasets, a multitude of algorithms for automatic 3D object detection (e.g., of single trees) and physical surface description (e.g., biomass) have been developed. However, so far the exchange of datasets and approaches (i.e., extraction algorithms) among LiDAR users

  3. Visual-LiDAR Odometry Aided by Reduced IMU

    Directory of Open Access Journals (Sweden)

    Yashar Balazadegan Sarvrood

    2016-01-01

    Full Text Available This paper proposes a method for combining stereo visual odometry, Light Detection And Ranging (LiDAR odometry and reduced Inertial Measurement Unit (IMU including two horizontal accelerometers and one vertical gyro. The proposed method starts with stereo visual odometry to estimate six Degree of Freedom (DoF ego motion to register the point clouds from previous epoch to the current epoch. Then, Generalized Iterative Closest Point (GICP algorithm refines the motion estimation. Afterwards, forward velocity and Azimuth obtained by visual-LiDAR odometer are integrated with reduced IMU outputs in an Extended Kalman Filter (EKF to provide final navigation solution. In this paper, datasets from KITTI (Karlsruhe Institute of Technology and Toyota technological Institute were used to compare stereo visual odometry, integrated stereo visual odometry and reduced IMU, stereo visual-LiDAR odometry and integrated stereo visual-LiDAR odometry and reduced IMU. Integrated stereo visual-LiDAR odometry and reduced IMU outperforms other methods in urban areas with buildings around. Moreover, this method outperforms simulated Reduced Inertial Sensor System (RISS, which uses simulated wheel odometer and reduced IMU. KITTI datasets do not include wheel odometry data. Integrated RTK (Real Time Kinematic GPS (Global Positioning System and IMU was replaced by wheel odometer to simulate the response of RISS method. Visual Odometry (VO-LiDAR is not only more accurate than wheel odometer, but it also provides azimuth aiding to vertical gyro resulting in a more reliable and accurate system. To develop low-cost systems, it would be a good option to use two cameras plus reduced IMU. The cost of such a system will be reduced than using full tactical MEMS (Micro-Electro-Mechanical Sensor based IMUs because two cameras are cheaper than full tactical MEMS based IMUs. The results indicate that integrated stereo visual-LiDAR odometry and reduced IMU can achieve accuracy at the

  4. UAS TOPOGRAPHIC MAPPING WITH VELODYNE LiDAR SENSOR

    Directory of Open Access Journals (Sweden)

    G. Jozkow

    2016-06-01

    Full Text Available 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.

  5. A Study on Factors Affecting Airborne LiDAR Penetration

    Directory of Open Access Journals (Sweden)

    Wei-Chen Hsu

    2015-01-01

    Full Text Available This study uses data from different periods, areas and parameters of airborne LiDAR (light detection and ranging surveys to understand the factors that influence airborne LiDAR penetration rate. A discussion is presented on the relationships between these factors and LiDAR penetration rate. The results show that the flight height above ground level (AGL does not have any relationship with the penetration rate. There are some factors that should have larger influence. For example, the laser is affected by a wet ground surface by reducing the number of return echoes. The field of view (FOV has a slightly negative correlation with the penetration rate, which indicates that the laser incidence angle close to zero should achieve the best penetration. The vegetation cover rate also shows a negative correlation with the penetration rate, thus bare ground and reduced vegetation in the aftermath of a typhoon also cause high penetration rate. More return echoes could be extracted from the full-waveform system, thereby effectively improving the penetration rate. This study shows that full-waveform LiDAR is an effective method for increasing the number of surface reflected echoes. This study suggests avoiding LiDAR survey employment directly following precipitation to prevent laser echo reduction.

  6. Automated Probabilistic LiDAR Swath Registration

    Science.gov (United States)

    Jalobeanu, A.; Gonçalves, G. R.

    2014-12-01

    We recently developed a new point cloud registration algorithm. Compared to Iterated Closest Point (ICP) techniques, it is robust to noise and outliers, and easier to use, as it is less sensitive to initial conditions. It minimizes the entropy of the joint point cloud (including intensity attributes to help register areas with poor relief), uses a voxel space and B-Spline interpolation to accelerate computation. A natural application of registration is swath alignment in airborne light detection and ranging (LiDAR). Indeed, due to uncertainty in the inertial navigation system (INS), attitude angles are subject to time-dependent errors. Such errors can be understood as a sum of three terms: 1) a global term, or boresight error, which can be addressed using several existing techniques; 2) a low-frequency term, which is modeled as a constant attitude error for regions several hundred meters along-track; 3) a high-frequency term, responsible for corduroy artifacts (not addressed here). We propose to use the new registration algorithm to correct the low-frequency attitude variations. Relative geometric errors are significantly reduced, as pairs of swaths are registered onto each other local corrections. Absolute geometric errors are reduced during a second step, by applying all the corrections together to the entire dataset. We used a test area of 200 km2 in Portugal, with a density of 3-4 pts/m2. The point clouds were derived from waveform data, and include predictive range uncertainties estimated within a Bayesian framework. The data collection was supported by FCT and FEDER as part of the AutoProbaDTM research project (2009-2012). Modeling and reducing geometric error helps build consistent uncertainty maps. After correction, residual errors are taken into account in the final 3D error budget. For gridded elevation models a vertical uncertainty map is computed. Finally, it is possible to use the inter-swath registration parameters to estimate the distribution of

  7. Peregrinaciones parisinas: Rubén Darío

    OpenAIRE

    Colombi, Beatriz

    1997-01-01

    Hacia 1900 se nuclea en París un grupo de corresponsales latinoamericanos conformando una suerte de enclave que reúne a figuras como Rubén Darío, Manuel Ugarte, Amado Nervo o Enrique Gómez Carrillo. Desde sus respectivas columnas estos cronistas construyen imágenes del mundo moderno atravesadas por el conflicto de pertenencia y marginalidad respecto al mismo. Este trabajo analiza las entregas que Rubén Darío escribe para La Nación de Buenos Aires durante la Feria Internacional de Paris de 190...

  8. Adolescent Girls with illegally Induced Abortion in Dar es Salaam

    DEFF Research Database (Denmark)

    Rasch, V; Silberschmidt, Margrethe; Mchumvu, Y

    2000-01-01

    This article reports on a study of induced abortion among adolescent girls in Dar es Salaam, Tanzania, who were admitted to a district hospital in Dar es Salaam because of an illegally induced abortion in 1997. In the quantitative part of the study, 197 teenage girls (aged 14-19) were asked...... contraception or condoms though they were also at risk of STDs and HIV. These girls were getting pregnant expecting their boyfriends to marry them, or because they did not think they could become pregnant or failed to use contraception correctly. Most adolescent girls are not aware of the 1994 Tanzanian policy...... adolescent girls....

  9. 2011 U.S. Geological Survey (USGS) Topographic LiDAR: Louisiana Region 1

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Louisiana Region 1 LiDAR ARRA Task Order LiDAR Data Acquisition and Processing Production Task- Vermillion, Iberia, St. Mary, Terrebonne, and Lafourche...

  10. 2011 U.S. Geological Survey (USGS) Topographic LiDAR: Louisiana Region 2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Louisiana Region 2 LiDAR ARRA Task Order LiDAR Data Acquisition and Processing Production Task- Orleans, Plaquemines, St. Bernard, St. Tammany Parishes,...

  11. 2007 US Army Corps of Engineers (USACE), Jacksonville District US Virgin Islands LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) bare-earth classified LAS dataset is a topographic survey conducted for the USACE USVI LiDAR Project. These data were...

  12. 2004 Federal Emergency Management Agency (FEMA) Bare Earth Topographic LiDAR: Connecticut River

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. The LiDAR files were converted from .PTS format to LAS...

  13. Study on environmental test technology of LiDAR used for vehicle

    Science.gov (United States)

    Wang, Yi; Yang, Jianfeng; Ou, Yong

    2018-03-01

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

  14. Presentation and management of maxillofacial trauma in Dar es ...

    African Journals Online (AJOL)

    Setting: Department of Oral and Maxillofacial Surgery, Muhimbili National Hospital (MNH), Dar es Salaam, Tanzania. ... age, gender, length of interval between injury and presentation to the hospital, aetiology, pattern of soft tissue injury and fractures, therapy, co-morbidity, complications and number of hospitalisation days.

  15. Feeding Dar es Salaam: a symbiotic food system perspective

    NARCIS (Netherlands)

    Wegerif, Marc C.A.

    2017-01-01

    This thesis is a sociological analysis of the agri-food system that feeds most of the over four and a half million residents of the fast-growing city of Dar es Salaam in Tanzania. It is based on qualitative research that has generated a picture of the food system that supplies the important foods

  16. SURVEY OF WOODY FLORA AND FAUNA OF THE BAHIR DAR ...

    African Journals Online (AJOL)

    Abstract: The aim of this project was to survey the flora and fauna of the main campus of. Bahir Dar Vniversity. It was necessary because the university campus is relatively well rehabilitated and it is very important that the composition of the vegetation, the regeneration capacity of the vegetation and the importance of the tree ...

  17. Suicidal ideation among school-attending adolescents in Dar es ...

    African Journals Online (AJOL)

    Background: Suicidal ideation is an understudied risk factor for suicidal intent. The present study investigates the patterns and risk factors for suicidal ideation among a sample of school-attending adolescents in Dar es Salaam, Tanzania. Methods: This study examined secondary data collected in 2006 through the Global ...

  18. Aloe; Beyond use as cosmetics | Pili | Dar Es Salaam Medical ...

    African Journals Online (AJOL)

    Dar Es Salaam Medical Students' Journal. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 15, No 1 (2008) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. Aloe; Beyond use as cosmetics. K Pili. Abstract.

  19. Nitrogen concentration estimation with hyperspectral LiDAR

    Directory of Open Access Journals (Sweden)

    O. Nevalainen

    2013-10-01

    Full Text Available Agricultural lands have strong impact on global carbon dynamics and nitrogen availability. Monitoring changes in agricultural lands require more efficient and accurate methods. The first prototype of a full waveform hyperspectral Light Detection and Ranging (LiDAR instrument has been developed at the Finnish Geodetic Institute (FGI. The instrument efficiently combines the benefits of passive and active remote sensing sensors. It is able to produce 3D point clouds with spectral information included for every point which offers great potential in the field of remote sensing of environment. This study investigates the performance of the hyperspectral LiDAR instrument in nitrogen estimation. The investigation was conducted by finding vegetation indices sensitive to nitrogen concentration using hyperspectral LiDAR data and validating their performance in nitrogen estimation. The nitrogen estimation was performed by calculating 28 published vegetation indices to ten oat samples grown in different fertilization conditions. Reference data was acquired by laboratory nitrogen concentration analysis. The performance of the indices in nitrogen estimation was determined by linear regression and leave-one-out cross-validation. The results indicate that the hyperspectral LiDAR instrument holds a good capability to estimate plant biochemical parameters such as nitrogen concentration. The instrument holds much potential in various environmental applications and provides a significant improvement to the remote sensing of environment.

  20. Aggression; a Paradoxical pathology of the mind | Kitapondya | Dar ...

    African Journals Online (AJOL)

    Dar Es Salaam Medical Students' Journal. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 15, No 1 (2008) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. Aggression; a Paradoxical pathology of the mind.

  1. Knowledge, attitudes and practice of Bahir Dar University ...

    African Journals Online (AJOL)

    Nowadays environmental problems have become issues of great concern to many parties. However, many people in Ethiopia seem to have low level of environmental knowledge. This study examined environmental awareness and attitudes of Bahir Dar University students. Data were collected from 523 respondents using ...

  2. Assessment on Vulnerable Youths Integration to Dar es Salaam ...

    African Journals Online (AJOL)

    The present study assessed the possibility of integrating vulnerable youths to complement government and community based efforts in improving the existing municipal solid waste management crisis facing Dar es Salaam City using a case study of Kinondoni Municipality. The study was motivated by the fact that, many ...

  3. Dar es Salaam City and Challenges in Solid Waste Management ...

    African Journals Online (AJOL)

    The focus of this paper is on challenges facing solid waste management in. Manzese and Sinza wards, in Dar es Salaam city. In this paper different ways of generating, disposing waste and the associated problems are surveyed. About 102 people were interviewed. Different methods were employed in data collection which ...

  4. Accessibility, Congestion and Travel Delays in Dar es Salaam

    DEFF Research Database (Denmark)

    Melbye, Dea Christine; Møller-Jensen, Lasse; Andreasen, Manja Hoppe

    2015-01-01

    on to present a review of research into travel speed levels and congestion in Dar es Salaam. A set of city-wide maps of accessibility and delay levels are constructed based on available speed data and road network data obtained from the OpenStreetMap project and the findings are discussed with respect...

  5. Heavy Metals and Organic Pollutants in Sediments of Dar es ...

    African Journals Online (AJOL)

    The Florida criteria (MacDonald 1993) for assessment of pollution of tropical marine sediments was adopted in oredr to evaluate the extent of pollution in Dar es Salaam harbour sediments. The Florida criteria is one of the established references for sediment quality assessment. Heavy metals that had concentrations above ...

  6. Engineering geological mapping of Dar es Salaam city, Tanzania ...

    African Journals Online (AJOL)

    Two basic maps were prepared, namely, geomorphological and geological map depicts the spatial extent of the Neogene geological formations. Three distinct sandstone terraces could be distinguished in Dar es Salaam region at 0-15 m and 30 – 40 m above sea level. The terraces comprised sandstones fringed by coral ...

  7. Charcoal Supply In Dar Es Salaam City, Tanzania | Malimbwi ...

    African Journals Online (AJOL)

    In Tanzania, charcoal is the primary source of energy particularly in urban areas. Dar es Salaam, being the largest urban center in the country, is also the largest consumer of charcoal. Assuming that all charcoal transported in the city is consumed, an investigation to estimate the amount of charcoal supplied daily was ...

  8. International Journal of Science and Technology (STECH) Bahir Dar ...

    African Journals Online (AJOL)

    Nneka Umera-Okeke

    International Journal of Science and Technology. (STECH). Bahir Dar- Ethiopia. Vol. 6 (1) ... Logic studies the relation of propositions in order to ascertain the relation of entailment, which ultimately leads to the relation of truth ...... Filosofika: University of. Port Harcourt Journal of Philosophy and Public Affairs. 1.1 (2014): 96 –.

  9. Community violence in Dar es Salaam, Tanzania: A mixed methods ...

    African Journals Online (AJOL)

    Most homicide deaths in Dar es Salaam, Tanzania (DSM) are a result of violence arising from within the community. This type of violence is commonly called, by perpetrators and victims, “mob justice”. Unilateral non-state collective violence can take four forms: lynching, vigilantism, rioting, and terrorism. The purpose of this ...

  10. Knowledge, Attitude and Practice of Commercial Drivers in Dar es ...

    African Journals Online (AJOL)

    Purpose: The objective of this study was, first, to assess the knowledge, attitude and practice of commercial drivers in Dar es Salaam with regard to medicines that impair driving, and second, to evaluate the adequacy of antihistamine label information. Methods: Drivers were interviewed using a questionnaire after obtaining ...

  11. Aloe; Beyond use as cosmetics | Pili | Dar Es Salaam Medical ...

    African Journals Online (AJOL)

    Dar Es Salaam Medical Students' Journal. Journal Home · ABOUT · Advanced Search · Current Issue · Archives · Journal Home > Vol 15, No 1 (2008) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register · Download this PDF file. The PDF file you selected should load ...

  12. Performance Analysis of Throughput at Bahir Dar University LAN ...

    African Journals Online (AJOL)

    Computer scientists and network users have discovered that standard TCP does not perform well in high bandwidth delay environments. As a model, the Local Area Network of Bahir Dar University Engineering Faculty was tested and reported. . In this paper, we explore the challenges of achieving high throughput over real ...

  13. Coastal Marine Pollution in Dar es Salaam (Tanzania) relative to ...

    African Journals Online (AJOL)

    Abstract—Pollution surveys were undertaken during 2007 and 2008 in the coastal marine environment of Dar es Salaam and the remote Ras Dege. Creek. The objective was to determine the levels of microbial contamination, heavy metals and persistent organic pollutants and compare these with the recommended ...

  14. Case Report: Congenital Biliary Atresia | Gulamabbas | Dar Es ...

    African Journals Online (AJOL)

    Dar Es Salaam Medical Students' Journal. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 15, No 1 (2008) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. Case Report: Congenital Biliary Atresia.

  15. Case Report: Congenital Biliary Atresia | Gulamabbas | Dar Es ...

    African Journals Online (AJOL)

    Dar Es Salaam Medical Students' Journal. Journal Home · ABOUT · Advanced Search · Current Issue · Archives · Journal Home > Vol 15, No 1 (2008) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register · Download this PDF file. The PDF file you selected should load ...

  16. Modeling low-height vegetation with airborne LiDAR

    Science.gov (United States)

    Low-height vegetation, common in semiarid regions, is difficult to characterize with LiDAR (Light Detection and Ranging) due to similarities, in time and space, of the point returns of vegetation and ground. Other complications may occur due to the low-height vegetation structural characteristics a...

  17. Coastal Marine Pollution in Dar es Salaam (Tanzania) relative to ...

    African Journals Online (AJOL)

    Pollution surveys were undertaken during 2007 and 2008 in the coastal marine environment of Dar es Salaam and the remote Ras Dege Creek. The objective was to determine the levels of microbial contamination, heavy metals and persistent organic pollutants and compare these with the recommended environmental ...

  18. Quantifying Ladder Fuels: A New Approach Using LiDAR

    Science.gov (United States)

    Heather Kramer; Brandon Collins; Maggi Kelly; Scott Stephens

    2014-01-01

    We investigated the relationship between LiDAR and ladder fuels in the northern Sierra Nevada, California USA. Ladder fuels are often targeted in hazardous fuel reduction treatments due to their role in propagating fire from the forest floor to tree crowns. Despite their importance, ladder fuels are difficult to quantify. One common approach is to calculate canopy base...

  19. 2011 USGS Topographic LiDAR: Suwannee River Expansion

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — USGS Task Order No. G10PD00236 USGS Contract No. G10PC00093 The Light Detection and Ranging (LiDAR) dataset is a survey of the Suwannee River Expansion in...

  20. History of diagnosis of cardiovascular diseases | Lubinza | Dar Es ...

    African Journals Online (AJOL)

    Dar Es Salaam Medical Students' Journal. Journal Home · ABOUT · Advanced Search · Current Issue · Archives · Journal Home > Vol 19, No 2 (2012) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register · Download this PDF file. The PDF file you selected should load ...

  1. Relationship between LiDAR-derived forest canopy height and Landsat images

    Science.gov (United States)

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

    2010-01-01

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

  2. Demystifying LiDAR technologies for temperate rainforest in the Pacific Northwest

    Science.gov (United States)

    Rhonda Mazza; Demetrios Gatziolis

    2013-01-01

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

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Science.gov (United States)

    Jeffrey S. Evans; Andrew T. Hudak

    2007-01-01

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

  5. 2005 Mississippi Merged LiDAR Data (2005 LiDAR data merged with 2005 Post-Katrina LiDAR data to create a bare-earth product for flood plain mapping in coastal Mississippi).

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Pre- and post-hurricane Katrina LiDAR datasets of Hancock, Harrison, and Jackson Counties, MS, were merged into a seamless coverage by URS. The pre-Katrina LiDAR...

  6. Rockfall hazard analysis using LiDAR and spatial modeling

    Science.gov (United States)

    Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho

    2010-05-01

    Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.

  7. Development of a regional LiDAR field plot strategy for Oregon and Washington

    Science.gov (United States)

    Arvind Bhuta; Leah. Rathbun

    2015-01-01

    The National Forest System (NFS) Pacific Northwest Region (R6) has been flying LiDAR on a per project basis. Additional field data was also collected in situ to many of these LiDAR projects to aid in the development of predictive models and estimate values which are unattainable through LiDAR data alone (e.g. species composition, tree volume, and downed woody material...

  8. Peregrinaciones parisinas: Rubén Darío

    Directory of Open Access Journals (Sweden)

    Beatriz Colombi

    1996-11-01

    Full Text Available Hacia 1900 se nuclea en París un grupo de corresponsales latinoamericanos conformando una suerte de enclave que reúne a figuras como Rubén Darío, Manuel Ugarte, Amado Nervo o Enrique Gómez Carrillo. Desde sus respectivas columnas estos cronistas construyen imágenes del mundo moderno atravesadas por el conflicto de pertenencia y marginalidad respecto al mismo. Este trabajo analiza las entregas que Rubén Darío escribe para La Nación de Buenos Aires durante la Feria Internacional de Paris de 1900, en relación con su contexto discursivo. En la enunciación de estas crónicas se alternan pasajes donde prima la superficialidad de la crónica elegante parisina con otras secciones argumentativas que dan cuenta de los desplazamientos de este sujeto entre el 'chroniqueur' y el intelectual que interviene -con la autoridad que le otorga su liderazgo estético- en el campo de los sucesos políticos, desmoronando cualquier 'fetichización' del espectáculo. Darío trama en su crónica la línea 'ondulante' de su prosa de artista con la línea 'informativa' de su tarea de diarista, imponiendo una marca 'modern style' a su escritura, que privilegia imágenes donde se fusionan elementos de ámbitos dispares; también se contamina de la retórica del acontecimiento moderno, en una hibridez propia del efecto sumativo de ese vasto mercado. Las crónicas, reunidas luego en Peregrinaciones de 1901, señalan también el pasaje entre el gran mercado cultural y el pequeño mercado estético, en una posición anfibia propia de esta textualidad

  9. LiDAR remote sensing applied to forest resources assessment

    OpenAIRE

    Fernández-Landa, Alfredo

    2016-01-01

    Disponer de información precisa y actualizada de inventario forestal es una pieza clave para mejorar la gestión forestal sostenible y para proponer y evaluar políticas de conservación de bosques que permitan la reducción de emisiones de carbono debidas a la deforestación y degradación forestal (REDD). En este sentido, la tecnología LiDAR ha demostrado ser una herramienta perfecta para caracterizar y estimar de forma continua y en áreas extensas la estructura del bosque y las principales vari...

  10. Bovine Pulmonary Tuberculosis At Bahir Dar Municipality Abattoir ...

    African Journals Online (AJOL)

    Une étude transversale a été menée de décembre 2005 à juin 2006 pour déterminer la prévalence de la tuberculose bovine chez 1441 bovins abattus et aussi pour valider la qualité de diagnostic de l'inspection de routine à l'abattoir de la municipalité de Bahir Dar, dans le nord-ouest de l'Ethiopie. On a aussi comparé la ...

  11. Automatic building extraction using LiDAR and aerial photographs

    Directory of Open Access Journals (Sweden)

    Melis Uzar

    Full Text Available This paper presents an automatic building extraction approach using LiDAR data and aerial photographs from a multi-sensor system positioned at the same platform. The automatic building extraction approach consists of segmentation, analysis and classification steps based on object-based image analysis. The chessboard, contrast split and multi-resolution segmentation methods were used in the segmentation step. The determined object primitives in segmentation, such as scale parameter, shape, completeness, brightness, and statistical parameters, were used to determine threshold values for classification in the analysis step. The rule-based classification was carried out with defined decision rules based on determined object primitives and fuzzy rules. In this study, hierarchical classification was preferred. First, the vegetation and ground classes were generated; the building class was then extracted. The NDVI, slope and Hough images were generated and used to avoid confusing the building class with other classes. The intensity images generated from the LiDAR data and morphological operations were utilized to improve the accuracy of the building class. The proposed approach achieved an overall accuracy of approximately 93% for the target class in a suburban neighborhood, which was the study area. Moreover, completeness (96.73% and correctness (95.02% analyses were performed by comparing the automatically extracted buildings and reference data.

  12. Performance testing of LiDAR exploitation software

    Science.gov (United States)

    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. 2001-2002 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Island County and Northeast Jefferson County, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TerraPoint surveyed and created this data for the Puget Sound LiDAR Consortium under contract. The area surveyed is approximately 525 square miles and covers all of...

  14. The Typology of Female Sex Workers in Dar-es-Salaam ...

    African Journals Online (AJOL)

    Objective: To establish the categories of female sex workers in Dar es Salaam. Methods: We conducted in depth-interviews with 32 female sex workers (FSWs) in five geographic areas of Dar-es-Salaam known to be the primary residential and working places, three local government leaders in three of the five areas known ...

  15. Anti-diabetic drugs in the private and public sector in Dar es Salaam ...

    African Journals Online (AJOL)

    Objectives: To compare availability, cost, affordability and sources of anti-diabetic drugs between private and public health facilities in Dar es Salaam, Tanzania. Design: Cross sectional descriptive study. Setting: Diabetic clinics in private and public health facilities in Dar es Salaam, Tanzania. Subjects: Eighty patients ...

  16. Wayne and Washtenaw Counties 1.0 PPSM LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Wayne and Washtenaw Counties 1.0 PPSM LiDAR LiDAR Data Acquisition and Processing Production Task USGS CONTRACT: 07CRCN0006 TASK ORDER NUMBER: G09PD00300...

  17. The growth of population and employment in the Dar es Salaam city region, Tanzania.

    Science.gov (United States)

    Hayuma, A M

    1983-01-01

    The problems of rapid population growth and unemployment in the Dar es Salaam urban region, Tanzania, are discussed. Efforts to deal with these problems through the 1968 Dar es Salaam master plan are reviewed, and the ineffectiveness of the plan to date is noted.

  18. Layer stacking: A novel algorithm for individual forest tree segmentation from LiDAR point clouds

    Science.gov (United States)

    Elias Ayrey; Shawn Fraver; John A. Kershaw; Laura S. Kenefic; Daniel Hayes; Aaron R. Weiskittel; Brian E. Roth

    2017-01-01

    As light detection and ranging (LiDAR) technology advances, it has become common for datasets to be acquired at a point density high enough to capture structural information from individual trees. To process these data, an automatic method of isolating individual trees from a LiDAR point cloud is required. Traditional methods for segmenting trees attempt to isolate...

  19. Using LiDAR surveys to document floods: A case study of the 2008 Iowa flood

    Science.gov (United States)

    Chen, Bo; Krajewski, Witold F.; Goska, Radek; Young, Nathan

    2017-10-01

    Can we use Light Detection and Ranging (LiDAR), an emergent remote sensing technology with wide applications, to document floods with high accuracy? To explore the feasibility of this application, we propose a method to extract distributed inundation depths from a LiDAR survey conducted during flooding. This method consists of three steps: (1) collecting LiDAR data during flooding; (2) classifying the LiDAR observational points as flooded water surface points and non-flooded points, and generating a floodwater surface elevation model; and (3) subtracting the bare earth Digital Terrain Model (DTM) from the flood surface elevation model to obtain a flood depth map. We applied this method to the 2008 Iowa flood in the United States and evaluated the results using the high-water mark measurements, flood extent extracted from SPOT (Small Programmable Object Technology) imagery, and the near-simultaneously acquired aerial photography. The root mean squared error of the LiDAR-derived floodwater surface profile to high-water marks was 30 cm, the consistency between the two flooded areas derived from LiDAR and SPOT imagery was 72% (81% if suspicious isolated ponds in the SPOT-derived extent were removed), and LiDAR-derived flood extent had a horizontal resolution of ∼3 m. This work demonstrates that LiDAR technology has the potential to provide calibration and validation reference data with appreciable accuracy for improved flood inundation modeling.

  20. 2011-2013 Indiana Statewide Imagery and LiDAR Program: Lake Michigan Watershed Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Indiana's Statewide LiDAR data is produced at 1.5-meter average post spacing for all 92 Indiana Counties covering more than 36,420 square miles. New LiDAR data was...

  1. Effect of slope on treetop detection using a LiDAR Canopy Height Model

    NARCIS (Netherlands)

    Khosravipour, A.; Skidmore, A.K.; Wang, Tiejun; Isenburg, M.; Khoshelham, K.

    2015-01-01

    Canopy Height Models (CHMs) or normalized Digital Surface Models (nDSM) derived from LiDAR data have been applied to extract relevant forest inventory information. However, generating a CHM by height normalizing the raw LiDAR points is challenging if trees are located on complex terrain. On steep

  2. Mapping of landslides under dense vegetation cover using object - oriented analysis and LiDAR derivatives

    NARCIS (Netherlands)

    Van Den Eeckhout, Miet; Kerle, N.; Hervas, Javier; Supper, Robert; Margottini, C.; Canuti, P.; Sassa, K.

    2013-01-01

    Light Detection and Ranging (LiDAR) and its wide range of derivative products have become a powerful tool in landslide research, particularly for landslide identification and landslide inventory mapping. In contrast to the many studies that use expert-based analysis of LiDAR derivatives to identify

  3. Utility of LiDAR for large area forest inventory applications

    Science.gov (United States)

    Nicholas S. Skowronski; Andrew J. Lister

    2012-01-01

    Multi-resource inventory data are used in conjunction with Light Detection and Ranging (LiDAR) data from the Pennsylvania Department of Natural Resource's PAMAP Program to assess the utility of extensive LiDAR acquisitions for large area forest assessments. Background, justification, and initial study designs are presented. The proposed study will involve three...

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

    Science.gov (United States)

    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...

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

    Science.gov (United States)

    2014-01-01

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

  6. Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys

    Science.gov (United States)

    Andrew T. Hudak; Eva K. Strand; Lee A. Vierling; John C. Byrne; Jan U. H. Eitel; Sebastian Martinuzzi; Michael J. Falkowski

    2012-01-01

    Sound forest policy and management decisions to mitigate rising atmospheric CO2 depend upon accurate methodologies to quantify forest carbon pools and fluxes over large tracts of land. LiDAR remote sensing is a rapidly evolving technology for quantifying aboveground biomass and thereby carbon pools; however, little work has evaluated the efficacy of repeat LiDAR...

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

    Science.gov (United States)

    2013-02-01

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

  8. Investigating assumptions of crown archetypes for modelling LiDAR returns

    NARCIS (Netherlands)

    Calders, K.; Lewis, P.; Disney, M.; Verbesselt, J.; Herold, M.

    2013-01-01

    LiDAR has the potential to derive canopy structural information such as tree height and leaf area index (LAI), via models of the LiDAR signal. Such models often make assumptions regarding crown shape to simplify parameter retrieval and crown archetypes are typically assumed to contain a turbid

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

    Science.gov (United States)

    2009-02-01

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

  10. University of Dar es Salaam Library Journal - Vol 9, No 1 (2007)

    African Journals Online (AJOL)

    Gender Analysis Of Electronic Information Resource Use: The Case Of The University Of Dar Es Salaam, Tanzania · EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT DOWNLOAD FULL ... A Bibliometric Study Of Research On Dar Es Salaam Region: 1980 To 2003 · EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

  11. FY12 St Johns River Water Management LiDAR Survey: Putnam (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the FY12 St Johns River Water Management LiDAR Survey, project area in north-central Florida and...

  12. Epidemiological Studies on Bovine Mastitis in Smallholder Dairy Herds in the Dar es Salaam Region, Tanzania

    NARCIS (Netherlands)

    Kivaria, F.M.

    2006-01-01

    Recently the number of milking cows has increased substantially in the Dar es Salaam region due to an increasing demand for fresh milk in this densely populated urban centre. It is estimated that there are 1,765 smallholder dairy herds with 8,233 improved dairy animals in and around the Dar es

  13. Status and prospects for LiDAR remote sensing of forested ecosystems

    Science.gov (United States)

    M. A. Wulder; N. C. Coops; A. T. Hudak; F. Morsdorf; R. Nelson; G. Newnham; M. Vastaranta

    2013-01-01

    The science associated with the use of airborne and satellite Light Detection and Ranging (LiDAR) to remotely sense forest structure has rapidly progressed over the past decade. LiDAR has evolved from being a poorly understood, potentially useful tool to an operational technology in a little over a decade, and these instruments have become a major success story in...

  14. 2007 South Carolina LiDAR: Charleston (partial), Jasper, and Colleton Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data collection was performed utilizing a Leica ALS-50 sensor, collecting multiple return x, y, and z data as well as intensity data. LiDAR data was processed...

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

    Science.gov (United States)

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

    2013-01-01

    Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR...

  16. Genetic linkage mapping in an F2 perennial ryegrass population using DArT markers

    DEFF Research Database (Denmark)

    Tomaszewski, Céline; Byrne, Stephen; Foito, Alexandra

    2012-01-01

    T markers, and a DArT array has recently been developed for the Lolium-Festuca complex. In this study, we report the first use of the DArTFest array to generate a genetic linkage map based on 326 markers in a Lolium perenne F2 population, consisting of 325 genotypes. For proof of concept, the map was used...

  17. Retrieval of savanna vegetation canopy height from ICESat-GLAS spaceborne LiDAR with terrain correction

    CSIR Research Space (South Africa)

    Khalefa, E

    2013-11-01

    Full Text Available Light detection and ranging (LiDAR) remote sensing enables accurate estimation and monitoring of vegetation structural properties. Airborne and spaceborne LiDAR is known to provide reliable information on terrain elevation and forest canopy height...

  18. Registration of vehicle based panoramic image and LiDAR point cloud

    Science.gov (United States)

    Chen, Changjun; Cao, Liang; Xie, Hong; Zhuo, Xiangyu

    2013-10-01

    Higher quality surface information would be got when data from optical images and LiDAR were integrated, owing to the fact that optical images and LiDAR point cloud have unique characteristics that make them preferable in many applications. While most previous works focus on registration of pinhole perspective cameras to 2D or 3D LiDAR data. In this paper, a method for the registration of vehicle based panoramic image and LiDAR point cloud is proposed. Using the translation among panoramic image, single CCD image, laser scanner and Position and Orientation System (POS) along with the GPS/IMU data, precise co-registration between the panoramic image and the LiDAR point cloud in the world system is achieved. Results are presented under a real world data set collected by a new developed Mobile Mapping System (MMS) integrated with a high resolution panoramic camera, two laser scanners and a POS.

  19. Building Contour Extraction Based on LiDAR Point Cloud

    Directory of Open Access Journals (Sweden)

    Zhang Xu-Qing

    2017-01-01

    Full Text Available This paper presents a new method for solving the problem of utilizing the LiDAR data to extract the building contour line. For detection of the edge points between the building test points by using the least squares fitting to get the edge line of buildings and give the weight determining of the building of edge line slope depend on the length of the edge line. And then get the weighted mean of the positive and negative slope of the building edge line. Based on the structure of the adjacent edge perpendicular hypothesis, regularization processing to extract the edge of the skeleton line perpendicular. The experiments show that the extracted building edges have the good accuracy and have the good applicability in complex urban areas.

