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Sample records for dar mohasebe sathe

  1. Sathasivan ("Saths") Cooper: Award for Distinguished Contributions to the International Advancement of Psychology.

    Science.gov (United States)

    2014-11-01

    The Award for Distinguished Contributions to the International Advancement of Psychology is given to individuals who have made sustained and enduring contributions to international cooperation and the advancement of knowledge in psychology. The 2014 recipient is Sathasivan ("Saths") Cooper. Cooper is active in global cooperation in psychology for the public and the discipline's benefit so that psychology can truly serve all of humanity. The first psychologist from outside the West to lead the International Union of Psychological Science, he is the driving force behind the Pan-African Psychology Union and continues to ensure that less-developed psychology dispensations play meaningful roles in international psychology." Cooper's award citation, biography, and a selected bibliography are presented here.

  2. DAR ES SALAAM CITY, TANZANIA

    African Journals Online (AJOL)

    Engineering geological mapping of Dar es Salaam city in Tanzania has been carried out using .... faces and road cuts. The studied material ... for regional and city master planning, and these are geomorphological, geological, geo-hazard ...

  3. 2002 Willapa Bay LiDAR Project

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA contracted with Spencer B. Gross, Inc. (SBG) to obtain airborne LiDAR of Willapa Bay, Washington during low tide conditions. The LiDAR data was processed to...

  4. 2006 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Lewis County, WA

    Data.gov (United States)

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

  5. 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...

  6. 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...

  7. 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)...

  8. 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)...

  9. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Tulalip Partnership

    Data.gov (United States)

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

  10. 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 LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data on a...

  11. 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...

  12. 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...

  13. Saginaw Bay, MI LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME:(NRCS) Saginaw Bay, MI LiDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G11PD01254 Woolpert Order...

  14. 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...

  15. 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...

  16. University of Dar es Salaam Library Journal

    African Journals Online (AJOL)

    University of Dar es Salaam Library Journal. ... Secondary Education Development Plan (SEDP) and the provision of library service in Tanzania: a Case ... Sustainability of the Health Management Information System in Kinondoni and Muheza ...

  17. 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...

  18. 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...

  19. 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...

  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. 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

  2. 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 per

  3. 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...

  4. 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 &...

  5. 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 ?...

  6. 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...

  7. 2003 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Yakima 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 77 square miles and covers a...

  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. 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...

  10. 2005 Puget Sound LiDAR Consortium (PSLC) Bare-Earth Topographic LiDAR: Lynnwood

    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. Lynnwood, Snohomish County, Washington. This...

  11. 2007 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Sumpter, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data for the USDA Forest Service on September 17, 2007. The project covers an 8-mile...

  12. 2011 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Rattlesnake

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data on six days between September 15th and November 5th, and from November 6th ? 13th,...

  13. 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...

  14. 2003 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Yakima 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 77 square miles and covers a...

  15. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Entiat

    Data.gov (United States)

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

  16. 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...

  17. 2005 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Yakima County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint collected Light Detection and Ranging (LiDAR) data to complete the 2005 project for Yakima County. This project has partial coverage of Yakima County,...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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)...

  3. Characterizing Lava Flows With LiDAR

    Science.gov (United States)

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

    2009-12-01

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

  4. DAR: A Modern Institutional Repository with a Scalability Twist

    OpenAIRE

    Mikhail, Youssef; Adly, Noha; Nagi, Magdy

    2012-01-01

    The Digital Assets Repository (DAR) is an Institutional Repository developed at the Bibliotheca Alexandrina to manage the full lifecycle of a digital asset: its creation and ingestion, its metadata management, storage and archival in addition to the necessary mechanisms for publishing and dissemination. DAR was designed with a focus on integrating DAR with different sources of digital objects and metadata in addition to integration with applications built on top of the repository. As a modern...

  5. 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,...

  6. 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...

  7. '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

  8. 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...

  9. 2006 OSIP OGRIP Coastal 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...

  10. LiDAR - An emerging tool for geological applications

    Science.gov (United States)

    Stoker, Jason M.

    2012-01-01

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

  11. 2011 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Kittitas-Colockum Study Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data on 6 days between September 15th and November 5th, 2010 for the Puget Sound LiDAR...

  12. Tensor Modeling Based for Airborne LiDAR Data Classification

    Science.gov (United States)

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

    2016-06-01

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

  13. 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.

  14. Georeferenced LiDAR 3D Vine Plantation Map Generation

    OpenAIRE

    Meritxell Queraltó; Jordi Llop; Emilio Gil; Jordi Llorens

    2011-01-01

    The use of electronic devices for canopy characterization has recently been widely discussed. Among such devices, LiDAR sensors appear to be the most accurate and precise. Information obtained with LiDAR sensors during reading while driving a tractor along a crop row can be managed and transformed into canopy density maps by evaluating the frequency of LiDAR returns. This paper describes a proposed methodology to obtain a georeferenced canopy map by combining the information obtained with LiD...