  20. Delineation of peatland lagg boundaries from airborne LiDAR

    Science.gov (United States)

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

    2017-09-01

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

  1. Dynamic LiDAR-NDVI classification of fluvial landscape units

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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 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.

  3. Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR.

    Science.gov (United States)

    Brede, Benjamin; Lau, Alvaro; Bartholomeus, Harm M; Kooistra, Lammert

    2017-10-17

    In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX ® -1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Model (DTMs), Digital Surface Model (DSMs) and finally Canopy Height Model (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 c m higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 c m . We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB).

  4. Important LiDAR metrics for discriminating forest tree species in Central Europe

    Science.gov (United States)

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

    2018-03-01

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

  5. Mapping river bathymetry with a small footprint green LiDAR: Applications and challenges

    Science.gov (United States)

    Kinzel, Paul J.; Legleiter, Carl; Nelson, Jonathan M.

    2013-01-01

    Airborne bathymetric Light Detection And Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly sought after for high-resolution mapping of fluvial systems. To evaluate the potential utility of bathymetric LiDAR for applications of this kind, we compared detailed surveys collected using wading and sonar techniques with measurements from the United States Geological Survey’s hybrid topographic⁄ bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). These comparisons, based upon data collected from the Trinity and Klamath Rivers, California, and the Colorado River, Colorado, demonstrated

  6. Forest Roads Mapped Using LiDAR in Steep Forested Terrain

    Directory of Open Access Journals (Sweden)

    Russell A. White

    2010-04-01

    Full Text Available LiDAR-derived digital elevation models can reveal road networks located beneath dense forest canopy. This study tests the accuracy of forest road characteristics mapped using LiDAR in the Santa Cruz Mountains, CA. The position, gradient, and total length of a forest haul road were accurately extracted using a 1 m DEM. In comparison to a field-surveyed centerline, the LiDAR-derived road exhibited a positional accuracy of 1.5 m, road grade measurements within 0.53% mean absolute difference, and total road length within 0.2% of the field-surveyed length. Airborne LiDAR can provide thorough and accurate road inventory data to support forest management and watershed assessment activities.

  7. Identification of four Drosophila allatostatins as the cognate ligands for the Drosophila orphan receptor DAR-2

    DEFF Research Database (Denmark)

    Lenz, C; Williamson, M; Hansen, G N

    2001-01-01

    The allatostatins are generally inhibitory insect neuropeptides. The Drosophila orphan receptor DAR-2 is a G-protein-coupled receptor, having 47% amino acid residue identity with another Drosophila receptor, DAR-1 (which is also called dros. GPCR, or DGR) that was previously shown...... to be the receptor for an intrinsic Drosophila A-type (cockroach-type) allatostatin. Here, we have permanently expressed DAR-2 in CHO cells and found that it is the cognate receptor for four Drosophila A-type allatostatins, the drostatins-A1 to -A4. Of all the drostatins, drostatin-A4 (Thr...... weakly in the brain. The Drosophila larval gut also contains about 20-30 endocrine cells, expressing the gene for the drostatins-A1 to -A4. We suggest, therefore, that DAR-2 mediates an allatostatin (drostatin)-induced inhibition of gut motility. This is the first report on the permanent and functional...

  8. 2007 Lake County Board of County Commissioners Topographic LiDAR: Lake County, Florida

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata document describes the LiDAR point data in LAS format produced by Kucera covering the project area of Lake County, FL. The data produced is...

  9. 2007 Southwest Florida Water Management District (SWFWMD) LiDAR: Hernando County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset is one component of a digital terrain model (DTM) for the Southwest Florida Water Management Districts FY2006 Digital Orthophoto (B089) and LiDAR...

  10. 2006 U.S. Geological Survey Topographic LiDAR: Alameda County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) data set is a survey of Alameda County in Northern California. The entire survey covers approximately 868.382 square miles....

  11. 2008 Northwest Florida Water Management District (NWFWMD) LiDAR: Inland Okaloosa County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) LAS dataset is a survey of inland Okaloosa County, Florida not covered in the 2008 Florida Department of Emergency...

  12. 2009 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Fort Kent, Maine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Camp Dresser McKee Inc. contracted with Sanborn Map Company to provide LiDAR mapping services for Fort Kent, Maine. Utilizing multi-return systems, Light Detection...

  13. LiDAR-derived Vegetation Canopy Structure, Great Smoky Mountains National Park, 2011

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset provides multiple-return LiDAR-derived vegetation canopy structure at 30-meter spatial resolution for the Great Smoky Mountains National Park (GSMNP)....

  14. LiDAR and DTM Data from Forested Land Near Manaus, Amazonas, Brazil, 2008

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides LiDAR point clouds and digital terrain models (DTM) from surveys over the K34 tower site in the Cuieiras Biological Reserve, over forest...

  15. Case of rhesus antigen weak D type 4.2. (DAR category detection

    Directory of Open Access Journals (Sweden)

    L. L. Golovkina

    2015-01-01

    Full Text Available Serological methods of Rhesus antigens identification in humans cannot identify D-antigen variants. In this article the serological characteristics of Rhesus antigen D weak type 4.2. (Category DAR are described.

  16. LiDAR Elevation Data Collection - Putnam County, NY, 2008 (NYSDEC)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Summary of the surface elevation data collection project in Putnam County, NY (NYSDEC) 2008. Products generated include LiDAR point data in LAS Binary format v1.1....

  17. LiDAR Relative Reflectivity Surface (2011) for the St. Thomas East End Reserve, St. Thomas

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection & Ranging) 0.3x0.3 meter resolution relative seafloor reflectivity surface for the St. Thomas East End Reserve...

  18. 2009 Puget Sound Lidar Consortium (PSLC) Topographic LiDAR: Nooksack River

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data of the Nooksack River in Washington on February 20th - 22nd, 2009. The total area of...

  19. CMS: LiDAR Data for Forested Sites on Borneo Island, Kalimantan, Indonesia, 2014

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset provides airborne LiDAR data collected over 90 sites totaling approximately 100,000 hectares of forested land in Kalimantan, Indonesia on the island of...

  20. CMS: LiDAR-derived Canopy Height, Elevation for Sites in Kalimantan, Indonesia, 2014

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset provides canopy height and elevation data products derived from airborne LiDAR data collected over 90 sites on the island of Borneo in late 2014. The...

  1. LiDAR and DTM Data from Tapajos National Forest in Para, Brazil, 2008

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides LiDAR point clouds and digital terrain models (DTM) from surveys over the Tapajos National Forest in Belterra municipality, Para, Brazil...

  2. 2006-2008 PAMAP LiDAR Data of Pennsylvania (Northern Counties)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of classified LiDAR (Light Detection and Ranging) elevation points produced by the PAMAP Program. PAMAP data are organized into blocks, which...

  3. CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004-2008

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides estimates of forest canopy height derived from the Geoscience Laser Altimeter System (GLAS) LiDAR instrument that was aboard the NASA Ice,...

  4. LiDAR Data, DEM, and Maximum Vegetation Height Product from Southern Idaho, 2014

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset provides the point cloud data derived from small footprint waveform LiDAR data collected in August 2014 over Reynolds Creek Experimental Watershed and...

  5. 2010 U.S. Geological Survey (USGS) Topographic LiDAR: San Francisco Bay, California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (LiDAR)...

  6. CMS: LiDAR Data for Mangrove Forests in the Zambezi River Delta, Mozambique, 2014

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides high-resolution LiDAR point cloud data collected during surveys over mangrove forests in the Zambezi River Delta in Mozambique in May 2014....

  7. 2006 Florida LiDAR: Escambia, Santa Rosa, and Walton Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — ESCAMBIA: The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Escambia County, Florida. These data were produced for Dewberry and...

  8. 2006-2008 PAMAP LiDAR Data of Pennsylvania (Southern Counties)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of classified LiDAR (Light Detection and Ranging) elevation points produced by the PAMAP Program. Additional information is available at the...

  9. 2007 Southwest Florida Water Management District (SWFWMD) LiDAR: Hillsborough/Little Manatee Districts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — EarthData International collected ADS-50 derived LiDAR over a portion of Hillsborough and Manatee Counties with a one meter post spacing. The period of collection...

  10. 2010 U.S. Geological Survey Topographic LiDAR: Atchafalaya Basin, Louisiana

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Atchafalaya Basin in south-central Louisiana. The entire survey area encompasses 981 square miles....

  11. 2011 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Quinnipiac River Watershed, Connecticut

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Quinnipiac AOI consists of one 443 square mile area. Ground Control is collected throughout the AOI for use in the processing of LiDAR data to ensure data...

  12. 2009 National Renewable Energy Laboratory/Boston Redevelopment Authority Topographic LiDAR: Boston, Massachusetts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Alliance for Sustainable Energy, LLC contracted with Sanborn to provide LiDAR mapping services for the Boston area. Utilizing multi-return systems, Light...

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

    Science.gov (United States)

    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.

  14. Sexual behaviours and associated factors among students at Bahir Dar University: a cross sectional study

    OpenAIRE

    Mulu, Wondemagegn; Yimer, Mulat; Abera, Bayeh

    2014-01-01

    Background Sexual behaviour is the core of sexuality matters in adolescents and youths. Their modest or dynamic behaviour vulnerable them to risky sexual behaviours. In Ethiopia, there is scarcity of multicentered representative data on sexual behaviours in students to have a national picture at higher education. This study therefore conducted to assess sexual behaviours and associated factors at Bahir Dar University, Ethiopia. Methods A cross sectional study was conducted among Bahir Dar Uni...

  15. Synergy of VSWIR and LiDAR for Ecosystem Structure, Biomass, and Canopy Diversity

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  17. Remote sensing of forest structure using LiDAR and SAR

    OpenAIRE

    Balzter, Heiko; Burwell, Claire; Rowland, Clare S.; Tansey, Kevin

    2008-01-01

    Forests play an important role in the global climate system because they take up and store large amounts of carbon in the form of biomass. This paper examines techniques of retrieving structural forest information using the remote sensing techniques of LiDAR and SAR. Both sensing methods can provide information on the vertical structure of forests. Certain LiDAR instruments can record a vertical waveform of reflected radiation from the forest which can be related to vertical bioma...

  18. Status and prospects for LiDAR remote sensing of forested ecosystems

    OpenAIRE

    Wulder, Michael A; Coops, Nicholas C; Hudak, Andrew T; Morsdorf, Felix; Nelson, R; Newnham, G; Vastaranta, Mikko

    2013-01-01

    The science associated with the use of airborne and satellite Light Detection and Ranging (LiDAR) to remotely sense forest structure has rapidly progressed over the past decade. LiDAR has evolved from being a poorly understood, potentially useful tool to an operational technology in a little over a decade, and these instruments have become a major success story in terms of their application to the measurement, mapping, or monitoring of forests worldwide. Invented in 1960, the laser and, a sho...

  19. Getting the most neutrinos out of IsoDAR

    Energy Technology Data Exchange (ETDEWEB)

    Ciuffoli, Emilio; Zhao, Fengyi; Deliyergiyev, Maksym [CAS, Institute of Modern Physics, Lanzhou (China); Mohammed, Hosam; Evslin, Jarah [CAS, Institute of Modern Physics, Lanzhou (China); University of the Chinese Academy of Sciences, Beijing (China)

    2017-12-15

    Several experimental collaborations worldwide intend to test sterile neutrino models by measuring the disappearance of antineutrinos produced via isotope decay at rest (IsoDAR). The most advanced of these proposals have very similar setups, in which a proton beam strikes a target yielding neutrons which are absorbed by a high isotopic purity {sup 7}Li converter, yielding {sup 8}Li whose resulting decay yields the antineutrinos. In this note, we use FLUKA and GEANT4 simulations to investigate three proposed modifications of this standard proposal. In the first, the {sup 7}Li is replaced with {sup 7}Li compounds including a deuterium moderator. In the second, a gap is placed between the target and the converter to reduce the neutron bounce-back. Finally, we consider cooling the converter with liquid nitrogen. We find that these modifications can increase the antineutrino yield by as much as 50%. The first also substantially reduces the quantity of high purity {sup 7}Li which is needed. (orig.)

  20. (Women’s Readings of Parvaz- Dar- Hobab

    Directory of Open Access Journals (Sweden)

    Jamal Mohammadi

    2008-07-01

    Full Text Available This research is an attempt to explain how audiences read and decode the dominant or preferred reading of television soap operas ( here, one of them named : Parvaz Dar Hobab . The main problem of this research is that in what way TV soap operas prefer or make dominant some meanings, ideas and values and how audiences interpret and decode these meanings and ideas and values. From this viewpoint, a soap opera is an articulation constructed of different, and sometimes contrast, elements which are unified around a nodal point. In other words, a television soap opera is an articulatory discourse which is constructed through some technical, social and ideological codes by hegemonic system. In a TV soap opera, as a discourse, some ideas and meanings are preferred over the others. The question is that how social subjects, who have an objective position in the social structure, read and decode these dominant ideas and meanings? In this research, in the first part we have used the semilogical- structuralist method to explain the preferred reading of TV soap operas, and in the second part we used focused group interview to study women readings. To mention one of the conclusions of this research, we can say that this soap opera attempts to hide that social nihilism which is the main factor of addiction. Most of the audiences have an oppositional reading of this problem.

  1. Analyzing Glacier Surface Motion Using LiDAR Data

    Directory of Open Access Journals (Sweden)

    Jennifer W. Telling

    2017-03-01

    Full Text Available Understanding glacier motion is key to understanding how glaciers are growing, shrinking, and responding to changing environmental conditions. In situ observations are often difficult to collect and offer an analysis of glacier surface motion only at a few discrete points. Using light detection and ranging (LiDAR data collected from surveys over six glaciers in Greenland and Antarctica, particle image velocimetry (PIV was applied to temporally-spaced point clouds to detect and measure surface motion. The type and distribution of surface features, surface roughness, and spatial and temporal resolution of the data were all found to be important factors, which limited the use of PIV to four of the original six glaciers. The PIV results were found to be in good agreement with other, widely accepted, measurement techniques, including manual tracking and GPS, and offered a comprehensive distribution of velocity data points across glacier surfaces. For three glaciers in Taylor Valley, Antarctica, average velocities ranged from 0.8–2.1 m/year. For one glacier in Greenland, the average velocity was 22.1 m/day (8067 m/year.

  2. Adaptive Covariance Estimation Method for LiDAR-Aided Multi-Sensor Integrated Navigation Systems

    Directory of Open Access Journals (Sweden)

    Shifei Liu

    2015-01-01

    Full Text Available The accurate estimation of measurements covariance is a fundamental problem in sensors fusion algorithms and is crucial for the proper operation of filtering algorithms. This paper provides an innovative solution for this problem and realizes the proposed solution on a 2D indoor navigation system for unmanned ground vehicles (UGVs that fuses measurements from a MEMS-grade gyroscope, speed measurements and a light detection and ranging (LiDAR sensor. A computationally efficient weighted line extraction method is introduced, where the LiDAR intensity measurements are used, such that the random range errors and systematic errors due to surface reflectivity in LiDAR measurements are considered. The vehicle pose change is obtained from LiDAR line feature matching, and the corresponding pose change covariance is also estimated by a weighted least squares-based technique. The estimated LiDAR-based pose changes are applied as periodic updates to the Inertial Navigation System (INS in an innovative extended Kalman filter (EKF design. Besides, the influences of the environment geometry layout and line estimation error are discussed. Real experiments in indoor environment are performed to evaluate the proposed algorithm. The results showed the great consistency between the LiDAR-estimated pose change covariance and the true accuracy. Therefore, this leads to a significant improvement in the vehicle’s integrated navigation accuracy.

  3. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation

    Directory of Open Access Journals (Sweden)

    Wuming Zhang

    2016-06-01

    Full Text Available Separating point clouds into ground and non-ground measurements is an essential step to generate digital terrain models (DTMs from airborne LiDAR (light detection and ranging data. However, most filtering algorithms need to carefully set up a number of complicated parameters to achieve high accuracy. In this paper, we present a new filtering method which only needs a few easy-to-set integer and Boolean parameters. Within the proposed approach, a LiDAR point cloud is inverted, and then a rigid cloth is used to cover the inverted surface. By analyzing the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface. Finally, the ground points can be extracted from the LiDAR point cloud by comparing the original LiDAR points and the generated surface. Benchmark datasets provided by ISPRS (International Society for Photogrammetry and Remote Sensing working Group III/3 are used to validate the proposed filtering method, and the experimental results yield an average total error of 4.58%, which is comparable with most of the state-of-the-art filtering algorithms. The proposed easy-to-use filtering method may help the users without much experience to use LiDAR data and related technology in their own applications more easily.

  4. The application of LiDAR to investigate foredune morphology and vegetation

    Science.gov (United States)

    Doyle, Thomas B.; Woodroffe, Colin D.

    2018-02-01

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

  5. Airborne LiDAR Detects Selectively Logged Tropical Forest Even in an Advanced Stage of Recovery

    Directory of Open Access Journals (Sweden)

    Rafi Kent

    2015-06-01

    Full Text Available Identifying historical forest disturbances is difficult, especially in selectively logged areas. LiDAR is able to measure fine-scale variations in forest structure over multiple kilometers. We use LiDAR data from ca. 16 km2 of forest in Sierra Leone, West Africa, to discriminate areas of old-growth from areas recovering from selective logging for 23 years. We examined canopy height variation and gap size distributions. We found that though recovering blocks of forest differed little in height from old-growth forest (up to 3 m, they had a greater area of canopy gaps (average 10.2% gap fraction in logged areas, compared to 5.6% in unlogged area; and greater numbers of gaps penetrating to the forest floor (162 gaps at 2 m height in logged blocks, and 101 in an unlogged block. Comparison of LiDAR measurements with field data demonstrated that LiDAR delivered accurate results. We found that gap size distributions deviated from power-laws reported previously, with substantially fewer large gaps than predicted by power-law functions. Our analyses demonstrate that LiDAR is a useful tool for distinguishing structural differences between old-growth and old-secondary forests. That makes LiDAR a powerful tool for REDD+ (Reduction of Emissions from Deforestation and Forest Degradation programs implementation and conservation planning.

  6. Quantifying Forest Carbon and Structure with Terrestrial LiDAR

    Science.gov (United States)

    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.

  7. NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

    Science.gov (United States)

    Chirayath, Ved

    2018-01-01

    We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and

  8. Parallel Landscape Driven Data Reduction & Spatial Interpolation Algorithm for Big LiDAR Data

    Directory of Open Access Journals (Sweden)

    Rahil Sharma

    2016-06-01

    Full Text Available Airborne Light Detection and Ranging (LiDAR topographic data provide highly accurate digital terrain information, which is used widely in applications like creating flood insurance rate maps, forest and tree studies, coastal change mapping, soil and landscape classification, 3D urban modeling, river bank management, agricultural crop studies, etc. In this paper, we focus mainly on the use of LiDAR data in terrain modeling/Digital Elevation Model (DEM generation. Technological advancements in building LiDAR sensors have enabled highly accurate and highly dense LiDAR point clouds, which have made possible high resolution modeling of terrain surfaces. However, high density data result in massive data volumes, which pose computing issues. Computational time required for dissemination, processing and storage of these data is directly proportional to the volume of the data. We describe a novel technique based on the slope map of the terrain, which addresses the challenging problem in the area of spatial data analysis, of reducing this dense LiDAR data without sacrificing its accuracy. To the best of our knowledge, this is the first ever landscape-driven data reduction algorithm. We also perform an empirical study, which shows that there is no significant loss in accuracy for the DEM generated from a 52% reduced LiDAR dataset generated by our algorithm, compared to the DEM generated from an original, complete LiDAR dataset. For the accuracy of our statistical analysis, we perform Root Mean Square Error (RMSE comparing all of the grid points of the original DEM to the DEM generated by reduced data, instead of comparing a few random control points. Besides, our multi-core data reduction algorithm is highly scalable. We also describe a modified parallel Inverse Distance Weighted (IDW spatial interpolation method and show that the DEMs it generates are time-efficient and have better accuracy than the one’s generated by the traditional IDW method.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2017-06-01

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

  11. Geotechnical applications of LiDAR pertaining to geomechanical evaluation and hazard identification

    Science.gov (United States)

    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

  12. Segmentation based building detection approach from LiDAR point cloud

    Directory of Open Access Journals (Sweden)

    Anandakumar M. Ramiya

    2017-06-01

    Full Text Available Accurate building detection and reconstruction is an important challenge posed to the remote sensing community dealing with LiDAR point cloud. The inherent geometric nature of LiDAR point cloud provides a new dimension to the remote sensing data which can be used to produce accurate 3D building models at relatively less time compared to traditional photogrammetry based 3D reconstruction methods. 3D segmentation is a key step to bring out the implicit geometrical information from the LiDAR point cloud. This research proposes to use open source point cloud library (PCL for 3D segmentation of LiDAR point cloud and presents a novel histogram based methodology to separate the building clusters from the non building clusters. The proposed methodology has been applied on two different airborne LiDAR datasets acquired over part of urban region around Niagara Falls, Canada and southern Washington, USA. An overall building detection accuracy of 100% and 82% respectively is achieved for the two datasets. The performance of proposed methodology has been compared with the commercially available Terrasolid software. The results show that the buildings detected using open source point cloud library produce comparable results with the buildings detected using commercial software (buildings detection accuracy: 86.3% and 89.2% respectively for the two datasets.

  13. BUILDING ROOF BOUNDARY EXTRACTION FROM LiDAR AND IMAGE DATA BASED ON MARKOV RANDOM FIELD

    Directory of Open Access Journals (Sweden)

    A. P. Dal Poz

    2017-05-01

    Full Text Available In this paper a method for automatic extraction of building roof boundaries is proposed, which combines LiDAR data and highresolution aerial images. The proposed method is based on three steps. In the first step aboveground objects are extracted from LiDAR data. Initially a filtering algorithm is used to process the original LiDAR data for getting ground and non-ground points. Then, a region-growing procedure and the convex hull algorithm are sequentially used to extract polylines that represent aboveground objects from the non-ground point cloud. The second step consists in extracting corresponding LiDAR-derived aboveground objects from a high-resolution aerial image. In order to avoid searching for the interest objects over the whole image, the LiDAR-derived aboveground objects’ polylines are photogrammetrically projected onto the image space and rectangular bounding boxes (sub-images that enclose projected polylines are generated. Each sub-image is processed for extracting the polyline that represents the interest aboveground object within the selected sub-image. Last step consists in identifying polylines that represent building roof boundaries. We use the Markov Random Field (MRF model for modelling building roof characteristics and spatial configurations. Polylines that represent building roof boundaries are found by optimizing the resulting MRF energy function using the Genetic Algorithm. Experimental results are presented and discussed in this paper.

  14. The Extraction of Vegetation Points from LiDAR Using 3D Fractal Dimension Analyses

    Directory of Open Access Journals (Sweden)

    Haiquan Yang

    2015-08-01

    Full Text Available Light Detection and Ranging (LiDAR, a high-precision technique used for acquiring three-dimensional (3D surface information, is widely used to study surface vegetation information. Moreover, the extraction of a vegetation point set from the LiDAR point cloud is a basic starting-point for vegetation information analysis, and an important part of its further processing. To extract the vegetation point set completely and to describe the different spatial morphological characteristics of various features in a LiDAR point cloud, we have used 3D fractal dimensions. We discovered that every feature has its own distinctive 3D fractal dimension interval. Based on the 3D fractal dimensions of tall trees, we propose a new method for the extraction of vegetation using airborne LiDAR. According to this method, target features can be distinguished based on their morphological characteristics. The non-ground points acquired by filtering are processed by region growing segmentation and the morphological characteristics are evaluated by 3D fractal dimensions to determine the features required for the determination of the point set for tall trees. Avon, New York, USA was selected as the study area to test the method and the result proves the method’s efficiency. Thus, this approach is feasible. Additionally, the method uses the 3D coordinate properties of the LiDAR point cloud and does not require additional information, such as return intensity, giving it a larger scope of application.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

    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

  16. Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry

    Directory of Open Access Journals (Sweden)

    Zhigang Pan

    2015-04-01

    Full Text Available We evaluate the performance of full waveform LiDAR decomposition algorithms with a high-resolution single band airborne LiDAR bathymetry system in shallow rivers. A continuous wavelet transformation (CWT is proposed and applied in two fluvial environments, and the results are compared to existing echo retrieval methods. LiDAR water depths are also compared to independent field measurements. In both clear and turbid water, the CWT algorithm outperforms the other methods if only green LiDAR observations are available. However, both the definition of the water surface, and the turbidity of the water significantly influence the performance of the LiDAR bathymetry observations. The results suggest that there is no single best full waveform processing algorithm for all bathymetric situations. Overall, the optimal processing strategies resulted in a determination of water depths with a 6 cm mean at 14 cm standard deviation for clear water, and a 16 cm mean and 27 cm standard deviation in more turbid water.

  17. LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models

    Science.gov (United States)

    Cawood, Adam J.; Bond, Clare E.; Howell, John A.; Butler, Robert W. H.; Totake, Yukitsugu

    2017-05-01

    Light Detection and Ranging (LiDAR) and Structure from Motion (SfM) provide large amounts of digital data from which virtual outcrops can be created. The accuracy of these surface reconstructions is critical for quantitative structural analysis. Assessment of LiDAR and SfM methodologies suggest that SfM results are comparable to high data-density LiDAR on individual surfaces. The effect of chosen acquisition technique on the full outcrop and the efficacy on its virtual form for quantitative structural analysis and prediction beyond single bedding surfaces, however, is less certain. Here, we compare the accuracy of digital virtual outcrop analysis with traditional field data, for structural measurements and along-strike prediction of fold geometry from Stackpole syncline. In this case, the SfM virtual outcrop, derived from UAV imagery, yields better along-strike predictions and a more reliable geological model, in spite of lower accuracy surface reconstructions than LiDAR. This outcome is attributed to greater coverage by UAV and reliable reconstruction of a greater number of bedding planes than terrestrial LiDAR, which suffers from the effects of occlusion. Irrespective of the chosen acquisition technique, we find that workflows must incorporate careful survey planning, data processing and quality checking of derived data if virtual outcrops are to be used for robust structural analysis and along-strike prediction.

  18. Using LiDAR to as a Potential Method for Detection Plastics in Water

    Science.gov (United States)

    Lee, G.; Neal, A.; Mielke, R.; Bookhagen, B.

    2010-12-01

    We conducted a series of experiments using Light Detection and Range (LiDAR) technology as an innovative way to detect the presence of plastics in water. The purpose of this study was to determine if LiDAR technology is a feasible, non-intrusive alternative to dredging in the ocean to determine the amount of plastics in the ocean. We used a tripod mounted RIEGL LMS-Z420i terrestrial LiDAR 3-D scanner and the associated operating software RiSCAN Pro. The terrestrial LiDAR is an optical remote sensing technology that measures the reflection of near infared light to find the range of a distant target that is most commonly used to create high precision digital elevation models of terrestrial surfaces. In theory, water should absorb the near infared light, while the plastics should reflect the light. The experiments consisted of different scale models of plastic pellets in water, ranging from a small plastic dish to a large tank to test the range of the LiDAR in different salt and fresh water mediums.

  19. Localized Segment Based Processing for Automatic Building Extraction from LiDAR Data

    Science.gov (United States)

    Parida, G.; Rajan, K. S.

    2017-05-01

    The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

  20. Green infrastructure for flood risk management in Dar es Salaam and Copenhagen

    DEFF Research Database (Denmark)

    Mguni, Patience; Herslund, Lise Byskov; Jensen, Marina Bergen

    2015-01-01

    The risk of flooding in urban areas could be better approached by complementing conventional sewer systems with sustainable urban drainage systems (SUDS) for storm-water management. This may be the case for developing world cities like Dar es Salaam with incomplete sewer services, as well as cities...... like Copenhagen with fully developed sewer systems. This paper explores some theories relevant to understanding how the implementation of SUDS may be one option for supporting a transition towards sustainable urban water management (SUWM). Using interviews, document analysis and observation......, a comparison of the opportunities and barriers to the implementation of SUDS in Dar es Salaam and Copenhagen is presented. The results indicate that a bottom-up approach in Dar es Salaam is important, with the community level taking the lead, while in Copenhagen the top-down approach currently employed...

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  2. Numerical modeling of the airflow around a forest edge using LiDAR-derived forest heigths

    DEFF Research Database (Denmark)

    Boudreault, Louis-Etienne; Dellwik, Ebba; Bechmann, Andreas

    A 3D methodology to quantify the effect of forests on the mean wind flow field is presented. The methodology is based on the treatment of forest raw data of light detection and ranging (LiDAR) scans, and a computational fluid dynamics (CFD) method based on a Reynolds-averaged Navier-Stokes (Ra......NS) approach using the k−e turbulence model with a corresponding canopy model. The example site investigated is a forest edge located on the Falster island in Denmark, where a measurement campaign was conducted. The LiDAR scans are used in order to obtain the forest heights, which served as input...

  3. A Hybrid Process/Thread Parallel Algorithm for Generating DEM from LiDAR Points

    Directory of Open Access Journals (Sweden)

    Yibin Ren

    2017-09-01

    Full Text Available Airborne Light Detection and Ranging (LiDAR is widely used in digital elevation model (DEM generation. However, the very large volume of LiDAR datasets brings a great challenge for the traditional serial algorithm. Using parallel computing to accelerate the efficiency of DEM generation from LiDAR points has been a hot topic in parallel geo-computing. Generally, most of the existing parallel algorithms running on high-performance clusters (HPC were in process-paralleling mode, with a static scheduling strategy. The static strategy would not respond dynamically according to the computation progress, leading to load unbalancing. Additionally, because each process has independent memory space, the cost of dealing with boundary problems increases obviously with the increase in the number of processes. Actually, these two problems can have a significant influence on the efficiency of DEM generation for larger datasets, especially for those of irregular shapes. Thus, to solve these problems, we combined the advantages of process-paralleling with the advantages of thread-paralleling, forming a new idea: using process-paralleling to achieve a flexible schedule and scalable computation, using thread-paralleling inside the process to reduce boundary problems. Therefore, we proposed a hybrid process/thread parallel algorithm for generating DEM from LiDAR points. Firstly, at the process level, we designed a parallel method (PPDB to accelerate the partitioning of LiDAR points. We also proposed a new dynamic scheduling strategy to achieve better load balancing. Secondly, at the thread level, we designed an asynchronous parallel strategy to hide the cost of LiDAR points’ reading. Lastly, we tested our algorithm with three LiDAR datasets. Experiments showed that our parallel algorithm had no influence on the accuracy of the resultant DEM. At the same time, our algorithm reduced the conversion time from 112,486 s to 2342 s when we used the largest dataset (150

  4. Grupo DAR : Actividades didácticas y recreativas para niños

    OpenAIRE

    Bellone, María Eugenia; Rizzi, Nicolás; Figueroa, Claudio; Biber, Leonardo

    2012-01-01

    El presente artículo propone dar cuenta de las acciones llevadas a cabo por el Grupo DAR (actividades didácticas y recreativas) conformado por jóvenes estudiantes universitarios y profesionales, residentes de la Ciudad de Córdoba. El equipo coordina desde el año 2005 diversos talleres destinados a niños de entre 4 y 14 años residentes y de zonas aledañas al Barrio Ferreyra, ubicado a 12 kilómetros de la zona céntrica. La modalidad de trabajo parte de una perspectiva de int...

  5. Prevalence of teeth with untreated dental trauma among nursery and primary school pupils in Dar es Salaam, Tanzania.

    NARCIS (Netherlands)

    Kahabuka, F.K.; Plasschaert, A.J.M.; Hof, M.A. van 't

    2001-01-01

    The aim of this study was to investigate the prevalence of teeth with untreated dental trauma among children aged 4-15 years in Dar es Salaam, Tanzania. A sample of 4524 children from three districts of different socio-economic status in the Dar es Salaam area was examined for signs of dental trauma

  6. Comparison of LiDAR-derived data and high resolution true color imagery for extracting urban forest cover

    Science.gov (United States)

    Aaron E. Maxwell; Adam C. Riley; Paul. Kinder

    2013-01-01

    Remote sensing has many applications in forestry. Light detection and ranging (LiDAR) and high resolution aerial photography have been investigated as means to extract forest data, such as biomass, timber volume, stand dynamics, and gap characteristics. LiDAR return intensity data are often overlooked as a source of input raster data for thematic map creation. We...

  7. Remote Sensing of Sonoran Desert Vegetation Structure and Phenology with Ground-Based LiDAR

    Directory of Open Access Journals (Sweden)

    Joel B. Sankey

    2014-12-01

    Full Text Available 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.

  8. Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey

    Science.gov (United States)

    Lei Wang; Andrew G. Birt; Charles W. Lafon; David M. Cairns; Robert N. Coulson; Maria D. Tchakerian; Weimin Xi; Sorin C. Popescu; James M. Guldin

    2013-01-01

    Small Footprint LiDAR (Light Detection And Ranging) has been proposed as an effective tool for measuring detailed biophysical characteristics of forests over broad spatial scales. However, by itself LiDAR yields only a sample of the true 3D structure of a forest. In order to extract useful forestry relevant information, this data must be interpreted using mathematical...

  9. Investigating the influence of LiDAR ground surface errors on the utility of derived forest inventories

    Science.gov (United States)

    Wade T. Tinkham; Alistair M. S. Smith; Chad Hoffman; Andrew T. Hudak; Michael J. Falkowski; Mark E. Swanson; Paul E. Gessler

    2012-01-01

    Light detection and ranging, or LiDAR, effectively produces products spatially characterizing both terrain and vegetation structure; however, development and use of those products has outpaced our understanding of the errors within them. LiDAR's ability to capture three-dimensional structure has led to interest in conducting or augmenting forest inventories with...

  10. Comparing LiDAR-Generated to ground- surveyed channel cross-sectional profiles in a forested mountain stream

    Science.gov (United States)

    Brian C. Dietterick; Russell White; Ryan. Hilburn

    2012-01-01

    Airborne Light Detection and Ranging (LiDAR) holds promise to provide an alternative to traditional ground-based survey methods for stream channel characterization and some change detection purposes, even under challenging landscape conditions. This study compared channel characteristics measured at 53 ground-surveyed and LiDAR-derived crosssectional profiles located...

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

    Science.gov (United States)

    2009-02-01

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

  12. Visualization of High-Resolution LiDAR Topography in Google Earth

    Science.gov (United States)

    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

  13. Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 3 : advanced consideration in LiDAR technology for bridge evaluation.

    Science.gov (United States)

    2012-03-01

    This report describes Phase Two enhancement of terrestrial LiDAR scanning for bridge damage : evaluation that was initially developed in Phase One. Considering the spatial and reflectivity : information contained in LiDAR scans, two detection algorit...

  14. Habitat Classification of Temperate Marine Macroalgal Communities Using Bathymetric LiDAR

    Directory of Open Access Journals (Sweden)

    Richard Zavalas

    2014-03-01

    Full Text Available Here, we evaluated the potential of using bathymetric Light Detection and Ranging (LiDAR to characterise shallow water (<30 m benthic habitats of high energy subtidal coastal environments. Habitat classification, quantifying benthic substrata and macroalgal communities, was achieved in this study with the application of LiDAR and underwater video groundtruth data using automated classification techniques. Bathymetry and reflectance datasets were used to produce secondary terrain derivative surfaces (e.g., rugosity, aspect that were assumed to influence benthic patterns observed. An automated decision tree classification approach using the Quick Unbiased Efficient Statistical Tree (QUEST was applied to produce substrata, biological and canopy structure habitat maps of the study area. Error assessment indicated that habitat maps produced were primarily accurate (>70%, with varying results for the classification of individual habitat classes; for instance, producer accuracy for mixed brown algae and sediment substrata, was 74% and 93%, respectively. LiDAR was also successful for differentiating canopy structure of macroalgae communities (i.e., canopy structure classification, such as canopy forming kelp versus erect fine branching algae. In conclusion, habitat characterisation using bathymetric LiDAR provides a unique potential to collect baseline information about biological assemblages and, hence, potential reef connectivity over large areas beyond the range of direct observation. This research contributes a new perspective for assessing the structure of subtidal coastal ecosystems, providing a novel tool for the research and management of such highly dynamic marine environments.

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

    Science.gov (United States)

    Chad Babcock; Andrew O. Finley; John B. Bradford; Randy Kolka; Richard Birdsey; Michael G. Ryan

    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...

  16. The effect of El Nino on trypanosome infection in cattle in Dar es ...

    African Journals Online (AJOL)

    A retrospective study was carried out to assess the effect of El Nino on trypanosome infection in cattle. Trypanosome infection was monitored in free grazing dairy cattle before and after El Nino in Dar es Salaam. The study involved 49 smallholder dairy herds with a total of 570 dairy cattle. Trypanosomes were identified by ...

  17. Tensor-Based Sparse Representation Classification for Urban Airborne LiDAR Points

    Directory of Open Access Journals (Sweden)

    Nan Li

    2017-11-01

    Full Text Available The common statistical methods for supervised classification usually require a large amount of training data to achieve reasonable results, which is time consuming and inefficient. In many methods, only the features of each point are used, regardless of their spatial distribution within a certain neighborhood. This paper proposes a tensor-based sparse representation classification (TSRC method for airborne LiDAR (Light Detection and Ranging points. To keep features arranged in their spatial arrangement, each LiDAR point is represented as a 4th-order tensor. Then, TSRC is performed for point classification based on the 4th-order tensors. Firstly, a structured and discriminative dictionary set is learned by using only a few training samples. Subsequently, for classifying a new point, the sparse tensor is calculated based on the tensor OMP (Orthogonal Matching Pursuit algorithm. The test tensor data is approximated by sub-dictionary set and its corresponding subset of sparse tensor for each class. The point label is determined by the minimal reconstruction residuals. Experiments are carried out on eight real LiDAR point clouds whose result shows that objects can be distinguished by TSRC successfully. The overall accuracy of all the datasets is beyond 80% by TSRC. TSRC also shows a good improvement on LiDAR points classification when compared with other common classifiers.

  18. Identification of four Drosophila allatostatins as the cognate ligands for the Drosophila orphan receptor DAR-2

    DEFF Research Database (Denmark)

    Lenz, C; Williamson, M; Hansen, G N

    2001-01-01

    to be the receptor for an intrinsic Drosophila A-type (cockroach-type) allatostatin. Here, we have permanently expressed DAR-2 in CHO cells and found that it is the cognate receptor for four Drosophila A-type allatostatins, the drostatins-A1 to -A4. Of all the drostatins, drostatin-A4 (Thr...

  19. Automatic extraction of pavement markings on streets from point cloud data of mobile LiDAR

    Science.gov (United States)

    Gao, Yang; Zhong, Ruofei; Tang, Tao; Wang, Liuzhao; Liu, Xianlin

    2017-08-01

    Pavement markings provide an important foundation as they help to keep roads users safe. Accurate and comprehensive information about pavement markings assists the road regulators and is useful in developing driverless technology. Mobile light detection and ranging (LiDAR) systems offer new opportunities to collect and process accurate pavement markings’ information. Mobile LiDAR systems can directly obtain the three-dimensional (3D) coordinates of an object, thus defining spatial data and the intensity of (3D) objects in a fast and efficient way. The RGB attribute information of data points can be obtained based on the panoramic camera in the system. In this paper, we present a novel method process to automatically extract pavement markings using multiple attribute information of the laser scanning point cloud from the mobile LiDAR data. This method process utilizes a differential grayscale of RGB color, laser pulse reflection intensity, and the differential intensity to identify and extract pavement markings. We utilized point cloud density to remove the noise and used morphological operations to eliminate the errors. In the application, we tested our method process on different sections of roads in Beijing, China, and Buffalo, NY, USA. The results indicated that both correctness (p) and completeness (r) were higher than 90%. The method process of this research can be applied to extract pavement markings from huge point cloud data produced by mobile LiDAR.

  20. Key events and their effects on cycling behaviour in Dar-es-Salaam : abstract + powerpoint

    NARCIS (Netherlands)

    Nkurunziza, A.; Zuidgeest, M.H.P.; Brussel, M.J.G.; van Maarseveen, M.F.A.M.

    2012-01-01

    The paper explores key events and investigates their effects on cycling behaviour in the city of Dar-es-Salaam, Tanzania. The objective of the study is to identify specific key events during a person’s life course with a significant effect on change of travel behaviour towards cycling in relation to

  1. 2006 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Cumberland and York Counties, Maine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In the fall of 2006, Sanborn Map Company was contracted by Camp Dresser McKee, Inc (CDM) to execute a LiDAR (Light Detection and Ranging) survey campaign in the...

  2. International Journal of Arts and Humanities(IJAH) Bahir Dar- Ethiopia

    African Journals Online (AJOL)

    DrNneka

    International Journal of Arts and Humanities(IJAH). Bahir Dar- Ethiopia. Vol. 5(2), S/No 17, April, ... Commission's accreditation exercise on personnel in the business education programmes of the universities in the South-east .... education personnel in universities. Method. The study adopted descriptive survey design.

  3. Real-time surveillance system for marine environment based on HLIF LiDAR

    Science.gov (United States)

    Babichenko, Sergey; Sobolev, Innokenti; Aleksejev, Valeri; Sõro, Oliver

    2017-10-01

    The operational monitoring of the risk areas of marine environment requires cost-effective solutions. One of the options is the use of sensor networks based on fixed installations and moving platforms (coastal boats, supply-, cargo-, and passenger vessels). Such network allows to gather environmental data in time and space with direct links to operational activities in the controlled area for further environmental risk assessment. Among many remote sensing techniques the LiDAR (Light Detection And Ranging) based on Light Induced Fluorescence (LIF) is the tool of direct assessment of water quality variations caused by chemical pollution, colored dissolved organic matter, and phytoplankton composition. The Hyperspectral LIF (HLIF) LiDAR acquires comprehensive LIF spectra and analyses them by spectral pattern recognition technique to detect and classify the substances in water remotely. Combined use of HLIF LiDARs with Real-Time Data Management System (RTDMS) provides the economically effective solution for the regular monitoring in the controlled area. OCEAN VISUALS in cooperation with LDI INNOVATION has developed Oil in Water Locator (OWL™) with RTDMS (OWL MAP™) based on HLIF LiDAR technique. This is a novel technical solution for monitoring of marine environment providing continuous unattended operations. OWL™ has been extensively tested on board of various vessels in the North Sea, Norwegian Sea, Barents Sea, Baltic Sea and Caribbean Sea. This paper describes the technology features, the results of its operational use in 2014-2017, and outlook for the technology development.

  4. Validation of sentinel-1A SAR coastal wind speeds against scanning LiDAR

    DEFF Research Database (Denmark)

    Ahsbahs, Tobias Torben; Badger, Merete; Karagali, Ioanna

    2017-01-01

    for SAR wind retrieval are not fully validated here. Ground based scanning light detection and ranging (LiDAR) offer high horizontal resolution wind velocity measurements with high accuracy, also in the coastal zone. This study, for the first time, examines accuracies of SAR wind retrievals at 10 m height...... with respect to the distance to shore by validation against scanning LiDARs. Comparison of 15 Sentinel-1A wind retrievals using the GMF called C-band model 5.N (CMOD5.N) versus LiDARs show good agreement. It is found, when nondimenionalising with a reference point, that wind speed reductions are between 4......% and 8% from 3 km to 1 km from shore. Findings indicate that SAR wind retrievals give reliable wind speed measurements as close as 1 km to the shore. Comparisons of SAR winds versus two different LiDAR configurations yield root mean square error (RMSE) of 1.31 ms-1 and 1.42 ms-1 for spatially averaged...

  5. Patterns and correlates of solid waste disposal practices in Dar es ...

    African Journals Online (AJOL)

    This study examines the patterns and correlations of solid waste disposal practices among households in urbanized and populated Dar es Salaam city in Tanzania. The Tanzanian Household Budget Survey (HBS) data covering many households' characteristics was used. Multinomial Logit (MNL) model was applied to ...

  6. Post-Fire Changes in Forest Biomass Retrieved by Airborne LiDAR in Amazonia

    Science.gov (United States)

    Luciane Sato; Vitor Gomes; Yosio Shimabukuro; Michael Keller; Egidio Arai; Maiza dos-Santos; Irving Brown; Luiz Aragão

    2016-01-01

    Fire is one of the main factors directly impacting Amazonian forest biomass and dynamics. Because of Amazonia’s large geographical extent, remote sensing techniques are required for comprehensively assessing forest fire impacts at the landscape level. In this context, Light Detection and Ranging (LiDAR) stands out as a technology capable of retrieving direct...

  7. A LiDAR method of canopy structure retrieval for wind modeling of heterogeneous forests

    DEFF Research Database (Denmark)

    Boudreault, Louis-Etienne; Bechmann, Andreas; Taryainen, Lasse

    2015-01-01

    and this information is required for each grid point in the three-dimensional computational domain. By using raw data from aerial LiDAR scans together with the Beer-Lambert law, we propose and test a method to calculate and grid highly variable and realistic frontal area density input. An extensive comparison...

  8. Mapping snags and understory shrubs for LiDAR based assessment of wildlife habitat suitability

    Science.gov (United States)

    Sebastian Martinuzzi; Lee A. Vierling; William A. Gould; Michael J. Falkowski; Jeffrey S. Evans; Andrew T. Hudak; Kerri T. Vierling

    2009-01-01

    The lack of maps depicting forest three-dimensional structure, particularly as pertaining to snags and understory shrub species distribution, is a major limitation for managing wildlife habitat in forests. Developing new techniques to remotely map snags and understory shrubs is therefore an important need. To address this, we first evaluated the use of LiDAR data for...

  9. Into the third dimension: Benefits of incorporating LiDAR data in wildlife habitat models

    Science.gov (United States)

    Melissa J. Merrick; John L. Koprowski; Craig Wilcox

    2013-01-01

    LiDAR (Light detection and ranging) is a tool with potential for characterizing wildlife habitat by providing detailed, three-dimensional landscape information not available from other remote sensing applications. The ability to accurately map structural components such as canopy height, canopy cover, woody debris, tree density, and ground surface has potential to...

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

    Directory of Open Access Journals (Sweden)

    Marion W. Jenkins

    2015-02-01

    Full Text Available 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.

  11. planning for the automation of the university of dar es salaam library

    African Journals Online (AJOL)

    The paper examines the planning process for the automation of the University of Dar es Salaam Library. The planning phases described include the preparation phase, planning for implementation and database construction. The major issues during the preparation phase are the discussion on the context of automation, ...

  12. Modeling and mapping basal area of Pinus taeda L. plantation using airborne LiDAR data.

    Science.gov (United States)

    Silva, Carlos A; Klauberg, Carine; Hudak, Andrew T; Vierling, Lee A; Fennema, Scott J; Corte, Ana Paula D

    2017-01-01

    Basal area (BA) is a good predictor of timber stand volume and forest growth. This study developed predictive models using field and airborne LiDAR (Light Detection and Ranging) data for estimation of basal area in Pinus taeda plantation in south Brazil. In the field, BA was collected from conventional forest inventory plots. Multiple linear regression models for predicting BA from LiDAR-derived metrics were developed and evaluated for predictive power and parsimony. The best model to predict BA from a family of six models was selected based on corrected Akaike Information Criterion (AICc) and assessed by the adjusted coefficient of determination (adj. R²) and root mean square error (RMSE). The best model revealed an adj. R²=0.93 and RMSE=7.74%. Leave one out cross-validation of the best regression model was also computed, and revealed an adj. R² and RMSE of 0.92 and 8.31%, respectively. This study showed that LiDAR-derived metrics can be used to predict BA in Pinus taeda plantations in south Brazil with high precision. We conclude that there is good potential to monitor growth in this type of plantations using airborne LiDAR. We hope that the promising results for BA modeling presented herein will stimulate to operate this technology in Brazil.

  13. LiDAR Relative Reflectivity Surface (2011) for Fish Bay, St. John

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection & Ranging) 0.3x0.3 meter resolution relative seafloor reflectivity surface for Fish Bay, St. John in the U.S....

  14. Aboveground biomass estimation with airborne hyperspectral and LiDAR data in Tesinske Beskydy Mountains

    Czech Academy of Sciences Publication Activity Database

    Brovkina, Olga; Zemek, František; Fabiánek, Tomáš

    2015-01-01

    Roč. 8, č. 1 (2015), s. 35-46 ISSN 1803-2451 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk OC09001 Institutional support: RVO:67179843 Keywords : forest aboveground biomass * hyperspectral data * airborne LiDAR * Beskydy Mountains Subject RIV: EH - Ecology, Behaviour

  15. Interpersonal Conflicts and Styles of Managing Conflicts among Students at Bahir Dar University, Ethiopia

    Science.gov (United States)

    Bazezew, Arega; Neka, Mulugeta

    2017-01-01

    Interpersonal conflict happens everywhere and at any time and is inherent in all societies. However, the methods of managing such conflict are quite different from one organisation to the other. The general objective of the study was to assess interpersonal conflicts and styles of managing conflicts among students at Bahir Dar University.…

  16. Gender Equality and Equity at the University of Dar es Salaam ...

    African Journals Online (AJOL)

    This article examines the approaches and initiatives for gender equality and equity at the University of Dar es Salaam (UDSM). It argues that these approaches and initiatives are a reflection and a follow-up of gender equality and equity initiatives and strategies undertaken at global, regional, and national levels. However ...

  17. University of Dar es Salaam Library Journal - Vol 7, No 2 (2005)

    African Journals Online (AJOL)

    Library automation in Nigerian universities: a historical perspective · EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT ... Assessment of the use of information and communication technology in the improvement of performance and efficiency in the banking sector: a case study of the National Micro Finance Bank (NMB) Dar ...

  18. Linking rainforest ecophysiology and microclimate through fusion of airborne LiDAR and hyperspectral imagery

    Science.gov (United States)

    Eben N. Broadbent; Angélica M. Almeyda Zambrano; Gregory P. Asner; Christopher B. Field; Brad E. Rosenheim; Ty Kennedy-Bowdoin; David E. Knapp; David Burke; Christian Giardina; Susan Cordell

    2014-01-01

    We develop and validate a high-resolution three-dimensional model of light and air temperature for a tropical forest interior in Hawaii along an elevation gradient varying greatly in structure but maintaining a consistent species composition. Our microclimate models integrate high-resolution airborne waveform light detection and ranging data (LiDAR) and hyperspectral...

  19. 2014 U.S. Geological Survey CMGP LiDAR: Post Sandy (Pennsylvania)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Fugro EarthData, Inc. (Fugro) was tasked by the U.S. Geological Survey (USGS) to plan, acquire, process, and produce derivative products of LiDAR data at a nominal...

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

    Science.gov (United States)

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

    2012-08-07

    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.

  1. Coastal and tidal landform detection from high resolution topobathymetric LiDAR data

    DEFF Research Database (Denmark)

    Andersen, Mikkel S.; Al-Hamdani, Zyad K.; Steinbacher, Frank

    -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...

  2. Assessment of Ploidy and Genome Constitution of Some Musa balbisiana Cultivars using DArT Markers

    Czech Academy of Sciences Publication Activity Database

    Sales, E. K.; Butardo, N. G.; Paniagua, H. G.; Jansen, H.; Doležel, Jaroslav

    2011-01-01

    Roč. 36, č. 1 (2011), s. 11-18 ISSN 0115-463X Institutional research plan: CEZ:AV0Z50380511 Keywords : DArT * genome * Musa balbisiana Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 0.075, year: 2011 http://home.ueb.cas.cz/publikace/2011_Sales_PHILIPPINE_JOURNAL_OF_CROP_SCIENCE_11.pdf

  3. LiDAR Relative Reflectivity Surface (2011) for Coral Bay, St. John

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection & Ranging) 0.3x0.3 meter resolution relative seafloor reflectivity surface for Coral Bay, St. John in the U.S....

  4. Fast and nondestructive method for leaf level chlorophyll estimation using hyperspectral LiDAR

    NARCIS (Netherlands)

    Nevalainen, O.; Hakala, T.; Suomalainen, J.M.; Mäkipää, R.; Peltoniemi, M.; Krooks, A.; Kaasalainen, S.

    2014-01-01

    We propose an empirical method for nondestructive estimation of chlorophyll in tree canopies. The first prototype of a full waveform hyperspectral LiDAR instrument has been developed by the Finnish Geodetic Institute (FGI). The instrument efficiently combines the benefits of passive and active

  5. A comparison of two open source LiDAR surface classification algorithms

    Science.gov (United States)

    With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are op...

  6. Examining conifer canopy structural complexity across forest ages and elevations with LiDAR data

    Science.gov (United States)

    Van R. Kane; Jonathan D. Bakker; Robert J. McGaughey; James A. Lutz; Rolf F. Gersonde; Jerry F. Franklin

    2010-01-01

    LiDAR measurements of canopy structure can be used to classify forest stands into structural stages to study spatial patterns of canopy structure, identify habitat, or plan management actions. A key assumption in this process is that differences in canopy structure based on forest age and elevation are consistent with predictions from models of stand development. Three...

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

    Science.gov (United States)

    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…

  8. Analysis of airborne LiDAR surveys to quantify the characteristic morphologies of northern forested wetlands

    Science.gov (United States)

    Murray C. Richardson; Carl P. J. Mitchell; Brian A. Branfireun; Randall K. Kolka

    2010-01-01

    A new technique for quantifying the geomorphic form of northern forested wetlands from airborne LiDAR surveys is introduced, demonstrating the unprecedented ability to characterize the geomorphic form of northern forested wetlands using high-resolution digital topography. Two quantitative indices are presented, including the lagg width index (LWI) which objectively...

  9. 2010 U.S. Geological Survey (USGS) Topographic LiDAR: Mobile Bay, AL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — USGS Contract: G10PC00026 Task Order Number: G10PD00578 LiDAR was collected at a nominal pulse spacing of 2.0 meters for a 700 square mile area to the east of Mobile...

  10. Effect of Bahir Dar municipal effluents on water quality of the head of ...

    African Journals Online (AJOL)

    BOD5, conductivity and total alkalinity mean values were above permissible levels set for municipal effluents to be discharged to surface water. DO, BOD5 and total alkalinity mean values at head of Blue Nile River were lower than WHO recommended values for drinking water. The study concludes that the Bahir Dar ...

  11. Mobile hybrid LiDAR & infrared sensing for natural gas pipeline monitoring compendium.

    Science.gov (United States)

    2016-01-01

    This item consists of several documents that were created throughout the Mobile Hybrid LiDAR & Infrared Sensing for Natural Gas Pipeline Monitoring project, No. RITARS-14-H-RUT, which was conducted from January 15, 2014 to June 30, 2016. Documents in...

  12. Comparison of LiDAR- and photointerpretation-based estimates of canopy cover

    Science.gov (United States)

    Demetrios Gatziolis

    2012-01-01

    An evaluation of the agreement between photointerpretation- and LiDARbased estimates of canopy cover was performed using 397 90 x 90 m reference areas in Oregon. It was determined that at low canopy cover levels LiDAR estimates tend to exceed those from photointerpretation and that this tendency reverses at high canopy cover levels. Characteristics of the airborne...

  13. Multispectral LiDAR Data for Land Cover Classification of Urban Areas.

    Science.gov (United States)

    Morsy, Salem; Shaker, Ahmed; El-Rabbany, Ahmed

    2017-04-26

    Airborne Light Detection And Ranging (LiDAR) systems usually operate at a monochromatic wavelength measuring the range and the strength of the reflected energy (intensity) from objects. Recently, multispectral LiDAR sensors, which acquire data at different wavelengths, have emerged. This allows for recording of a diversity of spectral reflectance from objects. In this context, we aim to investigate the use of multispectral LiDAR data in land cover classification using two different techniques. The first is image-based classification, where intensity and height images are created from LiDAR points and then a maximum likelihood classifier is applied. The second is point-based classification, where ground filtering and Normalized Difference Vegetation Indices (NDVIs) computation are conducted. A dataset of an urban area located in Oshawa, Ontario, Canada, is classified into four classes: buildings, trees, roads and grass. An overall accuracy of up to 89.9% and 92.7% is achieved from image classification and 3D point classification, respectively. A radiometric correction model is also applied to the intensity data in order to remove the attenuation due to the system distortion and terrain height variation. The classification process is then repeated, and the results demonstrate that there are no significant improvements achieved in the overall accuracy.

  14. Shape Detection from Raw LiDAR Data with Subspace Modeling.

    Science.gov (United States)

    Wang, Jun; Xu, Kai

    2017-09-01

    LiDAR scanning has become a prevalent technique for digitalizing large-scale outdoor scenes. However, the raw LiDAR data often contain imperfections, e.g., missing large regions, anisotropy of sampling density, and contamination of noise and outliers, which are the major obstacles that hinder its more ambitious and higher level applications in digital city modeling. Observing that 3D urban scenes can be locally described with several low dimensional subspaces, we propose to locally classify the neighborhoods of the scans to model the substructures of the scenes. The key enabler is the adaptive kernel-scale scoring, filtering and clustering of substructures, making it possible to recover the local structures at all points simultaneously, even in the presence of severe data imperfections. Integrating the local analyses leads to robust shape detection from raw LiDAR data. On this basis, we develop several urban scene applications and verify them on a number of LiDAR scans with various complexities and styles, which demonstrates the effectiveness and robustness of our methods.

  15. ASTER GDEM validation using LiDAR data over coastal regions of Greenland

    DEFF Research Database (Denmark)

    Hvidegaard, Sine Munk; Sørensen, Louise Sandberg; Forsberg, René

    2011-01-01

    by a high spatial resolution of about 1 m and elevation accuracy of 20–30 cm root mean square error (RMSE). The LiDAR data sets used were acquired during ice-monitoring campaigns carried out from 2003 to 2008. The study areas include ice-free regions, local ice caps and the ice sheet margin. A linear error...

  16. Smoking among in-school adolescents in Dar es Salaam, Tanzania ...

    African Journals Online (AJOL)

    estimated frequencies and conducted logistic regression analysis to identify predictors of current .... cigarette smoking among high school students in 2003 in Dar es Salaam. Factor. Response. Total. Cigarette smokers. †OR (95% CI). ‡OR (95% CI). Sex ..... adolescents in Malaysia: a cross sectional Malaysian survey.

  17. Cannabis use among young people in Dar es Salaam, Tanzania: a ...

    African Journals Online (AJOL)

    The aim of this study was to explore the factors associated with initiation and continued use of cannabis among youths in Dar es salaam, Tanzania. The study employed an explorative qualitative design, using in-depth interviews. Purposive sampling and snowball techniques were used to obtain the study participants.

  18. Integrated analysis of light detection and ranging (LiDAR) and hyperspectral imagery (HSI) data

    Science.gov (United States)

    Kim, Angela M.; Kruse, Fred A.; Olsen, Richard C.

    2016-05-01

    LiDAR and hyperspectral data provide rich and complementary information about the content of a scene. In this work, we examine methods of data fusion, with the goal of minimizing information loss due to point-cloud rasterization and spatial-spectral resampling. Two approaches are investigated and compared: 1) a point-cloud approach in which spectral indices such as Normalized Difference Vegetation Index (NDVI) and principal components of the hyperspectral image are calculated and appended as attributes to each LiDAR point falling within the spatial extent of the pixel, and a supervised machine learning approach is used to classify the resulting fused point cloud; and 2) a raster-based approach in which LiDAR raster products (DEMs, DSMs, slope, height, aspect, etc) are created and appended to the hyperspectral image cube, and traditional spectral classification techniques are then used to classify the fused image cube. The methods are compared in terms of classification accuracy. LiDAR data and associated orthophotos of the NPS campus collected during 2012 - 2014 and hyperspectral Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data collected during 2011 are used for this work.

  19. GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD

    Directory of Open Access Journals (Sweden)

    P. Rashidi

    2017-09-01

    Full Text Available Separating point clouds into ground and non-ground points is a necessary step to generate digital terrain model (DTM from LiDAR dataset. In this research, a new method based on multi-scale analysis of height difference threshold is proposed for ground filtering of LiDAR data. The proposed method utilizes three windows with different sizes in small, average and large to cover the entire LiDAR point clouds, then with a height difference threshold, point clouds can be separated to ground and non-ground in each local window. Meanwhile, the best threshold values for size of windows are considered based on physical characteristics of the ground surface and size of objects. Also, the minimum of height of object in each window selected as height difference threshold. In order to evaluate the performance of the proposed algorithm, two datasets in rural and urban area were applied. The overall accuracy in rural and urban area was 96.06% and 94.88% respectively. These results of the filtering showed that the proposed method can successfully filters non-ground points from LiDAR point clouds despite of the data area.

  20. Implications of sensor configuration and topography on vertical plant profiles derived from terrestrial LiDAR

    NARCIS (Netherlands)

    Calders, K.; Armston, J.; Newnham, G.; Herold, M.; Goodwin, N.

    2014-01-01

    The vertical distribution of plant constituents is a key parameter to describe vegetation structure and influences several processes, such as radiation interception, growth and habitat. Terrestrial laser scanning (TLS), also referred to as terrestrial LiDAR, has the potential to measure the canopy

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

    Science.gov (United States)

    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…

  2. Childhood Burn Injuries in Children in Dar es Salaam: Patterns and ...

    African Journals Online (AJOL)

    A study was conducted in the three city hospitals of Dar es Salaam and two national referral hospitals to describe the pattern of burn injuries and to determine victims\\' and guardians\\' perceptions of the causes and prevention of burns. The study included all injured children younger than 18 years attending Mwananyamala, ...

  3. Smoking among in-school adolescents in Dar Es Salam, Tanzania ...

    African Journals Online (AJOL)

    Using data from the 2003 Dar es Salaam (Tanzania) Global Youth Tobacco Survey (GYTS), we assessed factors associated with current cigarette smoking among adolescents. We estimated frequencies and conducted logistic regression analysis to identify predictors of current cigarette smoking. Of the 1947 students ...

  4. Generalised small signal analysis of a DAR /Double Avalanche Region/ IMPATT diode

    Science.gov (United States)

    Datta, D. N.; Pal, B. B.

    1982-06-01

    A generalized small signal analysis of a DAR IMPATT diode is carried out using recent values of ionization rates and saturated drift velocities of electrons and holes for Si and GaAs taking both the drift and the diffusion of charge carriers into account. The results show similar discrete negative conductance frequency bands separated by positive conductance frequency bands for an asymmetrical structure as in the ideal case (Som et al., 1974), establishing that the harmonically related frequencies can be avoided in the Si DAR IMPATT diode. In contrast to the ideal case, however, the symmetrical DAR IMPATT here also exhibits finite negative conductance. The GaAs DAR IMPATT shows variations of negative conductance that are similar to those in Si at high frequencies (in the mm wave range); at the low frequency side (less than 1 GHz), however, the IMPATT gives uniform negative conductances unlike Si where the negative conductance comes only at higher frequencies. Consideration is given in the calculations to thin depletion layers (0.8, 1, and 2 microns) to show the usefulness of the device in the mm wave range.

  5. 2002 Maryland Department of Natural Resources LiDAR: Worcester County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) is a method of locating objects on the ground using aerial-borne equipment. It is similar to RADAR or SONAR in that the two-way...

  6. 2012-2013 U.S. Geological Survey LiDAR: Territory of Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Territory of Guam, LiDAR Task G11PD01189 This task order is for production of surface model products of The Territory of Guam. The models are produced from data...

  7. Airborne hyperspectral and LiDAR data integration for weed detection

    Science.gov (United States)

    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.

  8. The Dar es Salaam Seascape: A Case Study of an Environmental ...

    African Journals Online (AJOL)

    These pressures have resulted in substantial negative environmental state changes, e.g., habitat loss and degradation, biodiversity loss and disturbance of food webs, and coastal erosion/accretion. Thus, the Dar es Salaam seascape has become an environmental “hotspot” of degradation, with consequent negative ...

  9. A comparison of two open source LiDAR surface classification algorithms

    Science.gov (United States)

    Wade T. Tinkham; Hongyu Huang; Alistair M.S. Smith; Rupesh Shrestha; Michael J. Falkowski; Andrew T. Hudak; Timothy E. Link; Nancy F. Glenn; Danny G. Marks

    2011-01-01

    With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are openly available, free to use, and are supported by published results....

  10. Total canopy transmittance estimated from small-footprint, full-waveform airborne LiDAR

    Science.gov (United States)

    Milenković, Milutin; Wagner, Wolfgang; Quast, Raphael; Hollaus, Markus; Ressl, Camillo; Pfeifer, Norbert

    2017-06-01

    Canopy transmittance is a directional and wavelength-specific physical parameter that quantifies the amount of radiation attenuated when passing through a vegetation layer. The parameter has been estimated from LiDAR data in many different ways over the years. While early LiDAR methods treated each returned echo equally or weighted the echoes according to their return order, recent methods have focused more on the echo energy. In this study, we suggest a new method of estimating the total canopy transmittance considering only the energy of ground echoes. Therefore, this method does not require assumptions for the reflectance or absorption behavior of vegetation. As the oblique looking geometry of LiDAR is explicitly considered, canopy transmittance can be derived for individual laser beams and can be mapped spatially. The method was applied on a contemporary full-waveform LiDAR data set collected under leaf-off conditions and over a study site that contains two sub regions: one with a mixed (coniferous and deciduous) forest and another that is predominantly a deciduous forest in an alluvial plain. The resulting canopy transmittance map was analyzed for both sub regions and compared to aerial photos and the well-known fractional cover method. A visual comparison with aerial photos showed that even single trees and small canopy openings are visible in the canopy transmittance map. In comparison with the fractional cover method, the canopy transmittance map showed no saturation, i.e., there was better separability between patches with different vegetation structure.

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

    Directory of Open Access Journals (Sweden)

    Tingting Cui

    2016-12-01

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

  12. Prevalence and risk factors for obstructive sleep apnoea in Dar es ...

    African Journals Online (AJOL)

    Background: Obstructive sleep apnoea (OSA) is a common cause of daytime sleepiness, a condition associated with accidents, antisocial behaviour, mood disturbances, cognitive dysfunctions and inefficiency at work. This study was carried out to determine the prevalence and risk factors for obstructive sleep apnoea in Dar ...

  13. Dynamic Data Filtering of Long-Range Doppler LiDAR Wind Speed Measurements

    Directory of Open Access Journals (Sweden)

    Hauke Beck

    2017-06-01

    Full Text Available Doppler LiDARs have become flexible and versatile remote sensing devices for wind energy applications. The possibility to measure radial wind speed components contemporaneously at multiple distances is an advantage with respect to meteorological masts. However, these measurements must be filtered due to the measurement geometry, hard targets and atmospheric conditions. To ensure a maximum data availability while producing low measurement errors, we introduce a dynamic data filter approach that conditionally decouples the dependency of data availability with increasing range. The new filter approach is based on the assumption of self-similarity, that has not been used so far for LiDAR data filtering. We tested the accuracy of the dynamic data filter approach together with other commonly used filter approaches, from research and industry applications. This has been done with data from a long-range pulsed LiDAR installed at the offshore wind farm ‘alpha ventus’. There, an ultrasonic anemometer located approximately 2.8 km from the LiDAR was used as reference. The analysis of around 1.5 weeks of data shows, that the error of mean radial velocity can be minimised for wake and free stream conditions.

  14. Lead pollution in urban roadside environments of Dar es Salaam city

    African Journals Online (AJOL)

    Lead is among the most toxic elements in nature. It is non-biodegradable and its toxicity does not change with time. Use of leaded gasoline in motor vehicles is known as the major source of lead pollution in cities in the world. Dar es Salaam, the main city of Tanzania, has thousands of cars traveling along its roads. The lead ...