  15. DAR Assisted Layer-by-Layer Assembly of Aromatic Compounds

    Institute of Scientific and Technical Information of China (English)

    姜思光; 陈晓东; 张莉; 刘鸣华

    2003-01-01

    A facile DAR (diphenylamine-4-diazonium-formaldehyde resin)assisted layer-by-layer (LbL) assembly of uitrathin organic film of aromatic compounds has been investigated. The muitilayer of pyrene or anthracene was fabricated through simple dipping of the glass slide into the mixed solution of DAR with the target compounds. In this method, DAR acted as an assistant compound to help the assembling of the aromatic compounds. Such a convenient deposition method not only reserves the advantages of the traditional LbL technique but also simplifies the technique and extends the effectiveness of LbL technique to small molecules without any charge.

  16. 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...... 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...

  17. 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...

  18. 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...

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

    African Journals Online (AJOL)

    the coastal marine environment of Dar es Salaam and the remote Ras Dege. Creek. ... Creek and the Ocean Road sewer outfall was unfit for human consumption. ... has an estimated population of about ... annual growth rate of about 8%.

  20. 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...

  1. Automatic registration method for mobile LiDAR data

    Science.gov (United States)

    Wang, Ruisheng; Ferrie, Frank P.

    2015-01-01

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

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

    African Journals Online (AJOL)

    Abstract. The present study assessed the possibility of integrating vulnerable youths to ... crisis facing Dar es Salaam City using a case study of Kinondoni Municipality. ... Research methodology involved the use of quantitative method to collect ...

  3. 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...

  4. 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.

  5. Georeferenced LiDAR 3D vine plantation map generation.

    Science.gov (United States)

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

    2011-01-01

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

  6. Georeferenced LiDAR 3D Vine Plantation Map Generation

    Directory of Open Access Journals (Sweden)

    Meritxell Queraltó

    2011-06-01

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

  7. 2001-2002 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Clallam 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 with Clallam County. The data covers an area of approximately 524...

  8. 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,...

  9. 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,...

  10. 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...

  11. 2007 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,...

  12. 2007 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,...

  13. 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...

  14. Agrotóxico: que nome dar?

    Directory of Open Access Journals (Sweden)

    Márcia Gomide

    2005-12-01

    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.

  15. Uas Topographic Mapping with Velodyne LiDAR Sensor

    Science.gov (United States)

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

    2016-06-01

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

  16. 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

  17. 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.

  18. Mathematical modelling applied to LiDAR data

    Directory of Open Access Journals (Sweden)

    Javier Estornell

    2013-06-01

    Full Text Available The aim of this article is to explain the application of several mathematic calculations to LiDAR (Light Detection And Ranging data to estimate vegetation parameters and modelling the relief of a forest area in the town of Chiva (Valencia. To represent the surface that describes the topography of the area, firstly, morphological filters were applied iteratively to select LiDAR ground points. From these data, the Triangulated Irregular Network (TIN structure was applied to model the relief of the area. From LiDAR data the canopy height model (CHM was also calculated. This model allowed obtaining bare soil, shrub and tree vegetation mapping in the study area. In addition, biomass was estimated from measurements taken in the field in 39 circular plots of radius 0.5 m and the 95th percentile of the LiDAR height datanincluded in each plot. The results indicated a high relationship between the two variables (measurednbiomass and 95th percentile with a coeficient of determination (R2 of 0:73. These results reveal the importance of using mathematical modelling to obtain information of the vegetation and land relief from LiDAR data.

  19. Extraction of building by airborne LiDAR point cloud with support of ENVI LiDAR%ENVI LiDAR 支持下利用机载 LiDAR 点云提取建筑物

    Institute of Scientific and Technical Information of China (English)

    张杰; 贺清清; 王飞

    2016-01-01

    对机载激光雷达测量技术、ENVI LiDAR 软件、建筑物提取流程进行了介绍,以 ISPRS 第三委员会提供的机载激光雷达点云数据为基础,基于 ENVI LiDAR 5.1对实验区的建筑物进行了提取,并通过 ArcGIS 结合同地区影像对其质量进行评价,实验流程及结果有一定的参考意义。%Technology of Airborne LiDAR(Light Detection And Ranging),the ENVI LiDAR and the process of building extraction are intro-duced briefly in this paper. Then,based on the International Society for Photogrammetry and Remote Sensing(ISPRS)commission Ⅲ and ENVI LiDAR 5. 1,the buildings in testing area were extracted. The evaluation results of quality was learned by overlaying the buildings onto the image in same place through ArcGIS,and the process and results thereof have certain reference significance.