  15. Land Cover Classification Accuracy Assessment Using Full-Waveform LiDAR Data

    Directory of Open Access Journals (Sweden)

    Kuan-Tsung Chang

    2015-01-01

    Full Text Available The geomorphology of Taiwan is characterized by marked changes in terrain, geological fractures, and frequent natural disasters. Because of sustained economic growth, urbanization and land development, the land cover in Taiwan has undergone frequent use changes. Among the various technologies for monitoring changes in land cover, remote sensing technologies, such as LiDAR, are efficient tools for collecting a broad range of spectral and spatial data. Two types of airborne LiDAR systems exist; full-waveform (FW LiDAR and traditional discrete-echo LiDAR. Because reflected waveforms are affected by the land object material type and properties, the waveform features can be applied to analyze the characteristics specifically associated with land-cover classification (LCC. Five types of land cover that characterize the volcanic Guishan Island were investigated. The automatic LCC method was used to elucidate the spectral, geomorphometric and textural characteristics. Interpretation keys accompanied by additional information were extracted from the FW LiDAR data for subsequent statistical and separation analyses. The results show that the Gabor texture and geomorphometric features, such as the normalized digital surface model (nDSM and slopes can enhance the overall LCC accuracy to higher than 90%. Moreover, both the producer and user accuracy can be higher than 92% for forest and built-up types using amplitude and pulse width. Although the waveform characteristics did not perform as well as anticipated due to the waveform data sampling rate, the data provides suitable training samples for testing the waveform feature effects.

  16. Building Change Detection Using Old Aerial Images and New LiDAR Data

    Directory of Open Access Journals (Sweden)

    Shouji Du

    2016-12-01

    Full Text Available Building change detection is important for urban area monitoring, disaster assessment and updating geo-database. 3D information derived from image dense matching or airborne light detection and ranging (LiDAR is very effective for building change detection. However, combining 3D data from different sources is challenging, and so far few studies have focused on building change detection using both images and LiDAR data. This study proposes an automatic method to detect building changes in urban areas using aerial images and LiDAR data. First, dense image matching is carried out to obtain dense point clouds and then co-registered LiDAR point clouds using the iterative closest point (ICP algorithm. The registered point clouds are further resampled to a raster DSM (Digital Surface Models. In a second step, height difference and grey-scale similarity are calculated as change indicators and the graph cuts method is employed to determine changes considering the contexture information. Finally, the detected results are refined by removing the non-building changes, in which a novel method based on variance of normal direction of LiDAR points is proposed to remove vegetated areas for positive building changes (newly building or taller and nEGI (normalized Excessive Green Index is used for negative building changes (demolish building or lower. To evaluate the proposed method, a test area covering approximately 2.1 km2 and consisting of many different types of buildings is used for the experiment. Results indicate 93% completeness with correctness of 90.2% for positive changes, while 94% completeness with correctness of 94.1% for negative changes, which demonstrate the promising performance of the proposed method.

  17. Development and mapping of DArT markers within the Festuca - Lolium complex

    Directory of Open Access Journals (Sweden)

    Studer Bruno

    2009-10-01

    Full Text Available Abstract Background Grasses are among the most important and widely cultivated plants on Earth. They provide high quality fodder for livestock, are used for turf and amenity purposes, and play a fundamental role in environment protection. Among cultivated grasses, species within the Festuca-Lolium complex predominate, especially in temperate regions. To facilitate high-throughput genome profiling and genetic mapping within the complex, we have developed a Diversity Arrays Technology (DArT array for five grass species: F. pratensis, F. arundinacea, F. glaucescens, L. perenne and L. multiflorum. Results The DArTFest array contains 7680 probes derived from methyl-filtered genomic representations. In a first marker discovery experiment performed on 40 genotypes from each species (with the exception of F. glaucescens for which only 7 genotypes were used, we identified 3884 polymorphic markers. The number of DArT markers identified in every single genotype varied from 821 to 1852. To test the usefulness of DArTFest array for physical mapping, DArT markers were assigned to each of the seven chromosomes of F. pratensis using single chromosome substitution lines while recombinants of F. pratensis chromosome 3 were used to allocate the markers to seven chromosome bins. Conclusion The resources developed in this project will facilitate the development of genetic maps in Festuca and Lolium, the analysis on genetic diversity, and the monitoring of the genomic constitution of the Festuca × Lolium hybrids. They will also enable marker-assisted selection for multiple traits or for specific genome regions.

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

    Science.gov (United States)

    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.

  19. Estimating Stand Volume and Above-Ground Biomass of Urban Forests Using LiDAR

    Directory of Open Access Journals (Sweden)

    Vincenzo Giannico

    2016-04-01

    Full Text Available Assessing forest stand conditions in urban and peri-urban areas is essential to support ecosystem service planning and management, as most of the ecosystem services provided are a consequence of forest stand characteristics. However, collecting data for assessing forest stand conditions is time consuming and labor intensive. A plausible approach for addressing this issue is to establish a relationship between in situ measurements of stand characteristics and data from airborne laser scanning (LiDAR. In this study we assessed forest stand volume and above-ground biomass (AGB in a broadleaved urban forest, using a combination of LiDAR-derived metrics, which takes the form of a forest allometric model. We tested various methods for extracting proxies of basal area (BA and mean stand height (H from the LiDAR point-cloud distribution and evaluated the performance of different models in estimating forest stand volume and AGB. The best predictors for both models were the scale parameters of the Weibull distribution of all returns (except the first (proxy of BA and the 95th percentile of the distribution of all first returns (proxy of H. The R2 were 0.81 (p < 0.01 for the stand volume model and 0.77 (p < 0.01 for the AGB model with a RMSE of 23.66 m3·ha−1 (23.3% and 19.59 Mg·ha−1 (23.9%, respectively. We found that a combination of two LiDAR-derived variables (i.e., proxy of BA and proxy of H, which take the form of a forest allometric model, can be used to estimate stand volume and above-ground biomass in broadleaved urban forest areas. Our results can be compared to other studies conducted using LiDAR in broadleaved forests with similar methods.

  20. BUILDING DAMAGE ASSESSMENT AFTER EARTHQUAKE USING POST-EVENT LiDAR DATA

    Directory of Open Access Journals (Sweden)

    H. Rastiveis

    2015-12-01

    Full Text Available 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.

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

    Science.gov (United States)

    Onojeghuo, Alex Okiemute; Onojeghuo, Ajoke Ruth

    2017-07-01

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

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

    Science.gov (United States)

    Liu, Wanli

    2017-03-08

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

  3. Darüşşifas Where Music Threapy was Practiced During Anatolian Seljuks and Ottomans

    Directory of Open Access Journals (Sweden)

    Gülşen Erdal

    2013-03-01

    Full Text Available AbstractMusic therapy, one of the oldest treatment methods known, dates back to thousands of years. Turks’ using music therapy practices in hospitals -Ottoman and Seljuk hospitals- built with appropriate acoustic in the treatment of mental disorders, utilizing the books which included the researches done by scientists such as İbni Sina, Razî, Farabî, Hasan Şuurî and in Gevrekzade Hasan Efendi in music therapy and improving music therapy practices exemplarily in the period of Ottomans and Seljukians is assessed as the first serious music therapy practices. Darüşşifa is one of the names given to medical and educational establishments which give people health service depending on practice and observation and treated patients in Turkish and Islamic world. Turks started various reconstruction activities following their settlement in Anatolia. Within a short period, they built several types of artifacts such as; caravansaries, madrasahs, mosques, darüşşifas. In Seljukian and Ottoman darüşşifas, medical subjects were taught according to researches and scientific principals, and surgeons were educated at medical madrasahs as well. Medical health care service was provided in those places. In this study, of darüşşifas where music therapy was practised the ones surviving today and having importance have been analyzed so as to emphasize how curative power of art history and music was used by Turkish people centuries ago. From this point of view, Kayseri Gevher Nesibe Tıp Medresesi (Medical madrasah (1206, Divriği Ulu Camii ve Darüşşifası (Mosque and Hospital (1228, Amasya Darüşşifası (1309, Fatih Darüşşifası (1470 Edirne Sultan II. Bayezid Darüşşifası (1488, Süleymaniye Tıp Medresesi and Şifahanesi (Medical Madrasah and Hospital (1556 have been examined in this study as the featured ones among the institutions where music therapy was practised.ÖzetMüziğin insanlar üzerinde bıraktığı psikolojik ve fiziksel etki

  4. Rapid, high-resolution measurement of leaf area and leaf orientation using terrestrial LiDAR scanning data

    International Nuclear Information System (INIS)

    Bailey, Brian N; Mahaffee, Walter F

    2017-01-01

    The rapid evolution of high performance computing technology has allowed for the development of extremely detailed models of the urban and natural environment. Although models can now represent sub-meter-scale variability in environmental geometry, model users are often unable to specify the geometry of real domains at this scale given available measurements. An emerging technology in this field has been the use of terrestrial LiDAR scanning data to rapidly measure the three-dimensional geometry of trees, such as the distribution of leaf area. However, current LiDAR methods suffer from the limitation that they require detailed knowledge of leaf orientation in order to translate projected leaf area into actual leaf area. Common methods for measuring leaf orientation are often tedious or inaccurate, which places constraints on the LiDAR measurement technique. This work presents a new method to simultaneously measure leaf orientation and leaf area within an arbitrarily defined volume using terrestrial LiDAR data. The novelty of the method lies in the direct measurement of the fraction of projected leaf area G from the LiDAR data which is required to relate projected leaf area to total leaf area, and in the new way in which radiation transfer theory is used to calculate leaf area from the LiDAR data. The method was validated by comparing LiDAR-measured leaf area to (1) ‘synthetic’ or computer-generated LiDAR data where the exact area was known, and (2) direct measurements of leaf area in the field using destructive sampling. Overall, agreement between the LiDAR and reference measurements was very good, showing a normalized root-mean-squared-error of about 15% for the synthetic tests, and 13% in the field. (paper)

  5. An example for the application of music therapy in the medical history: Divrigi Darüssifa

    Directory of Open Access Journals (Sweden)

    Selim Bedri Benek

    2015-05-01

    Full Text Available The Seljuks built up so many medical buildings and darüssifas in lots of cities, and gave importance to medicina as well as the other branches of science. They provided great contributions to the development of modern medicine with darüssifas and medical centers by the treatment they applied as well as health care. Music therapy was applied with certain methods in these health centers where mental and spiritual diseases were tried to be treated. Sivas Divrigi Darüssifa, amongst the first ones in this concept and continued its existence until today, has an important place in terms of our medical history.

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

    Science.gov (United States)

    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 (judged by our team to warrant removal from the database due to incorrect feature reconstruction; and 6) significant variability in both accuracy of LiDAR offset

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

    Science.gov (United States)

    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 (??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 (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 Arctic river delta water surface and hydraulic attributes that would be challenging to acquire by other means. ?? 2011 John Wiley & Sons, Ltd.

  8. Evaluation of hyperspectral LiDAR for monitoring rice leaf nitrogen by comparison with multispectral LiDAR and passive spectrometer

    Science.gov (United States)

    Sun, Jia; Shi, Shuo; Gong, Wei; Yang, Jian; Du, Lin; Song, Shalei; Chen, Biwu; Zhang, Zhenbing

    2017-01-01

    Fast and nondestructive assessment of leaf nitrogen concentration (LNC) is critical for crop growth diagnosis and nitrogen management guidance. In the last decade, multispectral LiDAR (MSL) systems have promoted developments in the earth and ecological sciences with the additional spectral information. With more wavelengths than MSL, the hyperspectral LiDAR (HSL) system provides greater possibilities for remote sensing crop physiological conditions. This study compared the performance of ASD FieldSpec Pro FR, MSL, and HSL for estimating rice (Oryza sativa) LNC. Spectral reflectance and biochemical composition were determined in rice leaves of different cultivars (Yongyou 4949 and Yangliangyou 6) throughout two growing seasons (2014-2015). Results demonstrated that HSL provided the best indicator for predicting rice LNC, yielding a coefficient of determination (R2) of 0.74 and a root mean square error of 2.80 mg/g with a support vector machine, similar to the performance of ASD (R2 = 0.73). Estimation of rice LNC could be significantly improved with the finer spectral resolution of HSL compared with MSL (R2 = 0.56).

  9. Automated Extraction of 3D Trees from Mobile LiDAR Point Clouds

    Directory of Open Access Journals (Sweden)

    Y. Yu

    2014-06-01

    Full Text Available This paper presents an automated algorithm for extracting 3D trees directly from 3D mobile light detection and ranging (LiDAR data. To reduce both computational and spatial complexities, ground points are first filtered out from a raw 3D point cloud via blockbased elevation filtering. Off-ground points are then grouped into clusters representing individual objects through Euclidean distance clustering and voxel-based normalized cut segmentation. Finally, a model-driven method is proposed to achieve the extraction of 3D trees based on a pairwise 3D shape descriptor. The proposed algorithm is tested using a set of mobile LiDAR point clouds acquired by a RIEGL VMX-450 system. The results demonstrate the feasibility and effectiveness of the proposed algorithm.

  10. High resolution, topobathymetric LiDAR coastal zone characterization in Denmark

    DEFF Research Database (Denmark)

    Steinbacher, Frank; Baran, Ramona; Andersen, Mikkel S.

    2016-01-01

    , the vegetation and the water column in land-water transition zones like rivers, lakes, wetlands, estuaries and coasts; (ii) improve the understanding of the dynamics of these properties in shallow water ecosystems, which are under pressure due to changing environmental conditions driven by climate change......-resolution mapping of these land-water transition zones. We have carried out topobathymetric LiDAR surveys in the Knudedyb tidal inlet system in the Danish Wadden Sea and the Rødsand lagoon connected to Fehmarnbelt. The overall aims are to: (i) derive characteristic properties of the morphology, surface sediment...... locations with different environmental settings. We demonstrate the potential of using airborne topobathymetric LiDAR for seamless mapping of land-water transition zones in challenging coastal environments, e.g. in an environment with high water column turbidity and continuously varying water levels due...

  11. Comparison of Signal Extraction Method for Airborne LiDAR Bathymetry Based on Deconvolution

    Directory of Open Access Journals (Sweden)

    WANG Dandi

    2018-02-01

    Full Text Available To improve the extraction accuracy for airborne LiDAR bathymetry,a signal extraction method based on deconvolution is introduced in waveform processing in this paper.The received waveform is preprocessed by deconvolution,and the accurate positions of the LiDAR signals are determined by the peak detection.For the deconvolution,the validity of four common algorithms,namely,Wiener filter deconvolution,nonnegative least squares,Richardson-Lucy deconvolution and blind deconvolution,are comparatively studied and the performance of the proposed method is assessed by the defined metrics.The experimental results show that the Richardson-Lucy deconvolution can effectively recover the signal resolution with wide adaptation and high success rate.The proposed method compared to the traditional peak detection methods offers a higher detection rate and accuracy and a wider range of bathymetry.

  12. Determinants of acceptance of cervical cancer screening in Dar es Salaam, Tanzania

    DEFF Research Database (Denmark)

    Kahesa, Crispin; Kjaer, Susanne; Mwaiselage, Julius

    2012-01-01

    ABSTRACT: OBJECTIVE: To describe how demographic characteristics and knowledge of cervical cancer influence screening acceptance among women living in Dar es Salaam, Tanzania. METHODS: Multistage cluster sampling was carried out in 45 randomly selected streets in Dar es Salaam. Women between...... the ages of 25--59 who lived in the sampled streets were invited to a cervical cancer screening; 804 women accepted and 313 rejected the invitation. Information on demographic characteristics and knowledge of cervical cancer were obtained through structured questionnaire interviews. RESULTS: Women aged 35...... to accept screening in comparison with women who had five or more children (ORs 3.21). Finally, knowledge of cervical cancer and awareness of the existing screening program were also associated with increased acceptance rates (ORs of 5.90 and 4.20). CONCLUSION: There are identifiable subgroups where...

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

    Science.gov (United States)

    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.

  14. Comparative study of building footprint estimation methods from LiDAR point clouds

    Science.gov (United States)

    Rozas, E.; Rivera, F. F.; Cabaleiro, J. C.; Pena, T. F.; Vilariño, D. L.

    2017-10-01

    Building area calculation from LiDAR points is still a difficult task with no clear solution. Their different characteristics, such as shape or size, have made the process too complex to automate. However, several algorithms and techniques have been used in order to obtain an approximated hull. 3D-building reconstruction or urban planning are examples of important applications that benefit of accurate building footprint estimations. In this paper, we have carried out a study of accuracy in the estimation of the footprint of buildings from LiDAR points. The analysis focuses on the processing steps following the object recognition and classification, assuming that labeling of building points have been previously performed. Then, we perform an in-depth analysis of the influence of the point density over the accuracy of the building area estimation. In addition, a set of buildings with different size and shape were manually classified, in such a way that they can be used as benchmark.

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

    Science.gov (United States)

    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.

  16. Contour Cluster Shape Analysis for Building Damage Detection from Post-earthquake Airborne LiDAR

    Directory of Open Access Journals (Sweden)

    HE Meizhang

    2015-04-01

    Full Text Available Detection of the damaged building is the obligatory step prior to evaluate earthquake casualty and economic losses. It's very difficult to detect damaged buildings accurately based on the assumption that intact roofs appear in laser data as large planar segments whereas collapsed roofs are characterized by many small segments. This paper presents a contour cluster shape similarity analysis algorithm for reliable building damage detection from the post-earthquake airborne LiDAR point cloud. First we evaluate the entropies of shape similarities between all the combinations of two contour lines within a building cluster, which quantitatively describe the shape diversity. Then the maximum entropy model is employed to divide all the clusters into intact and damaged classes. The tests on the LiDAR data at El Mayor-Cucapah earthquake rupture prove the accuracy and reliability of the proposed method.

  17. Canopy Height and Biomass from LiDAR Surveys at La Selva, Costa Rica, 1998 and 2005

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains land-use, canopy height, and aboveground carbon estimates derived from LiDAR data collected at La Selva Biological Station in Costa Rica in...

  18. 2007 Oregon Department of Geology and Mineral Industries (DoGAMI) LiDAR: Northwest Oregon and Portland Metro Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. collected Light Detection and Ranging (LiDAR) data for the Oregon Department of Geology and Mineral Industries (DoGAMI) and the Oregon...

  19. Urban Classification Techniques Using the Fusion of LiDAR and Spectral Data

    Science.gov (United States)

    2012-09-01

    area of interest, San Francisco , California. A. LIGHT DETECTION AND RANGING 1. LiDAR Fundamentals Light detection and...CALIFORNIA The study area for this project was San Francisco California. San Francisco is located in northern California near where the Pacific Ocean...meets the San Francisco Bay and Golden Gate strait. It is situated at about North 37.759880 latitude and West 122.437393 longitude. The area of

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

    Science.gov (United States)

    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.

  1. Mapping Spartina alterniflora Biomass Using LiDAR and Hyperspectral Data

    Directory of Open Access Journals (Sweden)

    Jing Wang

    2017-06-01

    Full Text Available Large-scale coastal reclamation has caused significant changes in Spartina alterniflora (S. alterniflora distribution in coastal regions of China. However, few studies have focused on estimation of the wetland vegetation biomass, especially of S. alterniflora, in coastal regions using LiDAR and hyperspectral data. In this study, the applicability of LiDAR and hypersectral data for estimating S. alterniflora biomass and mapping its distribution in coastal regions of China was explored to attempt problems of wetland vegetation biomass estimation caused by different vegetation types and different canopy height. Results showed that the highest correlation coefficient with S. alterniflora biomass was vegetation canopy height (0.817, followed by Normalized Difference Vegetation Index (NDVI (0.635, Atmospherically Resistant Vegetation Index (ARVI (0.631, Visible Atmospherically Resistant Index (VARI (0.599, and Ratio Vegetation Index (RVI (0.520. A multivariate linear estimation model of S. alterniflora biomass using a variable backward elimination method was developed with R squared coefficient of 0.902 and the residual predictive deviation (RPD of 2.62. The model accuracy of S. alterniflora biomass was higher than that of wetland vegetation for mixed vegetation types because it improved the estimation accuracy caused by differences in spectral features and canopy heights of different kinds of wetland vegetation. The result indicated that estimated S. alterniflora biomass was in agreement with the field survey result. Owing to its basis in the fusion of LiDAR data and hyperspectral data, the proposed method provides an advantage for S. alterniflora mapping. The integration of high spatial resolution hyperspectral imagery and LiDAR data derived canopy height had significantly improved the accuracy of mapping S. alterniflora biomass.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  4. NASA Goddard’s LiDAR, Hyperspectral and Thermal (G-LiHT Airborne Imager

    Directory of Open Access Journals (Sweden)

    Vuong Ly

    2013-08-01

    Full Text Available 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 (~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.

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

    Science.gov (United States)

    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

  6. Intestinal Parasitic Infections in Bahir Dar and Risk Factors for Transmission

    OpenAIRE

    Erko, Berhanu; Medhin, Girmay; Birrie, Hailu

    1995-01-01

    A study of intestinal parasites and assessment of transmission factors were made in Bahir Dar town, northwestern Ethiopia. Out of 528 children examined by formolether concentration method over 95 % were found to harbour one or more intestinal parasites. Human behaviour and poor sanitary conditions appeared to be responsible for the transmission of geohelminths, faeco-orally transmitted amoebae and water-related schistosome parasites. Health education is suggested to play a vital role in the c...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2012-01-01

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

  9. An approach to conifer stem localization and modeling in high density airborne LiDAR data

    Science.gov (United States)

    Harikumar, A.; Bovolo, F.; Bruzzone, L.

    2017-10-01

    Individual tree level inventory performed using high density multi-return airborne Light Detection and Ranging (LiDAR) systems provides both internal and external geometric details on individual tree crowns. Among them, the parameters such as, the stem location, and Diameter at Breast Height of the stem (DBH) are very relevant for accurate biomass, and forest growth estimation. However, methods that can accurately estimate these parameters along the vertical canopy are lacking in the state of the art. Thus, we propose a method to locate and model the stem by analyzing the empty volume that appears within the 3D high density LiDAR point cloud of a conifer, due to the stem. In a high LiDAR density data, the points most proximal to the stem location in the upper half of the crown are very likely due to laser reflections from the stem and/or the branch-stem junctions. By locating accurately these points, we can define the lattice of points representing branch-stem junctions and use it to model the empty volume associated to the stem location. We identify these points by using a state-of-the-art internal crown structure modelling technique that models individual conifer branches in a high density LiDAR data. Under the assumption that conifer stem can be closely modelled using a cone shape, we regression fit a geometric shape onto the lattice of branch-stem junction points. The parameters of the geometric shape are used to accurately estimate the diameter at breast height, and height of the tree. The experiments were performed on a set of hundred conifers consisting of trees from six dominant European conifer species, for which the height and the DBH were known. The results prove the method to be accurate.

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

    Science.gov (United States)

    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

  11. LiDAR-based Prediction of Arthropod Abundance at the Southern Slopes of Mt. Kilimanjaro

    Science.gov (United States)

    Ziegler, Alice

    2017-04-01

    LiDAR (Light Detection And Ranging) is a remote sensing technology that offers high-resolution three-dimensional information about the covered area. These three-dimensional datasets were used in this work to derive structural parameters of the vegetation to predict the abundance of eight different arthropod assemblages with several models. For the model training of each arthropod assemblage, different versions (extent, filters) of the LiDAR datasets were provided and evaluated. Furthermore the importance of each of the LiDAR-derived structural parameters for each model was calculated. The best input dataset and structural parameters were used for the prediction of the abundance of arthropod assemblages. The analyses of the prediction results across seven different landuse types and the eight arthropod assemblages exposed, that for the arthropod assemblages, LiDAR-based predictions were in general best feasible for "Orthoptera" (average R2 (coefficient of determination) over all landuses: 0.14), even though the predictions for the other arthropod assemblages reached values of the same magnitude. It was also found that the landuse type "disturbed forest" showed the best results (average R2 over all assemblages: 0.20), whereas "home garden" was the least predictable (average R2 over all assemblages: 0.04). Differenciated by arthropod-landuse pairs, the results showed distinct differences and the R2 values diverged clearly. It was shown, that when model settings were optimized for only one arthropod taxa, values for R2 could reach values up to 0.55 ("Orthoptera" in "disturbed forest"). The analysis of the importance of each structural parameter for the prediction revealed that about one third of the 18 used parameters were always among the most important ones for the prediction of all assemblages. This strong ranking of parameters implied that focus for further research needs to be put on the selection of predictor variables.

  12. Risk factors associated with pre-term birth in Dar es Salaam ...

    African Journals Online (AJOL)

    ... p-value 0.004), cervical incompetence (AOR = 11.6; 95%CI 1.1-121.5; p-value 0.04), polyhydramnios (AOR = 8.3; 95%CI 1.7-40.2; p-value 0.008), and lack of antenatal visits (AOR = 5.1; 95%CI 1.4-17.8; p-value 0.042).Conclusion: This study has identified several risk factors for preterm birth in the city of Dar es Salaam.

  13. Towards sustainable ground water management in Dar Es Salaam city, Tanzania

    International Nuclear Information System (INIS)

    Mato, R.R.A.M.

    2005-01-01

    Groundwater pollution in urban areas is a worldwide growing environmental problem in this millennium. Many major cities in the world depend on groundwater for water supplies. However, urbanization processes threaten its quality. The problem is more pronounced in urban areas in developing countries like Tanzania, which are characterized with inadequate infrastructure for waste management. In Tanzania, the situation is more threatening in Dar Es Salaam City, which experiences acute deficiency in infrastructure provision: housing, water supply, sanitation, transportation and energy. The existing challenge is to protect groundwater resources amidst rapid growing Dar Es Salaam city, of which failure can lead to escalating costs for provision of drinking water with overall results of decreased public health conditions. A research conducted from 1997 to 2002, revealed that almost 50% of the water supply in Dar Es Salaam city comes from groundwater and that groundwater is being threatened by indiscriminate disposal practices of both domestic and industrial wastes. For example about 88% of the urban population use on-site sanitation systems, which discharge partially treated sewage to the groundwater. About 60 tonnes/day of chemical oxygen demand (COD) are transported to the groundwater through domestic sewage. Analysis of groundwater quality in the city indicated that the unconfined aquifer is starting to degrade. For instance, more than 40% of groundwater samples analysed for nitrate, chloride and faecal coliform bacteria, did not comply with the national standards for drinking water. Recognising the fact that demand for groundwater is on the increase in the city and that the aquifers have shown signs of degradation, a groundwater management plan is required to ensure sustainable utilization of the resource. This paper discusses the groundwater situation in Dar Es Salaam city and finally puts forward measures towards establishment of a management strategy. (author)

  14. True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An Update

    Directory of Open Access Journals (Sweden)

    Hamid Gharibi

    2018-04-01

    Full Text Available Image spectral and Light Detection and Ranging (LiDAR positional information can be related through the orthophoto generation process. Orthophotos have a uniform scale and represent all objects in their correct planimetric locations. However, orthophotos generated using conventional methods suffer from an artifact known as the double-mapping effect that occurs in areas occluded by tall objects. The double-mapping problem can be resolved through the commonly known true orthophoto generation procedure, in which an occlusion detection process is incorporated. This paper presents a review of occlusion detection methods, from which three techniques are compared and analyzed using experimental results. The paper also describes a framework for true orthophoto production based on an angle-based occlusion detection method. To improve the performance of the angle-based technique, two modifications to this method are introduced. These modifications, which aim at resolving false visibilities reported within the angle-based occlusion detection process, are referred to as occlusion extension and radial section overlap. A weighted averaging approach is also proposed to mitigate the seamline effect and spectral dissimilarity that may appear in true orthophoto mosaics. Moreover, true orthophotos generated from high-resolution aerial images and high-density LiDAR data using the updated version of angle-based methodology are illustrated for two urban study areas. To investigate the potential of image matching techniques in producing true orthophotos and point clouds, a comparison between the LiDAR-based and image-matching-based true orthophotos and digital surface models (DSMs for an urban study area is also presented in this paper. Among the investigated occlusion detection methods, the angle-based technique demonstrated a better performance in terms of output and running time. The LiDAR-based true orthophotos and DSMs showed higher qualities compared to their

  15. La Argentina del Centenario en Mundial magazine de Rubén Darío

    Directory of Open Access Journals (Sweden)

    Alejandra Torres

    2010-11-01

    Full Text Available A variety of texts about Latin American Republics are published in the illustrated Mundial Magazine, directed by Rubén Darío. During the commemoration of the 9th of July 1911, in the spirit of the centenary, the poet publishes the chronicle "República Argentina" with seventeen photographies. In this piece of work the relationship between text and photos concerning the ruling class of Argentina of those years will be analized

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

    Science.gov (United States)

    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.

  17. IsoDAR@KamLAND:A Conceptual Design Report for the Conventional Facilities arXiv

    CERN Document Server

    Alonso, Jose R.

    This document describes requirements for the caverns to house the cyclotron, beam transport line, and target systems; issues associated with transport and assembly of components on the site; electrical power, cooling and ventilation; as well as issues associated with radiation protection of the environment and staff of KamLAND who will be interfacing with IsoDAR during its operational phases. Specifics of IsoDAR operations at the KamLAND site are not addressed. Recent developments in planning for deployment of IsoDAR include the identification of a potential new site for the experiment, where the target can be placed directly on the equatorial plane of the KamLAND detector, and also, an upgrade of the detector resolution to 3\\%/$\\sqrt{E(MeV)}$. The option of the new site might allow, depending on the results of shielding and background evaluations in KamLAND, for an increase in event rate by about a factor of 1.6 owing to increased solid angle for the detector, improving the physics reach for a same period of...

  18. Data-Driven Approach to Benthic Cover Type Classification Using Bathymetric LiDAR Waveform Analysis

    Directory of Open Access Journals (Sweden)

    Teemu Kumpumäki

    2015-10-01

    Full Text Available A data-driven method for describing the benthic cover type based on full-waveform bathymetric LiDAR data analysis is presented. The waveform of the bathymetric LiDAR return pulse is first modeled as a sum of three functions: a Gaussian pulse representing the surface return, a function modeling the backscatter and another Gaussian pulse modeling the return from the bottom surface. Two sets of variables are formed: one containing features describing the bottom return and the other describing various conditions, such as water quality and the depth of the seabed. Regression analysis is used to eliminate the effect of the condition variables on the features, after which the features are mapped onto a cell lattice using a self-organizing map (SOM. The cells of the SOM are grouped into seven clusters using the neighborhood distance matrix method. The clustering result is evaluated using the seabed substrate map based on sonar measurements, as well as delineation of photic zones in the study area. High correspondence between the clusters and the substrate type/photic zone has been obtained indicating that the proposed clustering method adequately describes the benthic cover in the study area. The bottom return pulse waveforms corresponding to the clusters and a cluster map of the study area are also presented. The method can be used for clustering full waveform bathymetric LiDAR data acquired from large areas to discover the structure of benthic cover types and to focus the field studies accordingly.

  19. Phylogenetic Relationships between Four Salix L. Species Based on DArT Markers

    Directory of Open Access Journals (Sweden)

    Jerzy A. Przyborowski

    2013-12-01

    Full Text Available 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.

  20. High-Density LiDAR Mapping of the Ancient City of Mayapán

    Directory of Open Access Journals (Sweden)

    Timothy Hare

    2014-09-01

    Full Text Available A 2013 survey of a 40 square kilometer area surrounding Mayapán, Yucatan, Mexico used high-density LiDAR data to map prehispanic architecture and related natural features. Most of the area is covered by low canopy dense forest vegetation over karstic hilly terrain that impedes full coverage archaeological survey. We used LiDAR at 40 laser points per square meter to generate a bare earth digital elevation model (DEM. Results were evaluated with comparisons to previously mapped areas and with traditional archaeological survey methods for 38 settlement clusters outside of the city wall. Ground checking employed full coverage survey of selected 500 m grid squares, as well as documentation of the chronology and detail of new public and domestic settlement features and cenotes. Results identify the full extent of continued, contemporary Postclassic settlement (A.D. 1150–1450 outside of the city wall to at least 500 meters to the east, north, and west. New data also reveal an extensive modified landscape of terraformed residential hills, rejolladas, and dense settlement dating from Preclassic through Classic Periods. The LiDAR data also allow for the identification of rooms, benches, and stone property walls and lanes within the city.

  1. Marine Habitat Mapping Incorporating Both Derivatives of LiDAR Data and Hydrodynamic Conditions

    Directory of Open Access Journals (Sweden)

    Grant Smith

    2015-06-01

    Full Text Available Accurate and efficient species-based marine habitat assessment is in great demand for the marine environment. Remote sensing techniques including airborne light detection and ranging (LiDAR derived bathymetry can now be used, in concert with suitable ground truthing, to produce marine habitat maps over wide areas. Hydrodynamic conditions, e.g., current speeds and wave exposure influence habitat types through direct impact on marine organisms, as well as influence on sediment transport and, hence, substrate type. Habitat classification and mapping was carried out using both LiDAR derivatives and hydrodynamic parameters derived from numerical modelling at a location off the coast of Port Hedland in the Pilbara region of Western Australia, 1660 km north of Perth. Habitat classes included seagrass, algae, invertebrates, hard coral, and areas where there is no evident epibenthos. The inclusion of the hydrodynamic parameters significantly increased the accuracy of the classification by 7.7% when compared to using LiDAR derivatives alone.

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

    Science.gov (United States)

    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

  3. Foliar and woody materials discriminated using terrestrial LiDAR in a mixed natural forest

    Science.gov (United States)

    Zhu, Xi; Skidmore, Andrew K.; Darvishzadeh, Roshanak; Niemann, K. Olaf; Liu, Jing; Shi, Yifang; Wang, Tiejun

    2018-02-01

    Separation of foliar and woody materials using remotely sensed data is crucial for the accurate estimation of leaf area index (LAI) and woody biomass across forest stands. In this paper, we present a new method to accurately separate foliar and woody materials using terrestrial LiDAR point clouds obtained from ten test sites in a mixed forest in Bavarian Forest National Park, Germany. Firstly, we applied and compared an adaptive radius near-neighbor search algorithm with a fixed radius near-neighbor search method in order to obtain both radiometric and geometric features derived from terrestrial LiDAR point clouds. Secondly, we used a random forest machine learning algorithm to classify foliar and woody materials and examined the impact of understory and slope on the classification accuracy. An average overall accuracy of 84.4% (Kappa = 0.75) was achieved across all experimental plots. The adaptive radius near-neighbor search method outperformed the fixed radius near-neighbor search method. The classification accuracy was significantly higher when the combination of both radiometric and geometric features was utilized. The analysis showed that increasing slope and understory coverage had a significant negative effect on the overall classification accuracy. Our results suggest that the utilization of the adaptive radius near-neighbor search method coupling both radiometric and geometric features has the potential to accurately discriminate foliar and woody materials from terrestrial LiDAR data in a mixed natural forest.

  4. Algorithm for Extracting Digital Terrain Models under Forest Canopy from Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Almasi S. Maguya

    2014-07-01

    Full Text Available Extracting digital elevationmodels (DTMs from LiDAR data under forest canopy is a challenging task. This is because the forest canopy tends to block a portion of the LiDAR pulses from reaching the ground, hence introducing gaps in the data. This paper presents an algorithm for DTM extraction from LiDAR data under forest canopy. The algorithm copes with the challenge of low data density by generating a series of coarse DTMs by using the few ground points available and using trend surfaces to interpolate missing elevation values in the vicinity of the available points. This process generates a cloud of ground points from which the final DTM is generated. The algorithm has been compared to two other algorithms proposed in the literature in three different test sites with varying degrees of difficulty. Results show that the algorithm presented in this paper is more tolerant to low data density compared to the other two algorithms. The results further show that with decreasing point density, the differences between the three algorithms dramatically increased from about 0.5m to over 10m.

  5. Airborne LiDAR Data Filtering Based on Geodesic Transformations of Mathematical Morphology

    Directory of Open Access Journals (Sweden)

    Yong Li

    2017-10-01

    Full Text Available The capability of acquiring accurate and dense three-dimensional geospatial information that covers large survey areas rapidly enables airborne light detection and ranging (LiDAR has become a powerful technology in numerous fields of geospatial applications and analysis. LiDAR data filtering is the first and essential step for digital elevation model generation, land cover classification, and object reconstruction. The morphological filtering approaches have the advantages of simple concepts and easy implementation, which are able to filter non-ground points effectively. However, the filtering quality of morphological approaches is sensitive to the structuring elements that are the key factors for the filtering success of mathematical operations. Aiming to deal with the dependence on the selection of structuring elements, this paper proposes a novel filter of LiDAR point clouds based on geodesic transformations of mathematical morphology. In comparison to traditional morphological transformations, the geodesic transformations only use the elementary structuring element and converge after a finite number of iterations. Therefore, this algorithm makes it unnecessary to select different window sizes or determine the maximum window size, which can enhance the robustness and automation for unknown environments. Experimental results indicate that the new filtering method has promising and competitive performance for diverse landscapes, which can effectively preserve terrain details and filter non-ground points in various complicated environments.

  6. Drainage Structure Datasets and Effects on LiDAR-Derived Surface Flow Modeling

    Directory of Open Access Journals (Sweden)

    Ruopu Li

    2013-12-01

    Full Text Available With extraordinary resolution and accuracy, Light Detection and Ranging (LiDAR-derived digital elevation models (DEMs have been increasingly used for watershed analyses and modeling by hydrologists, planners and engineers. Such high-accuracy DEMs have demonstrated their effectiveness in delineating watershed and drainage patterns at fine scales in low-relief terrains. However, these high-resolution datasets are usually only available as topographic DEMs rather than hydrologic DEMs, presenting greater land roughness that can affect natural flow accumulation. Specifically, locations of drainage structures such as road culverts and bridges were simulated as barriers to the passage of drainage. This paper proposed a geospatial method for producing LiDAR-derived hydrologic DEMs, which incorporates data collection of drainage structures (i.e., culverts and bridges, data preprocessing and burning of the drainage structures into DEMs. A case study of GIS-based watershed modeling in South Central Nebraska showed improved simulated surface water derivatives after the drainage structures were burned into the LiDAR-derived topographic DEMs. The paper culminates in a proposal and discussion of establishing a national or statewide drainage structure dataset.

  7. Automated method for measuring the extent of selective logging damage with airborne LiDAR data

    Science.gov (United States)

    Melendy, L.; Hagen, S. C.; Sullivan, F. B.; Pearson, T. R. H.; Walker, S. M.; Ellis, P.; Kustiyo; Sambodo, Ari Katmoko; Roswintiarti, O.; Hanson, M. A.; Klassen, A. W.; Palace, M. W.; Braswell, B. H.; Delgado, G. M.

    2018-05-01

    Selective logging has an impact on the global carbon cycle, as well as on the forest micro-climate, and longer-term changes in erosion, soil and nutrient cycling, and fire susceptibility. Our ability to quantify these impacts is dependent on methods and tools that accurately identify the extent and features of logging activity. LiDAR-based measurements of these features offers significant promise. Here, we present a set of algorithms for automated detection and mapping of critical features associated with logging - roads/decks, skid trails, and gaps - using commercial airborne LiDAR data as input. The automated algorithm was applied to commercial LiDAR data collected over two logging concessions in Kalimantan, Indonesia in 2014. The algorithm results were compared to measurements of the logging features collected in the field soon after logging was complete. The automated algorithm-mapped road/deck and skid trail features match closely with features measured in the field, with agreement levels ranging from 69% to 99% when adjusting for GPS location error. The algorithm performed most poorly with gaps, which, by their nature, are variable due to the unpredictable impact of tree fall versus the linear and regular features directly created by mechanical means. Overall, the automated algorithm performs well and offers significant promise as a generalizable tool useful to efficiently and accurately capture the effects of selective logging, including the potential to distinguish reduced impact logging from conventional logging.

  8. Automated object detection and tracking with a flash LiDAR system

    Science.gov (United States)

    Hammer, Marcus; Hebel, Marcus; Arens, Michael

    2016-10-01

    The detection of objects, or persons, is a common task in the fields of environment surveillance, object observation or danger defense. There are several approaches for automated detection with conventional imaging sensors as well as with LiDAR sensors, but for the latter the real-time detection is hampered by the scanning character and therefore by the data distortion of most LiDAR systems. The paper presents a solution for real-time data acquisition of a flash LiDAR sensor with synchronous raw data analysis, point cloud calculation, object detection, calculation of the next best view and steering of the pan-tilt head of the sensor. As a result the attention is always focused on the object, independent of the behavior of the object. Even for highly volatile and rapid changes in the direction of motion the object is kept in the field of view. The experimental setup used in this paper is realized with an elementary person detection algorithm in medium distances (20 m to 60 m) to show the efficiency of the system for objects with a high angular speed. It is easy to replace the detection part by any other object detection algorithm and thus it is easy to track nearly any object, for example a car or a boat or an UAV in various distances.

  9. AN EFFICIENT METHOD FOR AUTOMATIC ROAD EXTRACTION BASED ON MULTIPLE FEATURES FROM LiDAR DATA

    Directory of Open Access Journals (Sweden)

    Y. Li

    2016-06-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  11. Automatic 3d Building Model Generations with Airborne LiDAR Data

    Science.gov (United States)

    Yastikli, N.; Cetin, Z.

    2017-11-01

    LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D

  12. Flood Risk Mapping Using LiDAR for Annapolis Royal, Nova Scotia, Canada

    Directory of Open Access Journals (Sweden)

    Tim L. Webster

    2010-09-01

    Full Text Available A significant portion of the Canadian Maritime coastline has been surveyed with airborne Light Detection and Ranging (LiDAR. The purpose of these surveys has been to map the risk of flooding from storm surges and projected long-term sea‑level rise from climate change and to include projects in all three Maritime Provinces: Prince Edward Island, New Brunswick, and Nova Scotia. LiDAR provides the required details in order to map the flood inundation from 1 to 2 m storm surge events, which cause coastal flooding in many locations in this region when they occur at high tide levels. The community of Annapolis Royal, Nova Scotia, adjacent to the Bay of Fundy, has been surveyed with LiDAR and a 1 m DEM (Digital Elevation Model was constructed for the flood inundation mapping. Validation of the LiDAR using survey grade GPS indicates a vertical accuracy better than 30 cm. A benchmark storm, known as the Groundhog Day storm (February 1–3, 1976, was used to assess the flood maps and to illustrate the effects of different sea-level rise projections based on climate change scenarios if it were to re-occur in 100 years time. Near shore bathymetry has been merged with the LiDAR and local wind observations used to model the impact of significant waves during this benchmark storm. Long-term (ca. greater than 30 years time series of water level observations from across the Bay of Fundy in Saint John, New Brunswick, have been used to estimate return periods of water levels under present and future sea-level rise conditions. Results indicate that under current sea-level rise conditions this storm has a 66 year return period. With a modest relative sea-level (RSL rise of 80 cm/century this decreases to 44 years and, with a possible upper limit rise of 220 cm/century, this decreases further to 22 years. Due to the uncertainty of climate change scenarios and sea-level rise, flood inundation maps have been constructed at 10 cm increments up to the 9 m contour

  13. Decomposition of LiDAR waveforms by B-spline-based modeling

    Science.gov (United States)

    Shen, Xiang; Li, Qing-Quan; Wu, Guofeng; Zhu, Jiasong

    2017-06-01

    Waveform decomposition is a widely used technique for extracting echoes from full-waveform LiDAR data. Most previous studies recommended the Gaussian decomposition approach, which employs the Gaussian function in laser pulse modeling. As the Gaussian-shape assumption is not always satisfied for real LiDAR waveforms, some other probability distributions (e.g., the lognormal distribution, the generalized normal distribution, and the Burr distribution) have also been introduced by researchers to fit sharply-peaked and/or heavy-tailed pulses. However, these models cannot be universally used, because they are only suitable for processing the LiDAR waveforms in particular shapes. In this paper, we present a new waveform decomposition algorithm based on the B-spline modeling technique. LiDAR waveforms are not assumed to have a priori shapes but rather are modeled by B-splines, and the shape of a received waveform is treated as the mixture of finite transmitted pulses after translation and scaling transformation. The performance of the new model was tested using two full-waveform data sets acquired by a Riegl LMS-Q680i laser scanner and an Optech Aquarius laser bathymeter, comparing with three classical waveform decomposition approaches: the Gaussian, generalized normal, and lognormal distribution-based models. The experimental results show that the B-spline model performed the best in terms of waveform fitting accuracy, while the generalized normal model yielded the worst performance in the two test data sets. Riegl waveforms have nearly Gaussian pulse shapes and were well fitted by the Gaussian mixture model, while the B-spline-based modeling algorithm produced a slightly better result by further reducing 6.4% of fitting residuals, largely benefiting from alleviating the adverse impact of the ringing effect. The pulse shapes of Optech waveforms, on the other hand, are noticeably right-skewed. The Gaussian modeling results deviated significantly from original signals, and

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

    Science.gov (United States)

    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

  15. AUTOMATIC 3D BUILDING MODEL GENERATIONS WITH AIRBORNE LiDAR DATA

    Directory of Open Access Journals (Sweden)

    N. Yastikli

    2017-11-01

    Full Text Available LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified

  16. Fusion of Airborne Discrete-Return LiDAR and Hyperspectral Data for Land Cover Classification

    Directory of Open Access Journals (Sweden)

    Shezhou Luo

    2015-12-01

    Full Text Available Accurate land cover classification information is a critical variable for many applications. This study presents a method to classify land cover using the fusion data of airborne discrete return LiDAR (Light Detection and Ranging and CASI (Compact Airborne Spectrographic Imager hyperspectral data. Four LiDAR-derived images (DTM, DSM, nDSM, and intensity and CASI data (48 bands with 1 m spatial resolution were spatially resampled to 2, 4, 8, 10, 20 and 30 m resolutions using the nearest neighbor resampling method. These data were thereafter fused using the layer stacking and principal components analysis (PCA methods. Land cover was classified by commonly used supervised classifications in remote sensing images, i.e., the support vector machine (SVM and maximum likelihood (MLC classifiers. Each classifier was applied to four types of datasets (at seven different spatial resolutions: (1 the layer stacking fusion data; (2 the PCA fusion data; (3 the LiDAR data alone; and (4 the CASI data alone. In this study, the land cover category was classified into seven classes, i.e., buildings, road, water bodies, forests, grassland, cropland and barren land. A total of 56 classification results were produced, and the classification accuracies were assessed and compared. The results show that the classification accuracies produced from two fused datasets were higher than that of the single LiDAR and CASI data at all seven spatial resolutions. Moreover, we find that the layer stacking method produced higher overall classification accuracies than the PCA fusion method using both the SVM and MLC classifiers. The highest classification accuracy obtained (OA = 97.8%, kappa = 0.964 using the SVM classifier on the layer stacking fusion data at 1 m spatial resolution. Compared with the best classification results of the CASI and LiDAR data alone, the overall classification accuracies improved by 9.1% and 19.6%, respectively. Our findings also demonstrated that the

  17. LiDAR Sampling Density for Forest Resource Inventories in Ontario, Canada

    Directory of Open Access Journals (Sweden)

    Dave Etheridge

    2012-03-01

    Full Text Available Over the past two decades there has been an abundance of research demonstrating the utility of airborne light detection and ranging (LiDAR for predicting forest biophysical/inventory variables at the plot and stand levels. However, to date there has been little effort to develop a set of protocols for data acquisition and processing that would move governments or the forest industry towards cost-effective implementation of this technology for strategic and tactical (i.e., operational forest resource inventories. The goal of this paper is to initiate this process by examining the significance of LiDAR data acquisition (i.e., point density for modeling forest inventory variables for the range of species and stand conditions representing much of Ontario, Canada. Field data for approximately 200 plots, sampling a broad range of forest types and conditions across Ontario, were collected for three study sites. Airborne LiDAR data, characterized by a mean density of 3.2 pulses m−2 were systematically decimated to produce additional datasets with densities of approximately 1.6 and 0.5 pulses m−2. Stepwise regression models, incorporating LiDAR height and density metrics, were developed for each of the three LiDAR datasets across a range of forest types to estimate the following forest inventory variables: (1 average height (R2(adj = 0.75–0.95; (2 top height (R2(adj = 0.74–0.98; (3 quadratic mean diameter (R2(adj = 0.55–0.85; (4 basal area (R2(adj = 0.22–0.93; (5 gross total volume (R2(adj = 0.42–0.94; (6 gross merchantable volume (R2(adj = 0.35–0.93; (7 total aboveground biomass (R2(adj = 0.23–0.93; and (8 stem density (R2(adj = 0.17–0.86. Aside from a few cases (i.e., average height and density for some stand types, no decimation effect was observed with respect to the precision of the prediction of the majority of forest variables, which suggests that a mean density of 0.5 pulses m−2 is sufficient for plot and stand level

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

    Science.gov (United States)

    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

  19. A Petrologic and Trace Element Study of Dar al Gani 476 and Dar al Gani 489: Twin Meteorites with Affinities to Basaltic and Lherzolitic Shergottites

    Science.gov (United States)

    Wadhwa, M.; Lentz, R. C. F.; McSween, H. Y.; Crozaz, G., Jr.

    2001-02-01

    We present the results of a combined mineralogic-petrologic and ion microprobe study of two martian meteorites recently recovered in the Lybian Sahara, Dar al Gani 476 (DaG 476) and Dar al Gani 489 (DaG 489). Having resided in a hot desert environment for an extended time, DaG 476 and DaG 489 were subjected to terrestrial weathering that significantly altered their chemical composition. In particular, analyses of some of the silicates show light rare earth element (LREE)-enrichment resulting from terrestrial alteration. In situ measurement of trace element abundances in minerals allows us to identify areas unaffected by this contamination and, thereby, to infer the petrogenesis of these meteorites. No significant compositional differences between DaG 476 and DaG 489 were found, supporting the hypothesis that they belong to the same fall. These meteorites have characteristics in common with both basaltic and lherzolitic shergottites, possibly suggesting spatial and petrogenetic associations of these two types of lithologies on Mars. However, the compositions of Fe-Ti oxides and the size of Eu anomalies in the earliest-formed pyroxenes indicate that the two Saharan meteorites probably experienced more reducing crystallization conditions than other shergottites (with the exception of Queen Alexandra Range (QUE) 94201). As is the case for other shergottites, trace element microdistributions in minerals of the DaG martian meteorites indicate that closed-system crystal fractionation from a LREE-depleted parent magma dominated their crystallization history. Furthermore, rare earth element abundances in the orthopyroxene megacrysts are consistent with their origin as xenocrysts rather than phenocrysts.

  20. Quantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR

    Science.gov (United States)

    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.

  1. The dar genes of Pseudomonas chlororaphis PCL1606 are crucial for biocontrol activity via production of the antifungal compound 2-hexyl, 5-propyl resorcinol.

    Science.gov (United States)

    Calderón, Claudia E; Pérez-García, Alejandro; de Vicente, Antonio; Cazorla, Francisco M

    2013-05-01

    To determine the genetic basis by which 2-hexyl, 5-propyl resorcinol (HPR) is produced by the biocontrol rhizobacterium Pseudomonas chlororaphis (formerly known as P. fluorescens) PCL1606, the presence and role of dar genes were investigated. To accomplish this aim, the pCGNOV-1 plasmid was isolated from a PCL1606 genomic library and was shown to hybridize to various dar probes by Southern blot. An analysis of the pCGNOV-1 genomic DNA revealed the presence of five open reading frames that were homologous to dar genes and had an organization that resembled the arrangement of previously described P. chlororaphis strains. Phylogenetic studies resulted in the clustering of PCL1606 with the P. chlororaphis subgroup, which supported the renaming of this strain from P. fluorescens to P. chlororaphis PCL1606. The construction of insertional mutants for each homologous dar gene in P. chlororaphis PCL1606 along with their corresponding complemented derivative strains restored HPR production and confirmed the key role of the dar A and darB genes in HPR production and in the antagonistic phenotype. Finally, biocontrol assays were performed on avocado-Rosellinia and tomato-Fusarium test systems using the HPR-defective and -complemented derivative strains generated here and demonstrated the crucial role of the biosynthetic dar genes in the biocontrol phenotype of P. chlororaphis PCL1606. This biocontrol phenotype is dependent on the dar genes via their production of the HPR antibiotic. Some of the dar genes not directly involved in the biosynthesis of HPR, such as darS or darR, might contribute to regulatory features of HPR production.

  2. On Feature Extraction from Large Scale Linear LiDAR Data

    Science.gov (United States)

    Acharjee, Partha Pratim

    Airborne light detection and ranging (LiDAR) can generate co-registered elevation and intensity map over large terrain. The co-registered 3D map and intensity information can be used efficiently for different feature extraction application. In this dissertation, we developed two algorithms for feature extraction, and usages of features for practical applications. One of the developed algorithms can map still and flowing waterbody features, and another one can extract building feature and estimate solar potential on rooftops and facades. Remote sensing capabilities, distinguishing characteristics of laser returns from water surface and specific data collection procedures provide LiDAR data an edge in this application domain. Furthermore, water surface mapping solutions must work on extremely large datasets, from a thousand square miles, to hundreds of thousands of square miles. National and state-wide map generation/upgradation and hydro-flattening of LiDAR data for many other applications are two leading needs of water surface mapping. These call for as much automation as possible. Researchers have developed many semi-automated algorithms using multiple semi-automated tools and human interventions. This reported work describes a consolidated algorithm and toolbox developed for large scale, automated water surface mapping. Geometric features such as flatness of water surface, higher elevation change in water-land interface and, optical properties such as dropouts caused by specular reflection, bimodal intensity distributions were some of the linear LiDAR features exploited for water surface mapping. Large-scale data handling capabilities are incorporated by automated and intelligent windowing, by resolving boundary issues and integrating all results to a single output. This whole algorithm is developed as an ArcGIS toolbox using Python libraries. Testing and validation are performed on a large datasets to determine the effectiveness of the toolbox and results are

  3. Scaling wood volume estimates from inventory plots to landscapes with airborne LiDAR in temperate deciduous forest

    Directory of Open Access Journals (Sweden)

    Shaun R. Levick

    2016-05-01

    Full Text Available Abstract Background Monitoring and managing carbon stocks in forested ecosystems requires accurate and repeatable quantification of the spatial distribution of wood volume at landscape to regional scales. Grid-based forest inventory networks have provided valuable records of forest structure and dynamics at individual plot scales, but in isolation they may not represent the carbon dynamics of heterogeneous landscapes encompassing diverse land-management strategies and site conditions. Airborne LiDAR has greatly enhanced forest structural characterisation and, in conjunction with field-based inventories, it provides avenues for monitoring carbon over broader spatial scales. Here we aim to enhance the integration of airborne LiDAR surveying with field-based inventories by exploring the effect of inventory plot size and number on the relationship between field-estimated and LiDAR-predicted wood volume in deciduous broad-leafed forest in central Germany. Results Estimation of wood volume from airborne LiDAR was most robust (R2 = 0.92, RMSE = 50.57 m3 ha−1 ~14.13 Mg C ha−1 when trained and tested with 1 ha experimental plot data (n = 50. Predictions based on a more extensive (n = 1100 plot network with considerably smaller (0.05 ha plots were inferior (R2 = 0.68, RMSE = 101.01 ~28.09 Mg C ha−1. Differences between the 1 and 0.05 ha volume models from LiDAR were negligible however at the scale of individual land-management units. Sample size permutation tests showed that increasing the number of inventory plots above 350 for the 0.05 ha plots returned no improvement in R2 and RMSE variability of the LiDAR-predicted wood volume model. Conclusions Our results from this study confirm the utility of LiDAR for estimating wood volume in deciduous broad-leafed forest, but highlight the challenges associated with field plot size and number in establishing robust relationships between airborne LiDAR and field derived wood volume. We

  4. High Frequency Field Measurements of an Undular Bore Using a 2D LiDAR Scanner

    Directory of Open Access Journals (Sweden)

    Kévin Martins

    2017-05-01

    Full Text Available The secondary wave field associated with undular tidal bores (known as whelps has been barely studied in field conditions: the wave field can be strongly non-hydrostatic, and the turbidity is generally high. In situ measurements based on pressure or acoustic signals can therefore be limited or inadequate. The intermittent nature of this process in the field and the complications encountered in the downscaling to laboratory conditions also render its study difficult. Here, we present a new methodology based on LiDAR technology to provide high spatial and temporal resolution measurements of the free surface of an undular tidal bore. A wave-by-wave analysis is performed on the whelps, and comparisons between LiDAR, acoustic and pressure-derived measurements are used to quantify the non-hydrostatic nature of this phenomenon. A correction based on linear wave theory applied on individual wave properties improves the results from the pressure transducer (Root mean square error, R M S E of 0 . 19 m against 0 . 38 m; however, more robust data is obtained from an upwards-looking acoustic sensor despite high turbidity during the passage of the whelps ( R M S E of 0 . 05 m. Finally, the LiDAR scanner provides the unique possibility to study the wave geometry: the distribution of measured wave height, period, celerity, steepness and wavelength are presented. It is found that the highest wave from the whelps can be steeper than the bore front, explaining why breaking events are sometimes observed in the secondary wave field of undular tidal bores.

  5. A linearly approximated iterative Gaussian decomposition method for waveform LiDAR processing

    Science.gov (United States)

    Mountrakis, Giorgos; Li, Yuguang

    2017-07-01

    Full-waveform LiDAR (FWL) decomposition results often act as the basis for key LiDAR-derived products, for example canopy height, biomass and carbon pool estimation, leaf area index calculation and under canopy detection. To date, the prevailing method for FWL product creation is the Gaussian Decomposition (GD) based on a non-linear Levenberg-Marquardt (LM) optimization for Gaussian node parameter estimation. GD follows a "greedy" approach that may leave weak nodes undetected, merge multiple nodes into one or separate a noisy single node into multiple ones. In this manuscript, we propose an alternative decomposition method called Linearly Approximated Iterative Gaussian Decomposition (LAIGD method). The novelty of the LAIGD method is that it follows a multi-step "slow-and-steady" iterative structure, where new Gaussian nodes are quickly discovered and adjusted using a linear fitting technique before they are forwarded for a non-linear optimization. Two experiments were conducted, one using real full-waveform data from NASA's land, vegetation, and ice sensor (LVIS) and another using synthetic data containing different number of nodes and degrees of overlap to assess performance in variable signal complexity. LVIS data revealed considerable improvements in RMSE (44.8% lower), RSE (56.3% lower) and rRMSE (74.3% lower) values compared to the benchmark GD method. These results were further confirmed with the synthetic data. Furthermore, the proposed multi-step method reduces execution times in half, an important consideration as there are plans for global coverage with the upcoming Global Ecosystem Dynamics Investigation LiDAR sensor on the International Space Station.

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

    Science.gov (United States)

    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.

  7. Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR

    Science.gov (United States)

    Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph

    2018-03-01

    Distinguishing tree species is relevant in many contexts of remote sensing assisted forest inventory. Accurate tree species maps support management and conservation planning, pest and disease control and biomass estimation. This study evaluated the performance of applying ensemble techniques with the goal of automatically distinguishing Pinus sylvestris L. and Pinus uncinata Mill. Ex Mirb within a 1.3 km2 mountainous area in Barcelonnette (France). Three modelling schemes were examined, based on: (1) high-density LiDAR data (160 returns m-2), (2) Worldview-2 multispectral imagery, and (3) Worldview-2 and LiDAR in combination. Variables related to the crown structure and height of individual trees were extracted from the normalized LiDAR point cloud at individual-tree level, after performing individual tree crown (ITC) delineation. Vegetation indices and the Haralick texture indices were derived from Worldview-2 images and served as independent spectral variables. Selection of the best predictor subset was done after a comparison of three variable selection procedures: (1) Random Forests with cross validation (AUCRFcv), (2) Akaike Information Criterion (AIC) and (3) Bayesian Information Criterion (BIC). To classify the species, 9 regression techniques were combined using ensemble models. Predictions were evaluated using cross validation and an independent dataset. Integration of datasets and models improved individual tree species classification (True Skills Statistic, TSS; from 0.67 to 0.81) over individual techniques and maintained strong predictive power (Relative Operating Characteristic, ROC = 0.91). Assemblage of regression models and integration of the datasets provided more reliable species distribution maps and associated tree-scale mapping uncertainties. Our study highlights the potential of model and data assemblage at improving species classifications needed in present-day forest planning and management.

  8. Quantification of glacial and ground surface velocities from repeat terrestrial LiDAR scans

    Science.gov (United States)

    Shahzad, F.; Ehlers, T. A.

    2012-04-01

    Repeat terrestrial LiDAR scans of moving surfaces (e.g. around faults, glaciers, mass movements, etc.) collected at different times offer the opportunity to quantify surface velocities in high resolution. This study presents a new approach for quantifying surface velocities from remote sensing data. Emphasis is placed on the interpretation of terrestrial LiDAR grid point cloud (GPC) data, but the technique presented is also applicable to other (RASTER) remote sensing datasets. The method used consists of investigating two or more temporally variable GPCs referred as a raw and displaced/deformed scans. A user-defined grid is defined on the raw and deformed scans and the center point of each grid is identified. A search window size is determined for comparison between the two scans. Elevations in both scans are then converted to a reference elevation and a normalized cross correlation is applied between the images for pattern recognition. The focal points of the raw image and correlated deformed location are used to prepare an affine transformation for that grid. This procedure is applied on all the grids to prepare the spatial distribution of the affine transformation. Finally, the affine transformation is extended to calculate the horizontal components of surface deformation. These components are used to prepare the spatial distribution of the displacement distance and angle between each grid on each scan. The routine was applied to a series of synthetic (test) datasets and to repeat LiDAR scans (ILRIS-LR) of the Rhone glacier, Switzerland collected in August 2011. Results from the synthetic tests indicate the approach provides a robust reconstruction of spatially non-uniform velocity fields on scans with different surface characteristics. For the Rhone glacier data both temporal and spatial variations in surface velocities were recovered across a large portion of the glacier at centimeter scale. Temporal variations in the glacier surface velocity were resolved

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

    Science.gov (United States)

    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

  10. A high density consensus map of rye (Secale cereale L. based on DArT markers.

    Directory of Open Access Journals (Sweden)

    Paweł Milczarski

    Full Text Available 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.

  11. Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data

    Directory of Open Access Journals (Sweden)

    Zhen Zhen

    2016-04-01

    Full Text Available Automated individual tree crown detection and delineation (ITCD using remotely sensed data plays an increasingly significant role in efficiently, accurately, and completely monitoring forests. This paper reviews trends in ITCD research from 1990–2015 from several perspectives—data/forest type, method applied, accuracy assessment and research objective—with a focus on studies using LiDAR data. This review shows that active sources are becoming more prominent in ITCD studies. Studies using active data—LiDAR in particular—accounted for 80% of the total increase over the entire time period, those using passive data or fusion of passive and active data comprised relatively small proportions of the total increase (8% and 12%, respectively. Additionally, ITCD research has moved from incremental adaptations of algorithms developed for passive data sources to innovative approaches that take advantage of the novel characteristics of active datasets like LiDAR. These improvements make it possible to explore more complex forest conditions (e.g., closed hardwood forests, suburban/urban forests rather than a single forest type although most published ITCD studies still focused on closed softwood (41% or mixed forest (22%. Approximately one-third of studies applied individual tree level (30% assessment, with only a quarter reporting more comprehensive multi-level assessment (23%. Almost one-third of studies (32% that concentrated on forest parameter estimation based on ITCD results had no ITCD-specific evaluation. Comparison of methods continues to be complicated by both choice of reference data and assessment metric; it is imperative to establish a standardized two-level assessment framework to evaluate and compare ITCD algorithms in order to provide specific recommendations about suitable applications of particular algorithms. However, the evolution of active remotely sensed data and novel platforms implies that automated ITCD will continue to be a

  12. Development of a UAV-LiDAR System with Application to Forest Inventory

    Directory of Open Access Journals (Sweden)

    Darren Turner

    2012-05-01

    Full Text Available We present the development of a low-cost Unmanned Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR system and an accompanying workflow to produce 3D point clouds. UAV systems provide an unrivalled combination of high temporal and spatial resolution datasets. The TerraLuma UAV-LiDAR system has been developed to take advantage of these properties and in doing so overcome some of the current limitations of the use of this technology within the forestry industry. A modified processing workflow including a novel trajectory determination algorithm fusing observations from a GPS receiver, an Inertial Measurement Unit (IMU and a High Definition (HD video camera is presented. The advantages of this workflow are demonstrated using a rigorous assessment of the spatial accuracy of the final point clouds. It is shown that due to the inclusion of video the horizontal accuracy of the final point cloud improves from 0.61 m to 0.34 m (RMS error assessed against ground control. The effect of the very high density point clouds (up to 62 points per m2 produced by the UAV-LiDAR system on the measurement of tree location, height and crown width are also assessed by performing repeat surveys over individual isolated trees. The standard deviation of tree height is shown to reduce from 0.26 m, when using data with a density of 8 points perm2, to 0.15mwhen the higher density data was used. Improvements in the uncertainty of the measurement of tree location, 0.80 m to 0.53 m, and crown width, 0.69 m to 0.61 m are also shown.

  13. 3D Scene Reconstruction Using Omnidirectional Vision and LiDAR: A Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Michiel Vlaminck

    2016-11-01

    Full Text Available In this paper, we propose a novel approach to obtain accurate 3D reconstructions of large-scale environments by means of a mobile acquisition platform. The system incorporates a Velodyne LiDAR scanner, as well as a Point Grey Ladybug panoramic camera system. It was designed with genericity in mind, and hence, it does not make any assumption about the scene or about the sensor set-up. The main novelty of this work is that the proposed LiDAR mapping approach deals explicitly with the inhomogeneous density of point clouds produced by LiDAR scanners. To this end, we keep track of a global 3D map of the environment, which is continuously improved and refined by means of a surface reconstruction technique. Moreover, we perform surface analysis on consecutive generated point clouds in order to assure a perfect alignment with the global 3D map. In order to cope with drift, the system incorporates loop closure by determining the pose error and propagating it back in the pose graph. Our algorithm was exhaustively tested on data captured at a conference building, a university campus and an industrial site of a chemical company. Experiments demonstrate that it is capable of generating highly accurate 3D maps in very challenging environments. We can state that the average distance of corresponding point pairs between the ground truth and estimated point cloud approximates one centimeter for an area covering approximately 4000 m 2 . To prove the genericity of the system, it was tested on the well-known Kitti vision benchmark. The results show that our approach competes with state of the art methods without making any additional assumptions.

  14. Canopy Height Estimation by Characterizing Waveform LiDAR Geometry Based on Shape-Distance Metric

    Directory of Open Access Journals (Sweden)

    Eric Ariel L. Salas

    2016-11-01

    Full Text Available There have been few approaches developed for the estimation of height using waveform LiDAR data. Unlike any existing methods, we illustrate how the new Moment Distance (MD framework can characterize the canopy height based on the geometry and return power of the LiDAR waveform without having to go through curve modeling processes. Our approach offers the possibilities of using the raw waveform data to capture vital information from the variety of complex waveform shapes in LiDAR. We assess the relationship of the MD metrics to the key waveform landmarks—such as locations of peaks, power of returns, canopy heights, and height metrics—using synthetic data and real Laser Vegetation Imaging Sensor (LVIS data. In order to verify the utility of the new approach, we use field measurements obtained through the DESDynI (Deformation, Ecosystem Structure and Dynamics of Ice campaign. Our results reveal that the MDI can capture temporal dynamics of canopy and segregate generations of stands based on curve shapes. The method satisfactorily estimates the canopy height using the synthetic (r2 = 0.40 and the LVIS dataset (r2 = 0.74. The MDI is also comparable with existing RH75 (relative height at 75% and RH50 (relative height at 50% height metrics. Furthermore, the MDI shows better correlations with ground-based measurements than relative height metrics. The MDI performs well at any type of waveform shape. This opens the possibility of looking more closely at single-peaked waveforms that usually carries complex extremes.

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

    Science.gov (United States)

    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.

  16. Derivation of Strike and Dip in Sedimentary Terrain Using 3D Image Interpretation Based on Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Chih-Hsiang Yeh

    2014-01-01

    Full Text Available Traditional geological mapping may be hindered by rough terrain and dense vegetation resulting in obscured geological details. The advent of airborne Light Detection and Ranging (LiDAR provides a very precise three-dimensional (3D digital terrain model (DTM. However, its full potential in complementing traditional geological mapping remains to be explored using 3D rendering techniques. This study uses two types of 3D images which differ in imaging principles to further explore the finer details of sedimentary terrain. Our purposes are to demonstrate detailed geological mapping with 3D rendering techniques, to generate LiDAR-derived 3D strata boundaries that are advantageous in generating 2D geological maps and cross sections, and to develop a new practice in deriving the strike and dip of bedding with LiDAR data using an example from the north bank of the Keelung River in northern Taiwan. We propose a geological mapping practice that improves efficiency and meets a high-precision mapping standard with up to 2 m resolution using airborne LiDAR data. Through field verification and assessment, LiDAR data manipulation with relevant 3D visualization is shown to be an effective approach in improving the details of existing geological maps, specifically in sedimentary terrain.