  20. Biomass Estimation for Individual Trees using Waveform LiDAR

    Science.gov (United States)

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

    2015-12-01

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

  1. Forest Road Detection Using LiDAR Data

    Institute of Scientific and Technical Information of China (English)

    Zahra Azizi; Akbar Najafi; Saeed Sadeghian

    2014-01-01

    We developed a three-step classification approach for forest road extraction utilizing LiDAR data. The first step employed the IDW method to interpolate LiDAR point data (first and last pulses) to achieve DSM, DTM and DNTM layers (at 1 m resolution). For this interpolation RMSE was 0.19 m. In the second step, the Support Vector Machine (SVM) was employed to classify the LiDAR data into two classes, road and non-road. For this classification, SVM indicated the merged distance layer with intensity data and yielded better identification of the road position. Assessments of the obtained results showed 63% correctness, 75% completeness and 52% quality of classification. In the next step, road edges were defined in the LiDAR-extracted layers, enabling accu-rate digitizing of the centerline location. More than 95% of the Li-DAR-derived road was digitized within 1.3 m to the field surveyed nor-mal. The proposed approach can provide thorough and accurate road inventory data to support forest management.

  2. 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.

  3. Development of a wind turbine LiDAR simulator

    OpenAIRE

    Schlipf, David; Trujillo , Juan José; Basterra, Valeria; Kühn, Martin

    2009-01-01

    Remote sensing techniques like LiDAR offer many novel applications to the wind energy community, e.g. fast and accurate measurements of inflow and wake wind fields from the turbine nacelle. The prospects of such a new technique are evaluated with a software tool simulating a nacelle-based LiDAR system. The paper presents the implementation and application of a simulator that has been conceived to support the design of wind field scanning procedures. The tool helps to optimize the hardware set...

  4. Raster Vs. Point Cloud LiDAR Data Classification

    Science.gov (United States)

    El-Ashmawy, N.; Shaker, A.

    2014-09-01

    Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the

  5. 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...

  6. 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...

  7. 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,...

  8. 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...

  9. Effective LiDAR Damage Detection: Comparing Two Detection Algorithms

    Institute of Scientific and Technical Information of China (English)

    BIAN Haitao; BAI Libin; WANG Xiaoyu; LIU Wangiu; CHEN Shenen; WANG Shengguo

    2011-01-01

    The health conditions of highway bridges is critical for sustained transportation operations. US federal government mandates that all bridges built with public funds are to be inspected visually every two years.There is a growing consensus that additional rapid and non-intrusive methods for bridge damage evaluation are needed. This paper explores the potential of applying ground-based laser scanners for bridge damage evaluation. LiDAR has the potential of providing high-density, full-field surface static imaging. Hence, it can generate volumetric quantification of concrete corrosion or steel erosion. By recording object surface topology, LiDAR can detect different damages on the bridge structure and differentiate damage types according to the surface flatness and smoothness. To determine the effectiveness of LiDAR damage detection, two damage detection algorithms are presented and compared using scans on actual bridge damages. The results demonstrate and validate LiDAR damage quantification, which can be a powerful tool for bridge condition evaluation.

  10. 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...

  11. Tree filtering for high density airborne LiDAR data

    NARCIS (Netherlands)

    Abd Rahman, M.Z.; Gorte, B.G.H.

    2008-01-01

    A high resolution Airborne LiDAR data creates better opportunity for an individual tree measurement and provides valuable results for more precise forest inventory. This paper presents tree filtering approach that able to separate dominant tree and undergrowth vegetation. The results can be used for

  12. 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...

  13. 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...

  14. Tree filtering for high density airborne LiDAR data

    NARCIS (Netherlands)

    Abd Rahman, M.Z.; Gorte, B.G.H.

    2008-01-01

    A high resolution Airborne LiDAR data creates better opportunity for an individual tree measurement and provides valuable results for more precise forest inventory. This paper presents tree filtering approach that able to separate dominant tree and undergrowth vegetation. The results can be used for

  15. 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- ... E-mail: andy4everyoung@gmail.com, aadega @bsum.edu.ng. Mobile Phone No: ..... The rain maker may also use a proto type (night) gun and a mirror enhanced with ...

  16. 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...

  17. 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...

  18. 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...