  17. INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm.

    Science.gov (United States)

    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.

  18. LiDAR and Orthophoto Synergy to optimize Object-Based Landscape Change: Analysis of an Active Landslide

    Directory of Open Access Journals (Sweden)

    Martijn Kamps

    2017-08-01

    Full Text Available Active landslides have three major effects on landscapes: (1 land cover change, (2 topographical change, and (3 above ground biomass change. Data derived from multi-temporal Light Detection and Ranging technology (LiDAR are used in combination with multi-temporal orthophotos to quantify these changes between 2006 and 2012, caused by an active deep-seated landslide near the village of Doren in Austria. Land-cover is classified by applying membership-based classification and contextual improvements based on the synergy of orthophotos and LiDAR-based elevation data. Topographical change is calculated by differencing of LiDAR derived digital terrain models. The above ground biomass is quantified by applying a local-maximum algorithm for tree top detection, in combination with allometric equations. The land cover classification accuracies were improved from 65% (using only LiDAR and 76% (using only orthophotos to 90% (using data synergy for 2006. A similar increase from respectively 64% and 75% to 91% was established for 2012. The increased accuracies demonstrate the effectiveness of using data synergy of LiDAR and orthophotos using object-based image analysis to quantify landscape changes, caused by an active landslide. The method has great potential to be transferred to larger areas for use in landscape change analyses.

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

    Science.gov (United States)

    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

  20. Quantification of tidal inlet morphodynamics using high-resolution MBES and LiDAR

    DEFF Research Database (Denmark)

    Ernstsen, Verner Brandbyge; Lefebvre, Alice; Fraccascia, Serena

    the system is needed to assess the impact of potentially changing environmental conditions, such as accelerating sea level rise, increasing storm intensities and frequencies, or shifting wind directions. The aim of this study is to investigate the morphodynamics in a natural tidal inlet system, the Knudedyb......-bathymetric surveys using high-resolution red and green Light Detection And Ranging (LiDAR). Detailed digital elevation models with a grid cell size of 1 m x 1 m were generated and analysed geomorphometrically. The analyses reveal a main ebb-directed net sand transport in the main channel; however, due...

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

    Science.gov (United States)

    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

  2. Acceptance of contraceptives among women who had an unsafe abortion in Dar es Salaam

    DEFF Research Database (Denmark)

    Rasch, Vibeke; Massawe, Siriel; Yambesi, Fortunata

    2004-01-01

    OBJECTIVE: To assess the need for post-abortion contraception and to determine if women who had an unsafe abortion will use a contraceptive method to avoid repeated unwanted pregnancies and STDs/HIV. METHOD: Women attending Temeke Municipal Hospital, Dar es Salaam, after an unsafe abortion...... or an induced abortion performed at the hospital (n=788) were counselled about contraception and the risk of contracting STDs/HIV. A free ward-based contraceptive service was offered and the women were asked to return for follow-up. RESULTS: Participants (90%) accepted the post-abortion contraceptive service...

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

    Science.gov (United States)

    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

  4. Use of LiDAR to Assist in Delineating Waters of the United States, Including Wetlands

    Science.gov (United States)

    2014-03-01

    derived products, and secondary products may be useful to regulators. Point clouds and DTMs can be used to identify topographic lows in a land - scape , to...position in the land - scape . Wetness indices are often calculated using the general formula WI = ln(A/tanβ) where A is the catchment area (m2/m...products should be verified in the field. During the preliminary, data-gathering stage of wet- land delineations, LiDAR data and products may be used to

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  7. Mineralogy and Chemistry of Desert Roses, Ayn Dar Area, Abqaiq, Eastern Province, Saudi Arabia

    OpenAIRE

    Al Mohandis, Ahmed A. [احمد عبد القادر المهندس

    2002-01-01

    Desert roses are crystals which usually take the form of rose petal. They have definite crystal shapes, and enclose sand grains. The desert roses were scattered along an area of about 500m2 in the Ayn Dar area, near Abqaiq, about 80km southwest of Ad Dammam, Eastern Province, Saudi Arabia. They are made up of gypsum crystals included sand grains in the from of rosettes, with distinctive petal morphology. Most quartz grains are cemented by gypsum crystals which show a fibrous structure. ...

  8. a Darío Bentancurt, el de la novísima historia

    Directory of Open Access Journals (Sweden)

    Javier Guerreo Barrón

    1999-01-01

    Full Text Available Ha perdido Colombia, y de que forma, a muchos de sus mejores hombres y mujeres y recientemente, el turno macabro le tocó a la inteligencia. Darío Betancourt Echeverry, nació en Restrepo, Valle, el 10 de diciembre de 1952. Estudió Ciencias Sociales en la Universidad Nacional y en la Universidad Libre. Su primera etapa profesional trasegó sobre la historia colonial y el movimiento Comunero, de la cual quedan dos obras: "Historia de Colombia" Colonial,(Bogotá, Universidad Santo Tomás, 1985 e "Historia de la Edad Media", (Bogotá, Universidad Santo Tomás, 1986.

  9. In-field High Throughput Phenotyping and Cotton Plant Growth Analysis Using LiDAR.

    Science.gov (United States)

    Sun, Shangpeng; Li, Changying; Paterson, Andrew H; Jiang, Yu; Xu, Rui; Robertson, Jon S; Snider, John L; Chee, Peng W

    2018-01-01

    Plant breeding programs and a wide range of plant science applications would greatly benefit from the development of in-field high throughput phenotyping technologies. In this study, a terrestrial LiDAR-based high throughput phenotyping system was developed. A 2D LiDAR was applied to scan plants from overhead in the field, and an RTK-GPS was used to provide spatial coordinates. Precise 3D models of scanned plants were reconstructed based on the LiDAR and RTK-GPS data. The ground plane of the 3D model was separated by RANSAC algorithm and a Euclidean clustering algorithm was applied to remove noise generated by weeds. After that, clean 3D surface models of cotton plants were obtained, from which three plot-level morphologic traits including canopy height, projected canopy area, and plant volume were derived. Canopy height ranging from 85th percentile to the maximum height were computed based on the histogram of the z coordinate for all measured points; projected canopy area was derived by projecting all points on a ground plane; and a Trapezoidal rule based algorithm was proposed to estimate plant volume. Results of validation experiments showed good agreement between LiDAR measurements and manual measurements for maximum canopy height, projected canopy area, and plant volume, with R 2 -values of 0.97, 0.97, and 0.98, respectively. The developed system was used to scan the whole field repeatedly over the period from 43 to 109 days after planting. Growth trends and growth rate curves for all three derived morphologic traits were established over the monitoring period for each cultivar. Overall, four different cultivars showed similar growth trends and growth rate patterns. Each cultivar continued to grow until ~88 days after planting, and from then on varied little. However, the actual values were cultivar specific. Correlation analysis between morphologic traits and final yield was conducted over the monitoring period. When considering each cultivar individually

  10. Storage, Collection and Disposal of Kariakoo Market Wastes in Dar Es Salaam, Tanzania

    DEFF Research Database (Denmark)

    Yhdego, Michael

    1992-01-01

    waste management in Kariakoo market, Dar es Salaam. The main problems identified were poor market design and lack of a well organized waste storage, collection and disposal systems. Two-thirds of the waste consists of vegetable matter. Proposals for improved design of storage and collection facilities...... are described. Experiments revealed wastes from the market are readily decomposable by composting. A change in the design of covered markets and improvements in waste handling are essential to reduce the potential health hazards in developing countries....

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

    Science.gov (United States)

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

    2017-12-01

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

  12. Rubén Darío y la pintura Principio ekfrástico y sinestesia // Rubén Darío and painting: Ekphrastic principle and synesthesia

    Directory of Open Access Journals (Sweden)

    Alvaro Salvador

    2016-12-01

    Full Text Available The article examines the relationships between literature and painting in the works of Rubén Darío. The issue is seen in the context of modernis synesthesia, which was strongly present in the literary ideology of the modernist discourse, and it is analyzed with the help of the theories of ekphrasis of Murray Krieger. In Darío’s canonical works painting plays an important role, both in the form of literary references, and the so called “transpositions of art”, in its intent to create a total art.

  13. A Concealed Car Extraction Method Based on Full-Waveform LiDAR Data

    Directory of Open Access Journals (Sweden)

    Chuanrong Li

    2016-01-01

    Full Text Available Concealed cars extraction from point clouds data acquired by airborne laser scanning has gained its popularity in recent years. However, due to the occlusion effect, the number of laser points for concealed cars under trees is not enough. Thus, the concealed cars extraction is difficult and unreliable. In this paper, 3D point cloud segmentation and classification approach based on full-waveform LiDAR was presented. This approach first employed the autocorrelation G coefficient and the echo ratio to determine concealed cars areas. Then the points in the concealed cars areas were segmented with regard to elevation distribution of concealed cars. Based on the previous steps, a strategy integrating backscattered waveform features and the view histogram descriptor was developed to train sample data of concealed cars and generate the feature pattern. Finally concealed cars were classified by pattern matching. The approach was validated by full-waveform LiDAR data and experimental results demonstrated that the presented approach can extract concealed cars with accuracy more than 78.6% in the experiment areas.

  14. Airborne LiDAR for the Detection of Archaeological Vegetation Marks Using Biomass as a Proxy

    Directory of Open Access Journals (Sweden)

    David Stott

    2015-02-01

    Full Text Available In arable landscapes, the airborne detection of archaeological features is often reliant on using the properties of the vegetation cover as a proxy for sub-surface features in the soil. Under the right conditions, the formation of vegetation marks allows archaeologists to identify and interpret archaeological features. Using airborne Laser Scanning, based on the principles of Light Detection and Ranging (LiDAR to detect these marks is challenging, particularly given the difficulties of resolving subtle changes in a low and homogeneous crop with these sensors. In this paper, an experimental approach is adopted to explore how these marks could be detected as variations in canopy biomass using both range and full waveform LiDAR data. Although some detection was achieved using metrics of the full waveform data, it is the novel multi-temporal method of using discrete return data to detect and characterise archaeological vegetation marks that is offered for further consideration. This method was demonstrated to be applicable over a range of capture conditions, including soils deemed as difficult (i.e., clays and other heavy soils, and should increase the certainty of detection when employed in the increasingly multi-sensor approaches to heritage prospection and management.

  15. Body-art practices among undergraduate medical university students in dar es salaam, Tanzania, 2014.

    Science.gov (United States)

    Chacha, Chacha Emmanuel; Kazaura, Method R

    2015-01-01

    Body-art practices are increasing among adolescents and young adults. Although substantial data are available in developed countries, little has been documented about body-art practices in developing countries. To determine the magnitude, types and reasons for practicing body-art practices among undergraduate medical University students in Dar es Salaam, Tanzania. A cross-sectional descriptive study was conducteed among undergraduate University students in Dar es Salaam involving 536 respondents from two Universities. We used a self-administered questionnaire to collect data. Analyses were based on summary measures and bivariate analyses. While 7.5% of undergraduate students reported having tattoos, 20% reported having body puncturing or piercing. Body piercing is reported more among female university undergraduate students than their male counterparts. Reported main reasons for undergoing body-art include "a mark of beauty," 24%, "just wanted one," 18% and "a mark of femininity or masculinity," 17%. The majority (98%) of students were aware that unsafe body-art practices may lead to contracting HIV and more than half (52%) reported awareness of the risk of Hepatitis B infection. Despite high awareness of the potential risks involved in unsafe body arts that include tattoo and piercing, these practices are increasing among adolescents and young adults. There is need to have educational and counseling efforts so as to minimize associated health risks.

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

    Science.gov (United States)

    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. PMID:27818664

  17. A new method for building roof segmentation from airborne LiDAR point cloud data

    International Nuclear Information System (INIS)

    Kong, Deming; Li, Xiaolu; Xu, Lijun

    2013-01-01

    A new method based on the combination of two kinds of clustering algorithms for building roof segmentation from airborne LiDAR (light detection and ranging) point cloud data is proposed. The K-plane algorithm is introduced to classify the laser footprints that cannot be correctly classified by the traditional K-means algorithm. High-precision classification can be obtained by combining the two aforementioned clustering algorithms. Furthermore, to improve the performance of the new segmentation method, a new initialization method is proposed to acquire the number and coordinates of the initial cluster centers for the K-means algorithm. In the proposed initialization method, the geometrical planes of a building roof are estimated from the elevation image of the building roof by using the mathematical morphology and Hough transform techniques. By calculating the number and normal vectors of the estimated geometrical planes, the number and coordinates of the initial cluster centers for the K-means algorithm are obtained. With the aid of the proposed initialization and segmentation methods, the point cloud of the building roof can be rapidly and appropriately classified. The proposed methods are validated by using both simulated and real LiDAR data. (paper)

  18. Automatic building extraction from LiDAR data fusion of point and grid-based features

    Science.gov (United States)

    Du, Shouji; Zhang, Yunsheng; Zou, Zhengrong; Xu, Shenghua; He, Xue; Chen, Siyang

    2017-08-01

    This paper proposes a method for extracting buildings from LiDAR point cloud data by combining point-based and grid-based features. To accurately discriminate buildings from vegetation, a point feature based on the variance of normal vectors is proposed. For a robust building extraction, a graph cuts algorithm is employed to combine the used features and consider the neighbor contexture information. As grid feature computing and a graph cuts algorithm are performed on a grid structure, a feature-retained DSM interpolation method is proposed in this paper. The proposed method is validated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction and compared to the state-art-of-the methods. The evaluation shows that the proposed method can obtain a promising result both at area-level and at object-level. The method is further applied to the entire ISPRS dataset and to a real dataset of the Wuhan City. The results show a completeness of 94.9% and a correctness of 92.2% at the per-area level for the former dataset and a completeness of 94.4% and a correctness of 95.8% for the latter one. The proposed method has a good potential for large-size LiDAR data.

  19. A Least Squares Collocation Method for Accuracy Improvement of Mobile LiDAR Systems

    Directory of Open Access Journals (Sweden)

    Qingzhou Mao

    2015-06-01

    Full Text Available In environments that are hostile to Global Navigation Satellites Systems (GNSS, the precision achieved by a mobile light detection and ranging (LiDAR system (MLS can deteriorate into the sub-meter or even the meter range due to errors in the positioning and orientation system (POS. This paper proposes a novel least squares collocation (LSC-based method to improve the accuracy of the MLS in these hostile environments. Through a thorough consideration of the characteristics of POS errors, the proposed LSC-based method effectively corrects these errors using LiDAR control points, thereby improving the accuracy of the MLS. This method is also applied to the calibration of misalignment between the laser scanner and the POS. Several datasets from different scenarios have been adopted in order to evaluate the effectiveness of the proposed method. The results from experiments indicate that this method would represent a significant improvement in terms of the accuracy of the MLS in environments that are essentially hostile to GNSS and is also effective regarding the calibration of misalignment.

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

    Science.gov (United States)

    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 (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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Edson P. Amorim

    2009-01-01

    Full Text Available 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.

  3. Evaluation of Tectonic Activities Using LiDAR Topographic Data: The Nankan Lineament in Northern Taiwan

    Directory of Open Access Journals (Sweden)

    Kuo-Jen Chang

    2010-01-01

    Full Text Available The Nankan lineament and the Shanchiao normal fault are two major tructures at the western and eastern boundaries of the Linkou Tableland. In contrast to the Shanchiao fault, the tectonic causes of the Nankan lineament have been studied and yet the results are rather inconsistent and controversial. The morphologic evolution is often the result of tectonic processes which can be regarded as the key information for revealing tectonic activity. This study takes advantage of high-resolution LiDAR images to re-examine the causes and tectonic activities of the Nankan lineament based on its morphological features. High-resolution morphological images enable detailed analyses of the major morphologic features of Nankan lineament and adjacent areas. The studied morphological features were analyzed based with several morphotectonic methodologies, including the curve fitting of river profiles, topographic anomaly analysis and a variation of contour density. The results reveal that Nankan lineament does not possess significant geomorphologic signs of recent tectonic activities. Thus, with the new morphological information based on LiDAR images, it seems reasonable to assert that the Nankan lineament has not been tectonically active recently or if so the lineament has healed and is now concealed by the subsequent surface processes.

  4. Point Spread Function (PSF) noise filter strategy for geiger mode LiDAR

    Science.gov (United States)

    Smith, O'Neil; Stark, Robert; Smith, Philip; St. Romain, Randall; Blask, Steven

    2013-05-01

    LiDAR is an efficient optical remote sensing technology that has application in geography, forestry, and defense. The effectiveness is often limited by signal-to-noise ratio (SNR). Geiger mode avalanche photodiode (APD) detectors are able to operate above critical voltage, and a single photoelectron can initiate the current surge, making the device very sensitive. These advantages come at the expense of requiring computationally intensive noise filtering techniques. Noise is a problem which affects the imaging system and reduces the capability. Common noise-reduction algorithms have drawbacks such as over aggressive filtering, or decimating in order to improve quality and performance. In recent years, there has been growing interest on GPUs (Graphics Processing Units) for their ability to perform powerful massive parallel processing. In this paper, we leverage this capability to reduce the processing latency. The Point Spread Function (PSF) filter algorithm is a local spatial measure that has been GPGPU accelerated. The idea is to use a kernel density estimation technique for point clustering. We associate a local likelihood measure with every point of the input data capturing the probability that a 3D point is true target-return photons or noise (background photons, dark-current). This process suppresses noise and allows for detection of outliers. We apply this approach to the LiDAR noise filtering problem for which we have recognized a speed-up factor of 30-50 times compared to traditional sequential CPU implementation.

  5. Invasive shrub mapping in an urban environment from hyperspectral and LiDAR-derived attributes

    Directory of Open Access Journals (Sweden)

    Curtis Matthew Chance

    2016-10-01

    Full Text Available 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, British Columbia, 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.

  6. Body-art practices among undergraduate medical university students in Dar Es Salaam, Tanzania, 2014

    Directory of Open Access Journals (Sweden)

    Chacha Emmanuel Chacha

    2015-01-01

    Full Text Available Background: Body-art practices are increasing among adolescents and young adults. Although substantial data are available in developed countries, little has been documented about body-art practices in developing countries. Objective: To determine the magnitude, types and reasons for practicing body-art practices among undergraduate medical University students in Dar es Salaam, Tanzania. Materials and Methods: A cross-sectional descriptive study was conducteed among undergraduate University students in Dar es Salaam involving 536 respondents from two Universities. We used a self-administered questionnaire to collect data. Analyses were based on summary measures and bivariate analyses. Results: While 7.5% of undergraduate students reported having tattoos, 20% reported having body puncturing or piercing. Body piercing is reported more among female university undergraduate students than their male counterparts. Reported main reasons for undergoing body-art include "a mark of beauty," 24%, "just wanted one," 18% and "a mark of femininity or masculinity," 17%. The majority (98% of students were aware that unsafe body-art practices may lead to contracting HIV and more than half (52% reported awareness of the risk of Hepatitis B infection. Conclusions: Despite high awareness of the potential risks involved in unsafe body arts that include tattoo and piercing, these practices are increasing among adolescents and young adults. There is need to have educational and counseling efforts so as to minimize associated health risks.

  7. Family perceptions of intellectual disability: Understanding and support in Dar es Salaam

    Science.gov (United States)

    2012-01-01

    When attempting to understand the construct of intellectual disability in different contexts, speaking to family members in addition to the individual with the disability may provide new insight about understandings of and responses to intellectual disability in society and may help to identify the forms of support that are available or needed to ensure the quality of life of people with disabilities. This article outlines and discusses interviews that were conducted in Dar es Salaam, Tanzania, with family members of children and adults with intellectual disabilities. These interviews explore how families came to understand that their child had an intellectual disability; the availability of family support; and family hopes and dreams for the future, and were a part of a wider exploratory study that gathered insight from individuals with disabilities, families, and other providers of support to explore understandings and perceptions of disability in Dar es Salaam. Understanding family experiences will help researchers, policy makers, non-governmental organisations, and others to identify family strengths and family support needs which can ultimately improve family quality of life and the quality of life of the member with a disability. PMID:28729979

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

    Science.gov (United States)

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

    Science.gov (United States)

    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. Copyright © 2014 Reproductive Health Matters. Published by Elsevier Ltd. All rights reserved.

  10. Use of Airborne LiDAR To Estimate Forest Stand Characteristics

    International Nuclear Information System (INIS)

    Li, Qi; Zhou, Wei; Li, Chang

    2014-01-01

    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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2017-04-01

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

  13. Hydrogeology and water chemistry of Infranz catchment springs, Bahir Dar Area, Lake Tana Basin, Ethiopia

    Science.gov (United States)

    Abera, F. N.

    2017-12-01

    The major springs in the Infranz catchment are a significant source of water for Bahir city and nearby villages, while they help to sustain Infranz River and the downstream wetlands. The aim of the research was to understand the hydrogeological conditions of these high-discharge springs, and to explain the hydrochemical composition of spring waters. Water samples from rainwater and springs were collected and analyzed and compared for major cations and anions. The hydrochemical data analysis showed that all water samples of the springs have freshwater chemistry, Ca-HCO3 type, while deep groundwater shows more evolved types. This indicates limited water-rock interaction and short residence time for the spring waters. The rise of NO3- and PO43- may indicate future water quality degradation unless the anthropogenic activities upgradient and nearby are restricted. The uptake of 75% of spring water for water supply of Bahir Dar results in wetland degradation. Key words: Spring water, Infranz River, Bahir Dar, Ethiopia, hydrochemistry

  14. A DATA DRIVEN METHOD FOR FLAT ROOF BUILDING RECONSTRUCTION FROM LiDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    A. Mahphood

    2017-09-01

    Full Text Available 3D building modeling is one of the most important applications in photogrammetry and remote sensing. Airborne LiDAR (Light Detection And Ranging is one of the primary information sources for building modeling. In this paper, a new data-driven method is proposed for 3D building modeling of flat roofs. First, roof segmentation is implemented using region growing method. The distance between roof points and the height difference of the points are utilized in this step. Next, the building edge points are detected using a new method that employs grid data, and then roof lines are regularized using the straight line approximation. The centroid point and direction for each line are estimated in this step. Finally, 3D model is reconstructed by integrating the roof and wall models. In the end, a qualitative and quantitative assessment of the proposed method is implemented. The results show that the proposed method could successfully model the flat roof buildings using LiDAR point cloud automatically.

  15. BUILDING CHANGE DETECTION BY COMBINING LiDAR DATA AND ORTHO IMAGE

    Directory of Open Access Journals (Sweden)

    D. Peng

    2016-06-01

    Full Text Available 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.

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

    Directory of Open Access Journals (Sweden)

    Sungdae Sim

    2016-06-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Christopher T Fisher

    Full Text Available 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Kriegel, Martin; Jakowski, Norbert; Berdermann, Jens; Sato, Hiroatsu [German Aerospace Center (DLR), Neustrelitz (Germany). Inst. of Communications and Navigation; Mersha, Mogese Wassaie [Bahir Dar Univ. (Ethiopia). Washera Geospace and Radar Science Lab.

    2017-04-01

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

  20. 3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds

    Directory of Open Access Journals (Sweden)

    Miguel Garrido

    2015-12-01

    Full Text Available 3D crop reconstruction with a high temporal resolution and by the use of non-destructive measuring technologies can support the automation of plant phenotyping processes. Thereby, the availability of such 3D data can give valuable information about the plant development and the interaction of the plant genotype with the environment. This article presents a new methodology for georeferenced 3D reconstruction of maize plant structure. For this purpose a total station, an IMU, and several 2D LiDARs with different orientations were mounted on an autonomous vehicle. By the multistep methodology presented, based on the application of the ICP algorithm for point cloud fusion, it was possible to perform the georeferenced point clouds overlapping. The overlapping point cloud algorithm showed that the aerial points (corresponding mainly to plant parts were reduced to 1.5%–9% of the total registered data. The remaining were redundant or ground points. Through the inclusion of different LiDAR point of views of the scene, a more realistic representation of the surrounding is obtained by the incorporation of new useful information but also of noise. The use of georeferenced 3D maize plant reconstruction at different growth stages, combined with the total station accuracy could be highly useful when performing precision agriculture at the crop plant level.

  1. Selection of LiDAR geometric features with adaptive neighborhood size for urban land cover classification

    Science.gov (United States)

    Dong, Weihua; Lan, Jianhang; Liang, Shunlin; Yao, Wei; Zhan, Zhicheng

    2017-08-01

    LiDAR has been an effective technology for acquiring urban land cover data in recent decades. Previous studies indicate that geometric features have a strong impact on land cover classification. Here, we analyzed an urban LiDAR dataset to explore the optimal feature subset from 25 geometric features incorporating 25 scales under 6 definitions for urban land cover classification. We performed a feature selection strategy to remove irrelevant or redundant features based on the correlation coefficient between features and classification accuracy of each features. The neighborhood scales were divided into small (0.5-1.5 m), medium (1.5-6 m) and large (>6 m) scale. Combining features with lower correlation coefficient and better classification performance would improve classification accuracy. The feature depicting homogeneity or heterogeneity of points would be calculated at a small scale, and the features to smooth points at a medium scale and the features of height different at large scale. As to the neighborhood definition, cuboid and cylinder were recommended. This study can guide the selection of optimal geometric features with adaptive neighborhood scale for urban land cover classification.

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

    Science.gov (United States)

    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.

  3. Modelling stand biomass fractions in Galician Eucalyptus globulus plantations by use of different LiDAR pulse densities

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez-Ferreiro, E.; Miranda, D.; Barreiro-Fernandez, L.; Bujan, S.; Garcia-Gutierrez, J.; Dieguez-Aranda, U.

    2013-07-01

    Aims of study: To evaluate the potential use of canopy height and intensity distributions, determined by airborne LiDAR, for the estimation of crown, stem and aboveground biomass fractions. To assess the effects of a reduction in LiDAR pulse densities on model precision. Area of study: The study area is located in Galicia, NW Spain. The forests are representative of Eucalyptus globulus stands in NW Spain, characterized by low-intensity silvicultural treatments and by the presence of tall shrub. Material and methods: Linear, multiplicative power and exponential models were used to establish empirical relationships between field measurements and LiDAR metrics. A random selection of LiDAR returns and a comparison of the prediction errors by LiDAR pulse density factor were performed to study a possible loss of fit in these models. Main results: Models showed similar goodness-of-fit statistics to those reported in the international literature. R2 ranged from 0.52 to 0.75 for stand crown biomass, from 0.64 to 0.87 for stand stem biomass, and from 0.63 to 0.86 for stand aboveground biomass. The RMSE/MEAN 100 of the set of fitted models ranged from 17.4% to 28.4%. Models precision was essentially maintained when 87.5% of the original point cloud was reduced, i.e. a reduction from 4 pulses m{sup 2} to 0.5 pulses m{sup 2}. Research highlights: Considering the results of this study, the low-density LiDAR data that are released by the Spanish National Geographic Institute will be an excellent source of information for reducing the cost of forest inventories. (Author)

  4. Modelling stand biomass fractions in Galician Eucalyptus globulus plantations by use of different LiDAR pulse densities

    Directory of Open Access Journals (Sweden)

    E.M. González-Ferreiro

    2013-11-01

    Full Text Available Aims of study: To evaluate the potential use of canopy height and intensity distributions, determined by airborne LiDAR, for the estimation of crown, stem and aboveground biomass fractions.To assess the effects of a reduction in LiDAR pulse densities on model precision.Area of study: The study area is located in Galicia, NW Spain. The forests are representative of Eucalyptus globules stands in NW Spain, characterized by low-intensity silvicultural treatments and by the presence of tall shrub.Material and methods: Linear, multiplicative power and exponential models were used to establish empirical relationships between field measurements and LiDAR metrics.A random selection of LiDAR returns and a comparison of the prediction errors by LiDAR pulse density factor were performed to study a possible loss of fit in these models.Main results: Models showed similar goodness-of-fit statistics to those reported in the international literature. R2 ranged from 0.52 to 0.75 for stand crown biomass, from 0.64 to 0.87 for stand stem biomass, and from 0.63 to 0.86 for stand aboveground biomass. The RMSE/MEAN · 100 of the set of fitted models ranged from 17.4% to 28.4%.Models precision was essentially maintained when 87.5% of the original point cloud was reduced, i.e. a reduction from 4 pulses m–2 to 0.5 pulses m–2.Research highlights: Considering the results of this study, the low-density LiDAR data that are released by the Spanish National Geographic Institute will be an excellent source of information for reducing the cost of forest inventories.Key words: Eucalypt plantations; airborne laser scanning; aboveground biomass; carbon stocks; remote sensing; forest inventory.

  5. LiCHy: The CAF’s LiDAR, CCD and Hyperspectral Integrated Airborne Observation System

    Directory of Open Access Journals (Sweden)

    Yong Pang

    2016-05-01

    Full Text Available We describe the design, implementation and performance of a novel airborne system, which integrates commercial waveform LiDAR, CCD (Charge-Coupled Device camera and hyperspectral sensors into a common platform system. CAF’s (The Chinese Academy of Forestry LiCHy (LiDAR, CCD and Hyperspectral Airborne Observation System is a unique system that permits simultaneous measurements of vegetation vertical structure, horizontal pattern, and foliar spectra from different view angles at very high spatial resolution (~1 m on a wide range of airborne platforms. The horizontal geo-location accuracy of LiDAR and CCD is about 0.5 m, with LiDAR vertical resolution and accuracy 0.15 m and 0.3 m, respectively. The geo-location accuracy of hyperspectral image is within 2 pixels for nadir view observations and 5–7 pixels for large off-nadir observations of 55° with multi-angle modular when comparing to LiDAR product. The complementary nature of LiCHy’s sensors makes it an effective and comprehensive system for forest inventory, change detection, biodiversity monitoring, carbon accounting and ecosystem service evaluation. The LiCHy system has acquired more than 8000 km2 of data over typical forests across China. These data are being used to investigate potential LiDAR and optical remote sensing applications in forest management, forest carbon accounting, biodiversity evaluation, and to aid in the development of similar satellite configurations. This paper describes the integration of the LiCHy system, the instrument performance and data processing workflow. We also demonstrate LiCHy’s data characteristics, current coverage, and potential vegetation applications.

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

    Directory of Open Access Journals (Sweden)

    J. Jubanski

    2013-06-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  8. Coastal and tidal landform detection from high resolution topobathymetric LiDAR data

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  10. Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

    OpenAIRE

    Sandip Pal

    2014-01-01

    There is compelling evidence that the incomplete laser beam receiver field-of-view overlap (i.e., partial overlap) of ground-based vertically-pointing aerosol LiDAR restricts the observational range for detecting aerosol layer boundaries to a certain height above the LiDAR. This height varies from one to few hundreds of meters, depending on the transceiver geometry. The range, or height of full overlap, is defined as the minimum distance at which the laser beam is completely imaged onto the ...

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

    Science.gov (United States)

    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

  12. Aggregating pixel-level basal area predictions derived from LiDAR data to industrial forest stands in North-Central Idaho

    Science.gov (United States)

    Andrew T. Hudak; Jeffrey S. Evans; Nicholas L. Crookston; Michael J. Falkowski; Brant K. Steigers; Rob Taylor; Halli Hemingway

    2008-01-01

    Stand exams are the principal means by which timber companies monitor and manage their forested lands. Airborne LiDAR surveys sample forest stands at much finer spatial resolution and broader spatial extent than is practical on the ground. In this paper, we developed models that leverage spatially intensive and extensive LiDAR data and a stratified random sample of...

  13. A comparison of accuracy and cost of LiDAR versus stand exam data for landscape management on the Malheur National Forest

    Science.gov (United States)

    Susan Hummel; A. T. Hudak; E. H. Uebler; M. J. Falkowski; K. A. Megown

    2011-01-01

    Foresters are increasingly interested in remote sensing data because they provide an overview of landscape conditions, which is impractical with field sample data alone. Light Detection and Ranging (LiDAR) provides exceptional spatial detail of forest structure, but difficulties in processing LiDAR data have limited their application beyond the research community....

  14. Fusion of LiDAR and aerial imagery for the estimation of downed tree volume using Support Vector Machines classification and region based object fitting

    Science.gov (United States)

    Selvarajan, Sowmya

    The study classifies 3D small footprint full waveform digitized LiDAR fused with aerial imagery to downed trees using Support Vector Machines (SVM) algorithm. Using small footprint waveform LiDAR, airborne LiDAR systems can provide better canopy penetration and very high spatial resolution. The small footprint waveform scanner system Riegl LMS-Q680 is addition with an UltraCamX aerial camera are used to measure and map downed trees in a forest. The various data preprocessing steps helped in the identification of ground points from the dense LiDAR dataset and segment the LiDAR data to help reduce the complexity of the algorithm. The haze filtering process helped to differentiate the spectral signatures of the various classes within the aerial image. Such processes, helped to better select the features from both sensor data. The six features: LiDAR height, LiDAR intensity, LiDAR echo, and three image intensities are utilized. To do so, LiDAR derived, aerial image derived and fused LiDAR-aerial image derived features are used to organize the data for the SVM hypothesis formulation. Several variations of the SVM algorithm with different kernels and soft margin parameter C are experimented. The algorithm is implemented to classify downed trees over a pine trees zone. The LiDAR derived features provided an overall accuracy of 98% of downed trees but with no classification error of 86%. The image derived features provided an overall accuracy of 65% and fusion derived features resulted in an overall accuracy of 88%. The results are observed to be stable and robust. The SVM accuracies were accompanied by high false alarm rates, with the LiDAR classification producing 58.45%, image classification producing 95.74% and finally the fused classification producing 93% false alarm rates The Canny edge correction filter helped control the LiDAR false alarm to 35.99%, image false alarm to 48.56% and fused false alarm to 37.69% The implemented classifiers provided a powerful tool for

  15. Analysis of diverse direct arylation polymerization (DArP) conditions toward the efficient synthesis of polymers converging with stille polymers in organic solar cells

    DEFF Research Database (Denmark)

    Livi, Francesco; Gobalasingham, Nemal S.; Thompson, Barry C.

    2016-01-01

    Despite the emergence of direct arylation polymerization (DArP) as an alternative method to traditional cross-coupling routes like Stille polymerization, the exploration of DArP polymers in practical applications like polymer solar cells (PSCs) is limited. DArP polymers tend to have a reputation...... for being marginally inferior to Stille counterparts due to the increased presence of defects that result from unwanted side reactions in direct arylation, such as unselective C-H bond activation and homocoupling. We report ten DArP protocols across the three major classes of DArP to generate poly[(2,5-bis...... was synthesized in superheated THF with Cs2CO3, neodecanoic acid, and P(o-anisyl)3, it generated polymers of exceptional quality that performed comparably to Stille counterparts in both roll coated ITO-free and spin-coated ITO devices....

  16. Leaf Movements of Indoor Plants Monitored by Terrestrial LiDAR.

    Science.gov (United States)

    Herrero-Huerta, Mónica; Lindenbergh, Roderik; Gard, Wolfgang

    2018-01-01

    Plant leaf movement is induced by some combination of different external and internal stimuli. Detailed geometric characterization of such movement is expected to improve understanding of these mechanisms. A metric high-quality, non-invasive and innovative sensor system to analyze plant movement is Terrestrial LiDAR (TLiDAR). This technique has an active sensor and is, therefore, independent of light conditions, able to obtain accurate high spatial and temporal resolution point clouds. In this study, a movement parameterization approach of leaf plants based on TLiDAR is introduced. For this purpose, two Calathea roseopicta plants were scanned in an indoor environment during 2 full-days, 1 day in natural light conditions and the other in darkness. The methodology to estimate leaf movement is based on segmenting individual leaves using an octree-based 3D-grid and monitoring the changes in their orientation by Principal Component Analysis. Additionally, canopy variations of the plant as a whole were characterized by a convex-hull approach. As a result, 9 leaves in plant 1 and 11 leaves in plant 2 were automatically detected with a global accuracy of 93.57 and 87.34%, respectively, compared to a manual detection. Regarding plant 1, in natural light conditions, the displacement average of the leaves between 7.00 a.m. and 12.30 p.m. was 3.67 cm as estimated using so-called deviation maps. The maximum displacement was 7.92 cm. In addition, the orientation changes of each leaf within a day were analyzed. The maximum variation in the vertical angle was 69.6° from 12.30 to 6.00 p.m. In darkness, the displacements were smaller and showed a different orientation pattern. The canopy volume of plant 1 changed more in the morning (4.42 dm 3 ) than in the afternoon (2.57 dm 3 ). The results of plant 2 largely confirmed the results of the first plant and were added to check the robustness of the methodology. The results show how to quantify leaf orientation variation and leaf

  17. Leaf Movements of Indoor Plants Monitored by Terrestrial LiDAR

    Directory of Open Access Journals (Sweden)

    Mónica Herrero-Huerta

    2018-02-01

    Full Text Available Plant leaf movement is induced by some combination of different external and internal stimuli. Detailed geometric characterization of such movement is expected to improve understanding of these mechanisms. A metric high-quality, non-invasive and innovative sensor system to analyze plant movement is Terrestrial LiDAR (TLiDAR. This technique has an active sensor and is, therefore, independent of light conditions, able to obtain accurate high spatial and temporal resolution point clouds. In this study, a movement parameterization approach of leaf plants based on TLiDAR is introduced. For this purpose, two Calathea roseopicta plants were scanned in an indoor environment during 2 full-days, 1 day in natural light conditions and the other in darkness. The methodology to estimate leaf movement is based on segmenting individual leaves using an octree-based 3D-grid and monitoring the changes in their orientation by Principal Component Analysis. Additionally, canopy variations of the plant as a whole were characterized by a convex-hull approach. As a result, 9 leaves in plant 1 and 11 leaves in plant 2 were automatically detected with a global accuracy of 93.57 and 87.34%, respectively, compared to a manual detection. Regarding plant 1, in natural light conditions, the displacement average of the leaves between 7.00 a.m. and 12.30 p.m. was 3.67 cm as estimated using so-called deviation maps. The maximum displacement was 7.92 cm. In addition, the orientation changes of each leaf within a day were analyzed. The maximum variation in the vertical angle was 69.6° from 12.30 to 6.00 p.m. In darkness, the displacements were smaller and showed a different orientation pattern. The canopy volume of plant 1 changed more in the morning (4.42 dm3 than in the afternoon (2.57 dm3. The results of plant 2 largely confirmed the results of the first plant and were added to check the robustness of the methodology. The results show how to quantify leaf orientation variation

  18. Evaluating solar irradiance over facades in high building cities, based on LiDAR technology

    International Nuclear Information System (INIS)

    Martínez-Rubio, A.; Sanz-Adan, F.; Santamaría-Peña, J.; Martínez, Araceli

    2016-01-01

    Highlights: • A method for evaluating solar irradiance over façades in building cities with mutual shading. • It calculates irradiance curves in all building façades, using LiDAR and irradiance information. • Solar irradiation maps of the city buildings are really important for urban planning. • It allows to selection BIPV elements depending of the irradiation in each façade point. • The model can be extrapolated to all the building envelope. - Abstract: Arranging a solar irradiation map of the buildings of a city is a valuable tool for sustainable urban planning in regard to non-carbonized criteria in important applications. Such applications may include: selection of materials for the building envelope and insulation according to the irradiation received at each point; monitoring the installation of photovoltaic systems to ensure that they are located in the optimal irradiance zones; or building restoration to improve the energy efficiency and electric generation. The proposed method enables to estimate the incidence of the solar irradiance as well as to visualize the effect it produces in every region of the buildings that compose the urban area of a city. The process includes the use of Laser Imaging Detection and Ranging (LiDAR) information along with 5-min horizontal irradiance data. This developed algorithm has been verified through being applied to different building envelopes distributed in different geographical areas. The results demonstrate a satisfied performance which makes that the methodology can be extrapolated to any city where the LiDAR Data and irradiance information are available, permitting an accurate analysis of the solar irradiance over the building envelopes. The algorithm succeeds in obtaining a map of solar radiation captured by the envelope of any urban building that estimates the photovoltaic power generation depending on the geographic location and on the influence of shading caused by adjacent buildings. The provided

  19. Tree species classification using within crown localization of waveform LiDAR attributes

    Science.gov (United States)

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

    2017-11-01

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

  20. Flood Damage Analysis: First Floor Elevation Uncertainty Resulting from LiDAR-Derived Digital Surface Models

    Directory of Open Access Journals (Sweden)

    José María Bodoque

    2016-07-01

    Full Text Available The use of high resolution ground-based light detection and ranging (LiDAR datasets provides spatial density and vertical precision for obtaining highly accurate Digital Surface Models (DSMs. As a result, the reliability of flood damage analysis has improved significantly, owing to the increased accuracy of hydrodynamic models. In addition, considerable error reduction has been achieved in the estimation of first floor elevation, which is a critical parameter for determining structural and content damages in buildings. However, as with any discrete measurement technique, LiDAR data contain object space ambiguities, especially in urban areas where the presence of buildings and the floodplain gives rise to a highly complex landscape that is largely corrected by using ancillary information based on the addition of breaklines to a triangulated irregular network (TIN. The present study provides a methodological approach for assessing uncertainty regarding first floor elevation. This is based on: (i generation an urban TIN from LiDAR data with a density of 0.5 points·m−2, complemented with the river bathymetry obtained from a field survey with a density of 0.3 points·m−2. The TIN was subsequently improved by adding breaklines and was finally transformed to a raster with a spatial resolution of 2 m; (ii implementation of a two-dimensional (2D hydrodynamic model based on the 500-year flood return period. The high resolution DSM obtained in the previous step, facilitated addressing the modelling, since it represented suitable urban features influencing hydraulics (e.g., streets and buildings; and (iii determination of first floor elevation uncertainty within the 500-year flood zone by performing Monte Carlo simulations based on geostatistics and 1997 control elevation points in order to assess error. Deviations in first floor elevation (average: 0.56 m and standard deviation: 0.33 m show that this parameter has to be neatly characterized in order

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

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Jitendra [ORNL; HargroveJr., William Walter [United States Department of Agriculture (USDA), United States Forest Service (USFS); Norman, Steven P [United States Department of Agriculture (USDA), United States Forest Service (USFS); Hoffman, Forrest M [ORNL; Newcomb, Doug [U.S. Fish and Wildlife Service

    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.

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

    Science.gov (United States)

    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.

  3. A categorical, improper probability method for combining NDVI and LiDAR elevation information for potential cotton precision agricultural applications

    Science.gov (United States)

    An algorithm is presented to fuse the Normalized Difference Vegetation Index (NDVI) with Light Detection and Ranging (LiDAR) elevation data to produce a map potentially useful for the site-specific scouting and pest management of several insect pests. In cotton, these pests include the Tarnished Pl...

  4. Development of a LiDAR derived digital elevation model (DEM) as Input to a METRANS geographic information system (GIS).

    Science.gov (United States)

    2011-05-01

    This report describes an assessment of digital elevation models (DEMs) derived from : LiDAR data for a subset of the Ports of Los Angeles and Long Beach. A methodology : based on Monte Carlo simulation was applied to investigate the accuracy of DEMs ...

  5. A comparison of forest height prediction from FIA field measurement and LiDAR data via spatial models

    Science.gov (United States)

    Yuzhen Li

    2009-01-01

    Previous studies have shown a high correspondence between tree height measurements acquired from airborne LiDAR and that those measured using conventional field techniques. Though these results are very promising, most of the studies were conducted over small experimental areas and tree height was measured carefully or using expensive instruments in the field, which is...

  6. Forecasting Forest Inventory Using Imputed Tree Lists for LiDAR Grid Cells and a Tree-List Growth Model

    Directory of Open Access Journals (Sweden)

    Sean M. Lamb

    2018-03-01

    Full Text Available A method to forecast forest inventory variables derived from light detection and ranging (LiDAR would increase the usefulness of such data in future forest management. We evaluated the accuracy of forecasted inventory from imputed tree lists for LiDAR grid cells (20 × 20 m in spruce (Picea sp. plantations and tree growth predicted using a locally calibrated tree-list growth model. Tree lists were imputed by matching measurements from a library of sample plots with grid cells based on planted species and the smallest sum of squared difference between six inventory variables. Total and merchantable basal area, total and merchantable volume, Lorey’s height, and quadratic mean diameter increments predicted using imputed tree lists were highly correlated (0.75–0.86 with those from measured tree lists in 98 validation plots. Percent root mean squared error ranged from 12.8–49.0% but was much lower (4.9–13.5% for plots with ≤10% LiDAR-derived error for all plot-matched variables. When compared with volumes from 15 blocks harvested 3–5 years after LiDAR acquisition, average forecasted volume differed by only 1.5%. To demonstrate the novel application of this method for operational management decisions, annual commercial thinning was planned at grid-cell resolution from 2018–2020 using forecasted inventory variables and commercial thinning eligibility rules.

  7. Reconstructing the Roman Site “Aquis Querquennis” (Bande, Spain from GPR, T-LiDAR and IRT Data Fusion

    Directory of Open Access Journals (Sweden)

    Iván Puente

    2018-03-01

    Full Text Available This work presents the three-dimensional (3D reconstruction of one of the most important archaeological sites in Galicia: “Aquis Querquennis” (Bande, Spain using in-situ non-invasive ground-penetrating radar (GPR and Terrestrial Light Detection and Ranging (T-LiDAR techniques, complemented with infrared thermography. T-LiDAR is used for the recording of the 3D surface of this particular case and provides high resolution 3D digital models. GPR data processing is performed through the novel software tool “toGPRi”, developed by the authors, which allows the creation of a 3D model of the sub-surface and the subsequent XY images or time-slices at different depths. All these products are georeferenced, in such a way that the GPR orthoimages can be combined with the orthoimages from the T-LiDAR for a complete interpretation of the site. In this way, the GPR technique allows for the detection of the structures of the barracks that are buried, and their distribution is completed with the structure measured by the T-LiDAR on the surface. In addition, the detection of buried elements made possible the identification and labelling of the structures of the surface and their uses. These structures are additionally inspected with infrared thermography (IRT to determine their conservation condition and distinguish between original and subsequent constructions.

  8. Separation of Ground and Low Vegetation Signatures in LiDAR Measurements of Salt-Marsh Environments

    NARCIS (Netherlands)

    Wang, C.; Menenti, M.; Stoll, M.P.; Feola, A.; Belluco, E.; Marani, M.

    2009-01-01

    Light detection and ranging (LiDAR) has been shown to have a great potential in the accurate characterization of forest systems; however, its application to salt-marsh environments is challenging because the characteristic short vegetation does not give rise to detectable differences between first

  9. Leaf area index, biomass carbon and growth rate of radiata pine genetic types and relationships with LiDAR

    Science.gov (United States)

    Peter N. Beets; Stephen Reutebuch; Mark O. Kimberley; Graeme R. Oliver; Stephen H. Pearce; Robert J. McGaughey

    2011-01-01

    Relationships between discrete-return light detection and ranging (LiDAR) data and radiata pine leaf area index (LAI), stem volume, above ground carbon, and carbon sequestration were developed using 10 plots with directly measured biomass and leaf area data, and 36 plots with modelled carbon data. The plots included a range of genetic types established on north- and...

  10. Gaussian Mixture Model with Variable Components for Full Waveform LiDAR Data Decomposition and RJMCMC Algorithm

    Directory of Open Access Journals (Sweden)

    ZHAO Quanhua

    2015-12-01

    Full Text Available Full waveform LiDAR data record the signal of the backscattered laser pulse. The elevation and the energy information of ground targets can be effectively obtained by decomposition of the full waveform LiDAR data. Therefore, waveform decomposition is the key to full waveform LiDAR data processing. However, in waveform decomposition, determining the number of the components is a focus and difficult problem. To this end, this paper presents a method which can automatically determine the number. First of all, a given full waveform LiDAR data is modeled on the assumption that energy recorded at elevation points satisfy Gaussian mixture distribution. The constraint function is defined to steer the model fitting the waveform. Correspondingly, a probability distribution based on the function is constructed by Gibbs. The Bayesian paradigm is followed to build waveform decomposition model. Then a RJMCMC (reversible jump Markov chain Monte Carlo scheme is used to simulate the decomposition model, which determines the number of the components and decomposes the waveform into a group of Gaussian distributions. In the RJMCMC algorithm, the move types are designed, including updating parameter vector, splitting or merging Gaussian components, birth or death Gaussian component. The results obtained from the ICESat-GLAS waveform data of different areas show that the proposed algorithm is efficient and promising.

  11. Report of the African Regional Seminar on Educational Evaluation (Dar es Salaam, Tanzania, April 7-May 2, 1975).

    Science.gov (United States)

    International Bank for Reconstruction and Development, Washington, DC.

    The Regional Seminar on Educational Evaluation held in Dar es Salaam, Tanzania, from 7 April to 2 May 1975, was organized as a follow-up activity to a study carried out by the International Institute for Educational Planning (IIEP, Paris) in 1973-1974. The International Bank for Reconstruction and Development had in 1973 requested the IIEP to…

  12. DEM Development from Ground-Based LiDAR Data: A Method to Remove Non-Surface Objects

    Directory of Open Access Journals (Sweden)

    Maneesh Sharma

    2010-11-01

    Full Text Available Topography and land cover characteristics can have significant effects on infiltration, runoff, and erosion processes on watersheds. The ability to model the timing and routing of surface water and erosion is affected by the resolution of the digital elevation model (DEM. High resolution ground-based Light Detecting and Ranging (LiDAR technology can be used to collect detailed topographic and land cover characteristic data. In this study, a method was developed to remove vegetation from ground-based LiDAR data to create high resolution DEMs. Research was conducted on intensively studied rainfall–runoff plots on the USDA-ARS Walnut Gulch Experimental Watershed in Southeast Arizona. LiDAR data were used to generate 1 cm resolution digital surface models (DSM for 5 plots. DSMs created directly from LiDAR data contain non-surface objects such as vegetation cover. A vegetation removal method was developed which used a slope threshold and a focal mean filter method to remove vegetation and create bare earth DEMs. The method was validated on a synthetic plot, where rocks and vegetation were added incrementally. Results of the validation showed a vertical error of ±7.5 mm in the final DEM.

  13. Tropical Forests of Réunion Island Classified from Airborne Full-Waveform LiDAR Measurements

    Directory of Open Access Journals (Sweden)

    Xiaoxia Shang

    2016-01-01

    Full Text Available From an unprecedented experiment using airborne measurements performed over the rich forests of Réunion Island, this paper aims to present a methodology for the classification of diverse tropical forest biomes as retrieved from vertical profiles measured using a full-waveform LiDAR. This objective is met through the retrieval of both the canopy height and the Leaf Area Index (LAI, obtained as an integral of the foliage profile. The campaign involved sites ranging from coastal to rain forest, including tropical montane cloud forest, as found on the Bélouve plateau. The mean values of estimated LAI retrieved from the apparent foliage profile are between ~5 and 8 m2/m2, and the mean canopy height values are ~15 m for both tropical montane cloud and rain forests. Good agreement is found between LiDAR- and MODIS-derived LAI for moderate LAI (~5 m2/m2, but the LAI retrieved from LiDAR is larger than MODIS on thick rain forest sites (~8 against ~6 m2/m2 from MODIS. Regarding the characterization of tropical forest biomes, we show that the rain and montane tropical forests can be well distinguished from planted forests by the use of the parameters directly retrieved from LiDAR measurements.

  14. Using LiDAR and remote microclimate loggers to downscale near-surface air temperatures for site-level studies

    Science.gov (United States)

    Andrew D. George; Frank R. Thompson; John. Faaborg

    2015-01-01

    A spatial mismatch exists between regional climate models and conditions experienced by individual organisms. We demonstrate an approach to downscaling air temperatures for site-level studies using airborne LiDAR data and remote microclimate loggers. In 2012-2013, we established a temperature logger network in the forested region of central Missouri, USA, and obtained...

  15. Mapping aboveground carbon stocks using LiDAR data in Eucalyptus spp. plantations in the state of Sao Paulo, Brazil

    Science.gov (United States)

    Carlos Alberto Silva; Carine Klauberg; Samuel de Padua Chaves e Carvalho; Andrew T. Hudak; e Luiz Carlos Estraviz. Rodriguez

    2014-01-01

    Fast growing plantation forests provide a low-cost means to sequester carbon for greenhouse gas abatement. The aim of this study was to evaluate airborne LiDAR (Light Detection And Ranging) to predict aboveground carbon (AGC) stocks in Eucalyptus spp. plantations. Biometric parameters (tree height (Ht) and diameter at breast height (DBH)) were collected from...

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

    Science.gov (United States)

    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…

  17. Application of LiDAR data for hydrologic assessments of low-gradient coastal watershed drainage characteristics

    Science.gov (United States)

    Devendra Amatya; Carl Trettin; Sudhanshu Panda; Herbert. Ssegane

    2013-01-01

    Documenting the recovery of hydrologic functions following perturbations of a landscape/watershed is important to address issues associated with land use change and ecosystem restoration. High resolution LiDAR data for the USDA Forest Service Santee Experimental Forest in coastal South Carolina,USA was used to delineate the remnant historical water management...

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

    Science.gov (United States)

    Jitendra Kumar; Jon Weiner; William W. Hargrove; Steve Norman; Forrest M. Hoffman; Doug Newcomb

    2016-01-01

    Vegetation canopy structure is a critically important habitat 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...

  19. Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.

    Science.gov (United States)

    Guo, Qinghua; Wu, Fangfang; Pang, Shuxin; Zhao, Xiaoqian; Chen, Linhai; Liu, Jin; Xue, Baolin; Xu, Guangcai; Li, Le; Jing, Haichun; Chu, Chengcai

    2018-03-01

    With the growing population and the reducing arable land, breeding has been considered as an effective way to solve the food crisis. As an important part in breeding, high-throughput phenotyping can accelerate the breeding process effectively. Light detection and ranging (LiDAR) is an active remote sensing technology that is capable of acquiring three-dimensional (3D) data accurately, and has a great potential in crop phenotyping. Given that crop phenotyping based on LiDAR technology is not common in China, we developed a high-throughput crop phenotyping platform, named Crop 3D, which integrated LiDAR sensor, high-resolution camera, thermal camera and hyperspectral imager. Compared with traditional crop phenotyping techniques, Crop 3D can acquire multi-source phenotypic data in the whole crop growing period and extract plant height, plant width, leaf length, leaf width, leaf area, leaf inclination angle and other parameters for plant biology and genomics analysis. In this paper, we described the designs, functions and testing results of the Crop 3D platform, and briefly discussed the potential applications and future development of the platform in phenotyping. We concluded that platforms integrating LiDAR and traditional remote sensing techniques might be the future trend of crop high-throughput phenotyping.

  20. Applying inventory methods to estimate aboveground biomass from satellite light detection and ranging (LiDAR) forest height data

    Science.gov (United States)

    Sean P. Healey; Paul L. Patterson; Sassan Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman; Gretchen G. Moisen

    2012-01-01

    Light Detection and Ranging (LiDAR) returns from the spaceborne Geoscience Laser Altimeter (GLAS) sensor may offer an alternative to solely field-based forest biomass sampling. Such an approach would rely upon model-based inference, which can account for the uncertainty associated with using modeled, instead of field-collected, measurements. Model-based methods have...

  1. 2013-2014 U.S. Geological Survey CMGP LiDAR: Post Sandy (MA, NH, RI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: New England CMGP Sandy Lidar LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G13PD00796 Woolpert Order...

  2. Development of height-volume relationships in second growth Abies grandis for use with aerial LiDAR

    Science.gov (United States)

    Wade T. Tinkham; Alistair M. S. Smith; David L. R. Affleck; Jarred D. Saralecos; Michael J. Falkowski; Chad M. Hoffman; Andrew T. Hudak; Michael A. Wulder

    2016-01-01

    Following typical forest inventory protocols, individual tree volume estimates are generally derived via diameter-at-breast-height (DBH)-based allometry. Although effective, measurement of DBH is time consuming and potentially a costly element in forest inventories. The capacity of airborne light detection and ranging (LiDAR) to provide individual tree-level...

  3. One-Class Classification of Airborne LiDAR Data in Urban Areas Using a Presence and Background Learning Algorithm

    Directory of Open Access Journals (Sweden)

    Zurui Ao

    2017-09-01

    Full Text Available Automatic classification of light detection and ranging (LiDAR data in urban areas is of great importance for many applications such as generating three-dimensional (3D building models and monitoring power lines. Traditional supervised classification methods require training samples of all classes to construct a reliable classifier. However, complete training samples are normally hard and costly to collect, and a common circumstance is that only training samples for a class of interest are available, in which traditional supervised classification methods may be inappropriate. In this study, we investigated the possibility of using a novel one-class classification algorithm, i.e., the presence and background learning (PBL algorithm, to classify LiDAR data in an urban scenario. The results demonstrated that the PBL algorithm implemented by back propagation (BP neural network (PBL-BP could effectively classify a single class (e.g., building, tree, terrain, power line, and others from airborne LiDAR point cloud with very high accuracy. The mean F-score for all of the classes from the PBL-BP classification results was 0.94, which was higher than those from one-class support vector machine (SVM, biased SVM, and maximum entropy methods (0.68, 0.82 and 0.93, respectively. Moreover, the PBL-BP algorithm yielded a comparable overall accuracy to the multi-class SVM method. Therefore, this method is very promising in the classification of the LiDAR point cloud.

  4. Computing Risk to West Coast Intertidal Rocky Habitat due to Sea Level Rise using LiDAR Topobathy

    Science.gov (United States)

    Compared to marshes, little information is available on the potential for rocky intertidal habitats to migrate upward in response to sea level rise (SLR). To address this gap, we utilized topobathy LiDAR digital elevation models (DEMs) downloaded from NOAA’s Digital Coast G...

  5. 2011 U.S. Geological Survey (USGS) Alabama Topographic LiDAR: Baldwin County East and West

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — USGS Contract: G10PC00026 Task Order Number: G10PD02126 LiDAR was collected at a 2.0 meter nominal post spacing (2.0m GSD) for approximately 329 square miles of...

  6. Occupational exposure and health problems in small-scale industry workers in Dar es Salaam, Tanzania: a situation analysis.

    NARCIS (Netherlands)

    Rongo, L.M.B.; Barten, F.J.M.H.; Msamanga, G.I.; Heederik, D.; Dolmans, W.M.V.

    2004-01-01

    BACKGROUND: Workers in informal small-scale industries (SSI) in developing countries involved in welding, spray painting, woodwork and metalwork are exposed to various hazards with consequent risk to health. Aim To assess occupational exposure and health problems in SSI in Dar es Salaam, Tanzania.

  7. Vegetation mapping in the St Lucia estuary using very high-resolution multispectral imagery and LiDAR

    CSIR Research Space (South Africa)

    Lück-Vogel, Melanie

    2016-05-01

    Full Text Available mapping in the St Lucia estuary using very high 1 resolution multispectral imagery and LiDAR 2 Melanie Lück-Vogel a, c,*, Cikizwa Mbolambi a, Kelly Rautenbach b, Janine Adams b, Lara 3 van Niekerk a 4 a Council for Scientific and Industrial Research, P...

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

    Directory of Open Access Journals (Sweden)

    Jose A. Jimenez-Berni

    2018-02-01

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

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

    Science.gov (United States)

    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

  10. Effects of LiDAR point density and landscape context on the retrieval of urban forest biomass

    Science.gov (United States)

    Singh, K. K.; Chen, G.; McCarter, J. B.; Meentemeyer, R. K.

    2014-12-01

    Light Detection and Ranging (LiDAR), as an alternative to conventional optical remote sensing, is being increasingly used to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and better data accuracies, which however pose challenges to the procurement and processing of LiDAR data for large-area assessments. Reducing point density cuts data acquisition costs and overcome computational challenges for broad-scale forest management. However, how does that impact the accuracy of biomass estimation in an urban environment containing a great level of anthropogenic disturbances? The main goal of this study is to evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing regions of Charlotte, North Carolina, USA. We used multiple linear regression to establish the statistical relationship between field-measured biomass and predictor variables (PVs) derived from LiDAR point clouds with varying densities. We compared the estimation accuracies between the general Urban Forest models (no discrimination of forest type) and the Forest Type models (evergreen, deciduous, and mixed), which was followed by quantifying the degree to which landscape context influenced biomass estimation. The explained biomass variance of Urban Forest models, adjusted R2, was fairly consistent across the reduced point densities with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models using two representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, signifying the distance impact of development on biomass estimation. Our evaluation

  11. Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR.

    Science.gov (United States)

    Gordon, Christopher E; Price, Owen F; Tasker, Elizabeth M

    2017-07-01

    There is a public perception that large high-severity wildfires decrease biodiversity and increase fire hazard by homogenizing vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10 × 10 m, 30 × 30 m, 50 × 50 m, 100 × 100 m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5-3.0 m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22-40% lower in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seed banks varied at finer scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01 ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high-severity fires do not homogenize vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

    Alhashimi, Anas; Varagnolo, Damiano; Gustafsson, Thomas

    2015-12-11

    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.

  14. A Three Tier Architecture Applied to LiDAR Processing and Monitoring

    Directory of Open Access Journals (Sweden)

    Efrat Jaeger-Frank

    2006-01-01

    Full Text Available Emerging Grid technologies enable solving scientific problems that involve large datasets and complex analyses, which in the past were often considered difficult to solve. Coordinating distributed Grid resources and computational processes requires adaptable interfaces and tools that provide modularized and configurable environments for accessing Grid clusters and executing high performance computational tasks. Computationally intensive processes are also subject to a high risk of component failures and thus require close monitoring. In this paper we describe a scientific workflow approach to coordinate various resources via data analysis pipelines. We present a three tier architecture for LiDAR interpolation and analysis, a high performance processing of point intensive datasets, utilizing a portal, a scientific workflow engine and Grid technologies. Our proposed solution is available to the community in a unified framework through a shared cyberinfrastructure, the GEON portal, enabling scientists to focus on their scientific work and not be concerned with the implementation of the underlying infrastructure.

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

    Science.gov (United States)

    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)

  16. Digital elevation modeling via curvature interpolation for LiDAR data

    Directory of Open Access Journals (Sweden)

    Hwamog Kim

    2016-03-01

    Full Text Available Digital elevation model (DEM is a three-dimensional (3D representation of a terrain's surface - for a planet (including Earth, moon, or asteroid - created from point cloud data which measure terrain elevation. Its modeling requires surface reconstruction for the scattered data, which is an ill-posed problem and most computational algorithms become overly expensive as the number of sample points increases. This article studies an effective partial differential equation (PDE-based algorithm, called the curvature interpolation method (CIM. The new method iteratively utilizes curvature information, estimated from an intermediate surface, to construct a reliable image surface that contains all of the data points. The CIM is applied for DEM for point cloud data acquired by light detection and ranging (LiDAR technology. It converges to a piecewise smooth image, requiring O(N operations independently of the number of sample points, where $N$ is the number of grid points.

  17. Storage, Collection and Disposal of Kariakoo Market Wastes in Dar Es Salaam, Tanzania

    DEFF Research Database (Denmark)

    Yhdego, Michael

    1992-01-01

    In many developing countries, the market is still the most important source of commerce for traders and provisions for the general public. The transmission of disease in the market place involves factors relating to the host, the agent and the environment. This study examines the quality of solid...... waste management in Kariakoo market, Dar es Salaam. The main problems identified were poor market design and lack of a well organized waste storage, collection and disposal systems. Two-thirds of the waste consists of vegetable matter. Proposals for improved design of storage and collection facilities...... are described. Experiments revealed wastes from the market are readily decomposable by composting. A change in the design of covered markets and improvements in waste handling are essential to reduce the potential health hazards in developing countries....

  18. Reinstalación del Archivo Rubén Darío

    OpenAIRE

    Rudilla Barón, Paula; López Sánchez, Almudena

    2010-01-01

    El Archivo Rubén Darío recoge los documentos facilitados al Ministerio de Educación en 1956 por Doña Francisca Sánchez, compañera del poeta a partir del año 1899, año desde el cual conservó todos sus documentos hasta su muerte; y que fueron depositados posteriormente en la Facultad de Filología de la Universidad Complutense. Su ubicación definitiva es en la Biblioteca Histórica U.C.M., donde se lleva a cabo el proyecto de reinstalación para su óptima conservación a largo plazo. Parte de este ...

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

    Directory of Open Access Journals (Sweden)

    Anas Alhashimi

    2015-12-01

    Full Text Available 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.

  20. Interpersonal Conflicts and Styles of Managing Conflicts among Students at Bahir Dar University, Ethiopia

    Directory of Open Access Journals (Sweden)

    Arega Bazezew

    2017-07-01

    Full Text Available Interpersonal conflict happens everywhere and at any time and is inherent in all societies. However, the methods of managing such metamorphoses are quite different from one organisation to the other. The general objective of the study was to assess interpersonal conflicts and styles of managing conflicts among students at Bahir Dar University. Mixed-methods research composed of quantitative and qualitative approaches was implemented for the study. One‑way Multivariate Analysis of Variance was employed to identify the interaction effect between dependent and independent variables. The study showed that the major sources of conflicts were ethnic differences, religious diversity, sexual abuse, theft and insulting. It was also noted that compromising, avoiding and collaborating were frequently used conflict management styles between students. It is recommended that university leaders and students be expected to understand the real causes of conflicts for healthier management styles.

  1. Cholera Mortality during Urban Epidemic, Dar es Salaam, Tanzania, August 16, 2015-January 16, 20161.

    Science.gov (United States)

    McCrickard, Lindsey S; Massay, Amani Elibariki; Narra, Rupa; Mghamba, Janneth; Mohamed, Ahmed Abade; Kishimba, Rogath Saika; Urio, Loveness John; Rusibayamila, Neema; Magembe, Grace; Bakari, Muhammud; Gibson, James J; Eidex, Rachel Barwick; Quick, Robert E

    2017-12-01

    In 2015, a cholera epidemic occurred in Tanzania; most cases and deaths occurred in Dar es Salaam early in the outbreak. We evaluated cholera mortality through passive surveillance, burial permits, and interviews conducted with decedents' caretakers. Active case finding identified 101 suspected cholera deaths. Routine surveillance had captured only 48 (48%) of all cholera deaths, and burial permit assessments captured the remainder. We interviewed caregivers of 56 decedents to assess cholera management behaviors. Of 51 decedents receiving home care, 5 (10%) used oral rehydration solution after becoming ill. Caregivers reported that 51 (93%) of 55 decedents with known time of death sought care before death; 16 (29%) of 55 delayed seeking care for >6 h. Of the 33 (59%) community decedents, 20 (61%) were said to have been discharged from a health facility before death. Appropriate and early management of cholera cases can reduce the number of cholera deaths.

  2. Sexual history and contraception among women with induced and spontaneous abortion in Dar es Salaam

    DEFF Research Database (Denmark)

    Rasch, V; Mary, V; Urassa, E

    2007-01-01

    The objective of this study was to create sexual history profiles of women with illegally induced abortion (IA) and women with spontaneous abortion (SA) and describe the women's knowledge of, attitude to, and practice of contraception. The study was carried out in two settings, Temeke District...... Hospital (TDH) and Muhimbili Medical Centre (MMC) in Dar es Salaam. At TDH 362/603 (60 per cent) were identified as IA and 241/603 (40 per cent) as SA. At MMC the figures were 68/220 (31 per cent) IA and 152/220 (69 per cent) SA. Both groups were well informed about modern contraception. As a contrast...... the rate of ever users of contraception was low in both groups, although significantly lower among IA women than among SA women. Outcome of first pregnancy had been an induced abortion in significantly higher proportion of IA than of SA women. In conclusion, sexual intercourse before marriage is common...

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

    Science.gov (United States)

    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

  4. Acceptance of contraceptives among women who had an unsafe abortion in Dar es Salaam

    DEFF Research Database (Denmark)

    Rasch, Vibeke; Massawe, Siriel; Yambesi, Fortunata

    2004-01-01

    OBJECTIVE: To assess the need for post-abortion contraception and to determine if women who had an unsafe abortion will use a contraceptive method to avoid repeated unwanted pregnancies and STDs/HIV. METHOD: Women attending Temeke Municipal Hospital, Dar es Salaam, after an unsafe abortion...... or an induced abortion performed at the hospital (n=788) were counselled about contraception and the risk of contracting STDs/HIV. A free ward-based contraceptive service was offered and the women were asked to return for follow-up. RESULTS: Participants (90%) accepted the post-abortion contraceptive service....... Of these, 86% stated they were still using contraception 1-6 months after discharge. Initially, 55% of the women accepted to use condoms either alone or as part of double protection. After 1-6 months this proportion had dropped to 18%. Single women were significantly more likely to use condoms. CONCLUSION...

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

    Science.gov (United States)

    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

  6. The role of local government in promoting sustainable urban agriculture in Dar es Salaam and Copenhagen

    DEFF Research Database (Denmark)

    Halloran, Afton Marian Szasz; Magid, Jakob

    2013-01-01

    . This article looks at the importance of local and central governments in promoting sustainable urban agriculture. Through participatory action research, it examines the cases of Dar es Salaam, Tanzania and Copenhagen, Denmark to understand stakeholder interactions, as well as present and future barriers...... to the conservation of existing urban agriculture and future initiatives. The findings suggest that municipal recognition and institutional support for urban agriculture is an important component in increasing the sustainability of related initiatives. Local and central government plays a role in the legitimization......As a multifunctional activity and land use, urban agriculture supports a range of objectives, from urban greening to food security. However, it is often left out of urban policy. As a result of the highly contextual and cross-cutting nature of urban agriculture, there are relatively few...

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

    Science.gov (United States)

    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

  8. Fine-scale ignimbrite morphology revealed in LiDAR at Crater Lake, OR

    Science.gov (United States)

    Robinson, J. E.; Bacon, C. R.; Wright, H. M.

    2011-12-01

    Mount Mazama erupted ~7,700 years ago resulting in the collapse of Crater Lake caldera, ash fall across the Pacific Northwest, and emplacement of compositionally zoned ignimbrite. Early climactic ignimbrite contains uniform rhyodacitic pumice and traveled far from the vent, whereas late, less mobile ignimbrite is dominated by crystal-rich andesitic scoria and mafic crystal mush. Funded by the USGS, NPS, and FHWA, the DOGAMI-led Oregon LiDAR Consortium contracted with Watershed Services to collect ~800 km2 of LiDAR over Crater Lake National Park from Aug 2010 to Sept 2010. Ground laser returns have an average density of 1.63 returns/m2 over the heavily forested area of interest. The data have a lateral RMSE and vertical accuracy of 0.05 m. A bare earth terrain model allows a virtual removal of the forest, revealing fine-scale surface morphology, notably in the climactic ignimbrite. Secondary pyroclastic flows, explosion craters, erosion by water, and compaction-related deformation modified the originally smooth ignimbrite surface. Distinct pyroclastic flow fronts are evident in the LiDAR in Annie Creek valley. Leveed flows stand approximately 5 m above the lower ignimbrite surface, and individual toes are about 1-2 m high. Preliminary field checking indicates that rhyodacitic pumice dominates the lower ignimbrite surface, but the leveed flows are a subequal mix of locally oxidized rhyodacitic pumice and andesitic scoria. We hypothesize that these deposits were secondary pyroclastic flows formed by gravitational failure of late ignimbrite. In the Castle Creek valley, is a 2-meter collapse scarp that may have spawned a small secondary pyroclastic flow; several such headwall scarps are present in Sand Creek valley. Differential compaction features are common in many thick ignimbrites. We suggest this caused the deformation of the ignimbrite apparent in the LiDAR. In Annie Creek valley are a series of flow parallel asymmetric ridges, with shallower slopes toward the

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  11. A saturated SSR/DArT linkage map of Musa acuminata addressing genome rearrangements among bananas

    Directory of Open Access Journals (Sweden)

    Matsumoto Takashi

    2010-04-01

    Full Text Available Abstract Background The genus Musa is a large species complex which includes cultivars at diploid and triploid levels. These sterile and vegetatively propagated cultivars are based on the A genome from Musa acuminata, exclusively for sweet bananas such as Cavendish, or associated with the B genome (Musa balbisiana in cooking bananas such as Plantain varieties. In M. acuminata cultivars, structural heterozygosity is thought to be one of the main causes of sterility, which is essential for obtaining seedless fruits but hampers breeding. Only partial genetic maps are presently available due to chromosomal rearrangements within the parents of the mapping populations. This causes large segregation distortions inducing pseudo-linkages and difficulties in ordering markers in the linkage groups. The present study aims at producing a saturated linkage map of M. acuminata, taking into account hypotheses on the structural heterozygosity of the parents. Results An F1 progeny of 180 individuals was obtained from a cross between two genetically distant accessions of M. acuminata, 'Borneo' and 'Pisang Lilin' (P. Lilin. Based on the gametic recombination of each parent, two parental maps composed of SSR and DArT markers were established. A significant proportion of the markers (21.7% deviated (p Conclusions We propose a synthetic map with 11 linkage groups containing 489 markers (167 SSRs and 322 DArTs covering 1197 cM. This first saturated map is proposed as a "reference Musa map" for further analyses. We also propose two complete parental maps with interpretations of structural rearrangements localized on the linkage groups. The structural heterozygosity in P. Lilin is hypothesized to result from a duplication likely accompanied by an inversion on another chromosome. This paper also illustrates a methodological approach, transferable to other species, to investigate the mapping of structural rearrangements and determine their consequences on marker

  12. Determinants of condom use among antenatal clinic attendees in Dar es Salaam, Tanzania.

    Science.gov (United States)

    Msamanga, Gernard; Tchetgen, Eric; Spiegelman, Donna; Fawzi, Mary Kay Smith; Kaaya, Sylvia; Urassa, Willy; Hunter, David; Kapiga, Saidi; Fawzi, Wafaie

    2009-08-01

    To determine the demographic, socio-economic and psycho-social factors associated with condom use amongst antenatal clinic attendees in Dar es Salaam. A cross sectional study design was employed in four antenatal clinics in Dar es Salaam. Pregnant women were interviewed between April 1995 and July 1997 to find out if they have ever used a condom and if so whether they had used them consistently for all coital acts in the previous year. Of 1,585 women interviewed, 41% had their first sexual experience before age of 18 years and 82% had a history of having more than two sexual partners during their lifetime. Sixty-two percent of women had never used a condom. Although 40% had used a condom in the previous year only 12% used them consistently. Ever use of a condom increased significantly with the number of years of education of the respondent and her partner also with the respondent's financial independence. Women with > 9 years of education were twice as likely as women with condom users (prevalence ratio (PR) = 2.1, 95% confidence interval (CI) = 1.6-2.7). Professional women were almost twice as likely as housewives to have ever used a condom (PR = 1.8, 95% CI = 1.3-2.3). Women who reported that they have had more than four sexual partners during their lifetime were associated with nearly a four-fold higher lifetime rate of having ever used a condom, compared with a single lifetime partnership (PR = 3.9, 95% CI = 2.8-5.4). The reported prevalence of ever use of a condom amongst antenatal clinic attendees is low and inconsistent especially among HIV positive women. Deliberate effort should be used to ensure condom access, availability and correct and consistent use of condoms by women in all sexual acts.

  13. Use of Remotely Piloted Aircraft System and LiDAR for Alpine forested Landslide

    Science.gov (United States)

    Borgniet, Laurent; Lachenal, Philippe; Berger, Frédéric

    2017-04-01

    In the last decade Remotely Piloted Aircraft Systems (RPAS) technologies considerably evolved, improving flight stability, GPS positioning and payload. Recent researches shown that RPAS-SfM framework, combining high volumes data acquisition and fast treatments capacity, make it suitable for environmental monitoring. However, monitoring, in a short period, an active landslide with major land displacements in a context of unstable and vegetated mountainous area still represent a real challenge. In this study, we aimed at developing a reproducible and optimized cost-efficiency method to accurately survey active terrain movements. The combined use of two RPAS allows to i)better visualize at large scale (1km2) the phenomenon dimensions and velocity in order to ii) focus our efforts on a safe topographic and photogrammetric data acquisition. The study area is a re-activated landslide previously reported in 1966 by forest management services located near Beaufort in the French Alps. For six time steps between April and September 2017, we acquired aerial photos with two reflex camera (Visible and Near Infra-Red Bands) mounted on a hexacopter with a payload up to 4kg. A validation campaign with aerial LiDAR and Terrestrial Laser Scanner took place on June 2017. Comparison of the digital Surface models and orthophotos derived from RPAS flights gave satisfactory results. Spatial analysis in a GIS allowed a quantitative evaluation of heterogeneous behaviors and dynamic distributions of materials (mineral and vegetal) along the slope. Estimations of displaced volumes (500 000 m3) constitute a precious information for improving in emergency crisis the calibration of deposits place in order to avoid jam and flood on the road network. In this research, we demonstrate the feasibility of a repetitive RPAS based data acquisition method but some limitations still remain. Research efforts will now focus on DEM under vegetation cover determination combining RPAS adapted LiDAR, improved

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  16. Virtual Surveyor based Object Extraction from Airborne LiDAR data

    Science.gov (United States)

    Habib, Md. Ahsan

    Topographic feature detection of land cover from LiDAR data is important in various fields - city planning, disaster response and prevention, soil conservation, infrastructure or forestry. In recent years, feature classification, compliant with Object-Based Image Analysis (OBIA) methodology has been gaining traction in remote sensing and geographic information science (GIS). In OBIA, the LiDAR image is first divided into meaningful segments called object candidates. This results, in addition to spectral values, in a plethora of new information such as aggregated spectral pixel values, morphology, texture, context as well as topology. Traditional nonparametric segmentation methods rely on segmentations at different scales to produce a hierarchy of semantically significant objects. Properly tuned scale parameters are, therefore, imperative in these methods for successful subsequent classification. Recently, some progress has been made in the development of methods for tuning the parameters for automatic segmentation. However, researchers found that it is very difficult to automatically refine the tuning with respect to each object class present in the scene. Moreover, due to the relative complexity of real-world objects, the intra-class heterogeneity is very high, which leads to over-segmentation. Therefore, the method fails to deliver correctly many of the new segment features. In this dissertation, a new hierarchical 3D object segmentation algorithm called Automatic Virtual Surveyor based Object Extracted (AVSOE) is presented. AVSOE segments objects based on their distinct geometric concavity/convexity. This is achieved by strategically mapping the sloping surface, which connects the object to its background. Further analysis produces hierarchical decomposition of objects to its sub-objects at a single scale level. Extensive qualitative and qualitative results are presented to demonstrate the efficacy of this hierarchical segmentation approach.

  17. Characterization of an alpine tree line using airborne LiDAR data and physiological modeling.

    Science.gov (United States)

    Coops, Nicholas C; Morsdorf, Felix; Schaepman, Michael E; Zimmermann, Niklaus E

    2013-12-01

    Understanding what environmental drivers control the position of the alpine tree line is important for refining our understanding of plant stress and tree development, as well as for climate change studies. However, monitoring the location of the tree line position and potential movement is difficult due to cost and technical challenges, as well as a lack of a clear boundary. Advanced remote sensing technologies such as Light Detection and Ranging (LiDAR) offer significant potential to map short individual tree crowns within the transition zone despite the lack of predictive capacity. Process-based forest growth models offer a complementary approach by quantifying the environmental stresses trees experience at the tree line, allowing transition zones to be defined and ultimately mapped. In this study, we investigate the role remote sensing and physiological, ecosystem-based modeling can play in the delineation of the alpine tree line. To do so, we utilize airborne LiDAR data to map tree height and stand density across a series of altitudinal gradients from below to above the tree line within the Swiss National Park (SNP), Switzerland. We then utilize a simple process-based model to assess the importance of seasonal variations on four climatically related variables that impose non-linear constraints on photosynthesis. Our results indicate that all methods predict the tree line to within a 50 m altitudinal zone and indicate that aspect is not a driver of significant variations in tree line position in the region. Tree cover, rather than tree height is the main discriminator of the tree line at higher elevations. Temperatures in fall and spring are responsible for the major differences along altitudinal zones, however, changes in evaporative demand also control plant growth at lower altitudes. Our results indicate that the two methods provide complementary information on tree line location and, when combined, provide additional insights into potentially endangered

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

    Science.gov (United States)

    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.

  19. Object Tracking with LiDAR: Monitoring Taxiing and Landing Aircraft

    Directory of Open Access Journals (Sweden)

    Zoltan Koppanyi

    2018-02-01

    Full Text Available Mobile light detection and ranging (LiDAR sensors used in car navigation and robotics, such as the Velodyne’s VLP-16 and HDL-32E, allow for sensing the surroundings of the platform with high temporal resolution to detect obstacles, tracking objects and support path planning. This study investigates the feasibility of using LiDAR sensors for tracking taxiing or landing aircraft close to the ground to improve airport safety. A prototype system was developed and installed at an airfield to capture point clouds to monitor aircraft operations. One of the challenges of accurate object tracking using the Velodyne sensors is the relatively small vertical field of view (30°, 41.3° and angular resolution (1.33°, 2°, resulting in a small number of points of the tracked object. The point density decreases with the object–sensor distance, and is already sparse at a moderate range of 30–40 m. The paper introduces our model-based tracking algorithms, including volume minimization and cube trajectories, to address the optimal estimation of object motion and tracking based on sparse point clouds. Using a network of sensors, multiple tests were conducted at an airport to assess the performance of the demonstration system and the algorithms developed. The investigation was focused on monitoring small aircraft moving on runways and taxiways, and the results indicate less than 0.7 m/s and 17 cm velocity and positioning accuracy achieved, respectively. Overall, based on our findings, this technology is promising not only for aircraft monitoring but for airport applications.

  20. OPEN-SOURCE DIGITAL ELEVATION MODEL (DEMs EVALUATION WITH GPS AND LiDAR DATA

    Directory of Open Access Journals (Sweden)

    N. F. Khalid

    2016-09-01

    Full Text Available 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.

  1. Temperature Compensation for Radiometric Correction of Terrestrial LiDAR Intensity Data

    Directory of Open Access Journals (Sweden)

    Angus F. C. Errington

    2017-04-01

    Full Text Available Correction of terrestrial Light Detection and Ranging (LiDAR intensity data has been increasingly studied in recent years. The purpose is to obtain additional insight into the scanned environment that is not available from the geometric information alone. Radiometric correction, as the name implies, corrects the received intensity to standard reflectance values in the range of ( 0 , 1 . This correction typically compensates for the dependence of angle and distance. This paper presents an additional compensation for temperature that may be necessary for some LiDAR instruments such as the Faro Focus 3 D X 330 laser scanner. It is also shown that temperature compensation is not necessary for the Riegl VZ–400. Another important contribution of this work is the verification of a previously published radiometric correction in different environments. The correction was applied to two different Terrestrial Laser Scanner (TLS instruments: a Faro Focus 3 D X 330 and Riegl VZ-400. Overall, the VZ-400, without temperature compensation, produced better results with a Root Mean Square (RMS of the standard deviation of error being 0.053 and a RMS of the mean error of 0.036 compared to 0.069 and 0.046 for the Faro Focus 3 D X 330. It was found, for the case of the Faro device, that the temperature of the instrument played an important role in the accuracy of the results. The proposed temperature compensation method improved the RMS standard deviation of the error by 1.4 times and the RMS of the error by 2.6 times, compared to the uncompensated results.

  2. Full-waveform LiDAR echo decomposition based on wavelet decomposition and particle swarm optimization

    Science.gov (United States)

    Li, Duan; Xu, Lijun; Li, Xiaolu

    2017-04-01

    To measure the distances and properties of the objects within a laser footprint, a decomposition method for full-waveform light detection and ranging (LiDAR) echoes is proposed. In this method, firstly, wavelet decomposition is used to filter the noise and estimate the noise level in a full-waveform echo. Secondly, peak and inflection points of the filtered full-waveform echo are used to detect the echo components in the filtered full-waveform echo. Lastly, particle swarm optimization (PSO) is used to remove the noise-caused echo components and optimize the parameters of the most probable echo components. Simulation results show that the wavelet-decomposition-based filter is of the best improvement of SNR and decomposition success rates than Wiener and Gaussian smoothing filters. In addition, the noise level estimated using wavelet-decomposition-based filter is more accurate than those estimated using other two commonly used methods. Experiments were carried out to evaluate the proposed method that was compared with our previous method (called GS-LM for short). In experiments, a lab-build full-waveform LiDAR system was utilized to provide eight types of full-waveform echoes scattered from three objects at different distances. Experimental results show that the proposed method has higher success rates for decomposition of full-waveform echoes and more accurate parameters estimation for echo components than those of GS-LM. The proposed method based on wavelet decomposition and PSO is valid to decompose the more complicated full-waveform echoes for estimating the multi-level distances of the objects and measuring the properties of the objects in a laser footprint.

  3. Determinants of High Blood Pressure and Barriers to Diagnosis and Treatment in Dar es Salaam, Tanzania

    Science.gov (United States)

    ZACK, Rachel M.; IREMA, Kahema; KAZONDA, Patrick; LEYNA, Germana H.; LIU, Enju; SPIEGELMAN, Donna; FAWZI, Wafaie; NJELEKELA, Marina; KILLEWO, Japhet; DANAEI, Goodarz

    2017-01-01

    Objectives We assessed prevalence and determinants of high blood pressure, and barriers to diagnosis and treatment, in Dar es Salaam, Tanzania. Methods We surveyed and screened 2,174 community-dwelling adults aged ≥40 years in 2014 and conducted a follow-up after one year. Results Median blood pressure was 131/81 mmHg and hypertension prevalence was 37%. Mean adjusted difference in SBP was 4.0 mmHg for overweight, 6.3 mmHg for obese class I, and 10.5 mmHg for obese class II/III compared with normal weight participants. Those who were physically inactive had 4.8 mmHg higher SBP compared to those with more than 24 hours of moderate or vigorous activity per week. Drinkers of at least 10 grams of alcohol per day had 4.5 mmHg higher SBP than did non-drinkers. Among hypertensives, 48% were diagnosed, 22% were treated, and 10% were controlled. Hypertensives without health insurance were 12% less likely to be diagnosed than insured hypertensives. Of referred participants, 68% sought care, but only 27% were on treatment and 8% had controlled blood pressure at follow-up. Reasons for not seeking care included lack of symptoms, cost of visit, and lack of time. Reasons for not being on treatment included lack of symptoms, not being prescribed treatment, and having finished one course of treatment. Conclusions Major risk factors for hypertension in Dar es Salaam are overweight, obesity, inadequate physical activity, and limited access to quality medical care. Increased insurance coverage and community-based screening, along with quality medical care and patient education, may help control this burgeoning epidemic. PMID:27648720

  4. Diagnóstico Territorial Integral del municipio de Ciudad Darío

    Directory of Open Access Journals (Sweden)

    Laurent Dietsch

    2010-12-01

    Full Text Available EN ESTE ARTÍCULO SE PRESENTA EL “DIAGNÓSTICO TERRITORIAL INTEGRAL de Ciudad Darío” realizado como trabajo de fin de curso de la Maestría en Desarrollo Rural de la Universidad Centroamericana. Este estudio ha buscado contribuir a la formulación de propuestas de intervención de los actores sociales del municipio de Ciudad Darío sobre los procesos estratégicos de desarrollo del territorio. Se realizó unazonificación integral del municipio, identificándose cuatro zonas: una zona alta, campesina de agricultura de subsistencia; una zona de laderas secas; una planicie seca de latifundio ganadero; y finalmente, una zona de llanos y vegas fértiles de riego semi-intensivo. Posteriormente, se identificaron y clasificaron por capital (ambiental, económico, social-humano y político-institucional y nivel territorial, los principales procesos de cambio que afectan o podrían afectar al municipio. Su análisis permitió caracterizar las principales oportunidades y amenazas para el desarrollo del territorio y, al relacionarlo con las fortalezas y debilidades identificadas en la zonificación, evidenciar los principales factores que podrían incidir en el municipio y sus principales retos. Para enfrentar estos retos, se identificaron tres ejes estratégicos: la reducción de los niveles de inseguridad alimentaria y vulnerabilidad ambiental del municipio; el fomento integral de las cadenas de producción de hortalizas; y la prevención de riesgos sociales. Para cada uno de estos ejes se ha definido un conjunto de acciones ordenadas por capital y nivel territorial, orientadas a incidir sobre los principales procesos de cambio identificados. Finalmente, se definieron ejes estratégicos transversales enfocados al desarrollo de capacidades de incidir sobre los procesos claves de desarrollo del municipio.

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

    International Nuclear Information System (INIS)

    Jones, Benjamin M; Stoker, Jason M; Gibbs, Ann E; Richmond, Bruce M; Grosse, Guido; Romanovsky, Vladimir E; Douglas, Thomas A; Kinsman, Nicole E 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 km 2 study area on the Beaufort Sea coastal plain of northern Alaska. We detected statistically significant change (99% confidence interval), defined as contiguous areas (>10 m 2 ) 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. (letter)

  6. Elevated blood pressure among primary school children in Dar es salaam, Tanzania: prevalence and risk factors.

    Science.gov (United States)

    Muhihi, Alfa J; Njelekela, Marina A; Mpembeni, Rose N M; Muhihi, Bikolimana G; Anaeli, Amani; Chillo, Omary; Kubhoja, Sulende; Lujani, Benjamin; Maghembe, Mwanamkuu; Ngarashi, Davis

    2018-02-13

    Whilst the burden of non-communicable diseases is increasing in developing countries, little data is available on blood pressure among Tanzanian children. This study aimed at determining the blood pressure profiles and risk factors associated with elevated blood pressure among primary school children in Dar es Salaam, Tanzania. We conducted a cross sectional survey among 446 children aged 6-17 years from 9 randomly selected primary schools in Dar es Salaam. We measured blood pressure using a standardized digital blood pressure measuring machine (Omron Digital HEM-907, Tokyo, Japan). We used an average of the three blood pressure readings for analysis. Elevated blood pressure was defined as average systolic or diastolic blood pressure ≥ 90th percentile for age, gender and height. The proportion of children with elevated blood pressure was 15.2% (pre-hypertension 4.4% and hypertension 10.8%). No significant gender differences were observed in the prevalence of elevated BP. Increasing age and overweight/obese children were significantly associated with elevated BP (p = 0.0029 and p < 0.0001) respectively. Similar associations were observed for age and overweight/obesity with hypertension. (p = 0.0506 and p < 0.0001) respectively. In multivariate analysis, age above 10 years (adjusted RR = 3.63, 95% CI = 1.03-7.82) was significantly and independently associated with elevated BP in this population of school age children. We observed a higher proportion of elevated BP in this population of school age children. Older age and overweight/obesity were associated with elevated BP. Assessment of BP and BMI should be incorporated in school health program in Tanzania to identify those at risk so that appropriate interventions can be instituted before development of associated complications.

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

    Science.gov (United States)

    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.

  8. Darüşşifas Where Music Threapy was Practiced During Anatolian Seljuks and Ottomans / Selçuklu ve Osmanlı Darüşşifalarında Müzikle Tedavi

    Directory of Open Access Journals (Sweden)

    Gülşen Erdal

    2013-03-01

    Full Text Available Abstract Music therapy, one of the oldest treatment methods known, dates back to thousands of years. Turks’ using music therapy practices in hospitals -Ottoman and Seljuk hospitals- built with appropriate acoustic in the treatment of mental disorders, utilizing the books which included the researches done by scientists such as İbni Sina, Razî, Farabî, Hasan Şuurî and in Gevrekzade Hasan Efendi in music therapy and improving music therapy practices exemplarily in the period of Ottomans and Seljukians is assessed as the first serious music therapy practices. Darüşşifa is one of the names given to medical and educational establishments which give people health service depending on practice and observation and treated patients in Turkish and Islamic world. Turks started various reconstruction activities following their settlement in Anatolia. Within a short period, they built several types of artifacts such as; caravansaries, madrasahs, mosques, darüşşifas. In Seljukian and Ottoman darüşşifas, medical subjects were taught according to researches and scientific principals, and surgeons were educated at medical madrasahs as well. Medical health care service was provided in those places. In this study, of darüşşifas where music therapy was practised the ones surviving today and having importance have been analyzed so as to emphasize how curative power of art history and music was used by Turkish people centuries ago. From this point of view, Kayseri Gevher Nesibe Tıp Medresesi (Medical madrasah (1206, Divriği Ulu Camii ve Darüşşifası (Mosque and Hospital (1228, Amasya Darüşşifası (1309, Fatih Darüşşifası (1470 Edirne Sultan II. Bayezid Darüşşifası (1488, Süleymaniye Tıp Medresesi and Şifahanesi (Medical Madrasah and Hospital (1556 have been examined in this study as the featured ones among the institutions where music therapy was practised. Özet Müziğin insanlar üzerinde bıraktığı psikolojik ve fiziksel

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  11. Calibration and Validation of a Detailed Architectural Canopy Model Reconstruction for the Simulation of Synthetic Hemispherical Images and Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Magnus Bremer

    2017-02-01

    Full Text Available Canopy density measures such as the Leaf Area Index (LAI have become standardized mapping products derived from airborne and terrestrial Light Detection And Ranging (aLiDAR and tLiDAR, respectively data. A specific application of LiDAR point clouds is their integration into radiative transfer models (RTM of varying complexity. Using, e.g., ray tracing, this allows flexible simulations of sub-canopy light condition and the simulation of various sensors such as virtual hemispherical images or waveform LiDAR on a virtual forest plot. However, the direct use of LiDAR data in RTMs shows some limitations in the handling of noise, the derivation of surface areas per LiDAR point and the discrimination of solid and porous canopy elements. In order to address these issues, a strategy upgrading tLiDAR and Digital Hemispherical Photographs (DHP into plausible 3D architectural canopy models is suggested. The presented reconstruction workflow creates an almost unbiased virtual 3D representation of branch and leaf surface distributions, minimizing systematic errors due to the object–sensor relationship. The models are calibrated and validated using DHPs. Using the 3D models for simulations, their capabilities for the description of leaf density distributions and the simulation of aLiDAR and DHP signatures are shown. At an experimental test site, the suitability of the models, in order to systematically simulate and evaluate aLiDAR based LAI predictions under various scan settings is proven. This strategy makes it possible to show the importance of laser point sampling density, but also the diversity of scan angles and their quantitative effect onto error margins.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  14. Effects of the D1 dopamine receptor agonist dihydrexidine (DAR-0100A) on working memory in schizotypal personality disorder.

    Science.gov (United States)

    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

  15. Habitat productivity and pyrethroid susceptibility status of Aedes aegypti mosquitoes in Dar es Salaam, Tanzania.

    Science.gov (United States)

    Mathias, Leah; Baraka, Vito; Philbert, Anitha; Innocent, Ester; Francis, Filbert; Nkwengulila, Gamba; Kweka, Eliningaya J

    2017-06-09

    Aedes aegypti (Diptera: Culicidae) is the main vector of the dengue virus globally. Dengue vector control is mainly based on reducing the vector population through interventions, which target potential breeding sites. However, in Tanzania, little is known about this vector's habitat productivity and insecticide susceptibility status to support evidence-based implementation of control measures. The present study aimed at assessing the productivity and susceptibility status of A. aegypti mosquitoes to pyrethroid-based insecticides in Dar es Salaam, Tanzania. An entomological assessment was conducted between January and July 2015 in six randomly selected wards in Dar es Salaam, Tanzania. Habitat productivity was determined by the number of female adult A. aegypti mosquitoes emerged per square metre. The susceptibility status of adult A. aegypti females after exposure to 0.05% deltamethrin, 0.75% permethrin and 0.05% lambda-cyhalothrin was evaluated using the standard WHO protocols. Mortality rates were recorded after 24 h exposure and the knockdown effect was recorded at the time points of 10, 15, 20, 30, 40, 50 and 60 min to calculate the median knockdown times (KDT 50 and KDT 95 ). The results suggest that disposed tyres had the highest productivity, while water storage tanks had the lowest productivity among the breeding habitats Of A. aegypti mosquitoes. All sites demonstrated reduced susceptibility to deltamethrin (0.05%) within 24 h post exposure, with mortalities ranging from 86.3 ± 1.9 (mean ± SD) to 96.8 ± 0.9 (mean ± SD). The lowest and highest susceptibilities were recorded in Mikocheni and Sinza wards, respectively. Similarly, all sites demonstrated reduced susceptibility permethrin (0.75%) ranging from 83.1 ± 2.1% (mean ± SD) to 96.2 ± 0.9% (mean ± SD), in Kipawa and Sinza, respectively. Relatively low mortality rates were observed in relation to lambda-cyhalothrin (0.05%) at all sites, ranging from 83.1 ± 0

  16. Financial sustainability in municipal solid waste management – Costs and revenues in Bahir Dar, Ethiopia

    International Nuclear Information System (INIS)

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

    2014-01-01

    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

  17. Financial sustainability in municipal solid waste management – Costs and revenues in Bahir Dar, Ethiopia

    Energy Technology Data Exchange (ETDEWEB)

    Lohri, Christian Riuji, E-mail: christian.lohri@eawag.ch; Camenzind, Ephraim Joseph, E-mail: ephraimcamenzind@hotmail.com; Zurbrügg, Christian, E-mail: christian.zurbruegg@eawag.ch

    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

  18. eEcoLiDAR, eScience infrastructure for ecological applications of LiDAR point clouds: reconstructing the 3D ecosystem structure for animals at regional to continental scales

    Directory of Open Access Journals (Sweden)

    W. Daniel Kissling

    2017-07-01

    Full Text Available The lack of high-resolution measurements of 3D ecosystem structure across broad spatial extents impedes major advancements in animal ecology and biodiversity science. We aim to fill this gap by using Light Detection and Ranging (LiDAR technology to characterize the vertical and horizontal complexity of vegetation and landscapes at high resolution across regional to continental scales. The newly LiDAR-derived 3D ecosystem structures will be applied in species distribution models for breeding birds in forests and marshlands, for insect pollinators in agricultural landscapes, and songbirds at stopover sites during migration. This will allow novel insights into the hierarchical structure of animal-habitat associations, into why animal populations decline, and how they respond to habitat fragmentation and ongoing land use change. The processing of these massive amounts of LiDAR point cloud data will be achieved by developing a generic interactive eScience environment with multi-scale object-based image analysis (OBIA and interpretation of LiDAR point clouds, including data storage, scalable computing, tools for machine learning and visualisation (feature selection, annotation/segmentation, object classification, and evaluation, and a PostGIS spatial database. The classified objects will include trees, forests, vegetation strata, edges, bushes, hedges, reedbeds etc. with their related metrics, attributes and summary statistics (e.g. vegetation openness, height, density, vertical biomass distribution etc.. The newly developed eScience tools and data will be available to other disciplines and applications in ecology and the Earth sciences, thereby achieving high impact. The project will foster new multi-disciplinary collaborations between ecologists and eScientists and contribute to training a new generation of geo-ecologists.

  19. Sexual behaviours and associated factors among students at Bahir Dar University: a cross sectional study.

    Science.gov (United States)

    Mulu, Wondemagegn; Yimer, Mulat; Abera, Bayeh

    2014-12-06

    Sexual behaviour is the core of sexuality matters in adolescents and youths. Their modest or dynamic behaviour vulnerable them to risky sexual behaviours. In Ethiopia, there is scarcity of multicentered representative data on sexual behaviours in students to have a national picture at higher education. This study therefore conducted to assess sexual behaviours and associated factors at Bahir Dar University, Ethiopia. A cross sectional study was conducted among Bahir Dar University students from December to February 2013. Multistage sampling and self administered questionnaires were employed. Descriptive statistics such as frequency and mean were used to describe the study participants in relation to relevant variables. Multivariate analysis was carried for those variables that had a p-value of ≤ 0.2 in the bivariate analysis to identify the predictor variables. Of the 817 study participants, 297 (36.4%) students had ever had sex. The mean age at first sexual practice was 18.6 years. Unprotected sex, having multiple sex partners, sex with commercial sex workers and sex for the exchange of money was practiced by 184 (62%), 126 (42.7%), 22 (7.4%) and 12 (4%) of sexually active students, respectively. The proportion of attending night clubs and watching porn videos was 130 (15.8%) and 534 (65.4%), respectively. Male respondents had significant positive association with watching porn videos (AOR = 4.8, CI = 3.49 - 6.54) and attending night clubs (AOR = 3.9, CI = 2.3 - 6.7). Watching porn videos, attending night clubs, khat chewing and taking alcohol frequently were significantly associated for ever had sex and having multiple sexual partners. Khat chewing practice (AOR = 8.5, CI =1.31 - 55.5) and attending night clubs (AOR = 4.6, CI = 1.8 - 11.77) had statistical significant association with the purpose of sexual intercourse for the sake of money and for having sex with commercial sex workers, respectively. Significant number of students had different risky sexual

  20. Informal urban settlements and cholera risk in Dar es Salaam, Tanzania.

    Science.gov (United States)

    Penrose, Katherine; de Castro, Marcia Caldas; Werema, Japhet; Ryan, Edward T

    2010-03-16

    As a result of poor economic opportunities and an increasing shortage of affordable housing, much of the spatial growth in many of the world's fastest-growing cities is a result of the expansion of informal settlements where residents live without security of tenure and with limited access to basic infrastructure. Although inadequate water and sanitation facilities, crowding and other poor living conditions can have a significant impact on the spread of infectious diseases, analyses relating these diseases to ongoing global urbanization, especially at the neighborhood and household level in informal settlements, have been infrequent. To begin to address this deficiency, we analyzed urban environmental data and the burden of cholera in Dar es Salaam, Tanzania. Cholera incidence was examined in relation to the percentage of a ward's residents who were informal, the percentage of a ward's informal residents without an improved water source, the percentage of a ward's informal residents without improved sanitation, distance to the nearest cholera treatment facility, population density, median asset index score in informal areas, and presence or absence of major roads. We found that cholera incidence was most closely associated with informal housing, population density, and the income level of informal residents. Using data available in this study, our model would suggest nearly a one percent increase in cholera incidence for every percentage point increase in informal residents, approximately a two percent increase in cholera incidence for every increase in population density of 1000 people per km(2) in Dar es Salaam in 2006, and close to a fifty percent decrease in cholera incidence in wards where informal residents had minimally improved income levels, as measured by ownership of a radio or CD player on average, in comparison to wards where informal residents did not own any items about which they were asked. In this study, the range of access to improved sanitation