  19. Development and assessment of DArT markers in triticale.

    Science.gov (United States)

    Badea, A; Eudes, F; Salmon, D; Tuvesson, S; Vrolijk, A; Larsson, C-T; Caig, V; Huttner, E; Kilian, A; Laroche, André

    2011-05-01

    Triticale (X Triticosecale Wittm.) is a hybrid derived by crossing wheat (Triticum sp.) and rye (Secale sp.). Till date, only a limited number of simple sequence repeat (SSRs) markers have been used in triticale molecular analyses and there is a need to identify dedicated high-throughput molecular markers to better exploit this crop. The objective of this study was to develop and evaluate diversity arrays technology (DArT) markers in triticale. DArT marker technology offers a high level of multiplexing. Development of new markers from triticale accessions was combined with mining the large collection of previously developed markers in rye and wheat. Three genotyping arrays were used to analyze a collection of 144 triticale accessions. The polymorphism level ranged from 8.6 to 23.8% for wheat and rye DArT markers, respectively. Among the polymorphic markers, rye markers were the most abundant (3,109) followed by wheat (2,214) and triticale (719). The mean polymorphism information content values were 0.34 for rye DArT markers and 0.37 for those from triticale and wheat. High correlation was observed between similarity matrices derived from rye, triticale, wheat and combined marker sets, as well as for the cophenetic values matrices. Cluster analysis revealed genetic relationships among the accessions consistent with the agronomic and pedigree information available. The newly developed triticale DArT markers as well as those originated from rye and wheat provide high quality markers that can be used for diversity analyses and might be exploited in a range of molecular breeding and genomics applications in triticale.

  20. 2011 U.S. Geological Survey Topographic LiDAR: LiDAR for the North East

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — USGS Contract: G10PC00026, Task Order Number: G10PD02143 Task Order Numbers: G10PD01027 (ARRA) and G10PD02143 (non-ARRA) The LiDAR for the North East Project, funded...

  1. 2012 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Jefferson and Clallam Counties, 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 Jefferson/Clallam study area on March 23rd-25th, April 13th-15th, and May...

  2. 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...

  3. San Clemente Island Baseline LiDAR Mapping Final Report

    Science.gov (United States)

    2016-12-01

    bands, wavelength and spectral width of each band, and Global Positioning System (GPS) start/stop times. • IGM folder - scene_radiance_IGM.txt IGM...indicating tile edge effects were eliminated during processing. 3.1.2.2 Quality Control of the DEMs Quality control of the initial DEMs showed... negative changes) and accretion (positive changes) were found. Sources of error in elevation change maps include the basic LiDAR observations, spatial

  4. 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.

  5. Road Curb Extraction From Mobile LiDAR Point Clouds

    Science.gov (United States)

    Xu, Sheng; Wang, Ruisheng; Zheng, Han

    2017-02-01

    Automatic extraction of road curbs from uneven, unorganized, noisy and massive 3D point clouds is a challenging task. Existing methods often project 3D point clouds onto 2D planes to extract curbs. However, the projection causes loss of 3D information which degrades the performance of the detection. This paper presents a robust, accurate and efficient method to extract road curbs from 3D mobile LiDAR point clouds. Our method consists of two steps: 1) extracting the candidate points of curbs based on the proposed novel energy function and 2) refining the candidate points using the proposed least cost path model. We evaluated our method on a large-scale of residential area (16.7GB, 300 million points) and an urban area (1.07GB, 20 million points) mobile LiDAR point clouds. Results indicate that the proposed method is superior to the state-of-the-art methods in terms of robustness, accuracy and efficiency. The proposed curb extraction method achieved a completeness of 78.62% and a correctness of 83.29%. These experiments demonstrate that the proposed method is a promising solution to extract road curbs from mobile LiDAR point clouds.

  6. Characterizing Canopy Structure Using Waveform LiDAR

    Science.gov (United States)

    Wang, K.; Kumar, P.

    2016-12-01

    The structure of light penetration through the canopy plays an important role in water, carbon, and energy fluxes between the biosphere and the atmosphere. Canopy clumping, a description of foliage distribution, is one of the major aspects of canopy structure that significantly influence light and vegetation interaction. Airborne full-waveform LiDAR data contains large amounts of vegetation structural information, and is a powerful tool for providing detailed foliage distribution information for large areas of vegetation. In this study, we present a method for describing physical canopy clumping structure for individual trees that can resolve fine scale variations in foliage distribution. We first utilize the K-means clustering algorithm to extract structure from the large amounts of vegetation data provided by full-waveform LiDAR. Then we find representative traits for data clusters and use them to classify the clusters into three groups. Based on these traits, we draw conclusions about physical representations of each group, and identify two groups to contain structurally significant clusters. This study demonstrates that large amounts of canopy structural information can be extracted from waveform LiDAR data. The fine resolution canopy clumping structure found by the method described in this work can be used as valuable input for ecological models.

  7. Detecting and connecting agricultural ditches using LiDAR data

    Science.gov (United States)

    Roelens, Jennifer; Dondeyne, Stefaan; Van Orshoven, Jos; Diels, Jan

    2017-04-01

    High-resolution hydrological data are essential for spatially-targeted water resource management decisions and future modelling efforts. For Flanders, small water courses like agricultural ditches and their connection to the river network are incomplete in the official digital atlas. High-resolution LiDAR data offer the prospect for automated detection of ditches, but there is no established method or software to do so nor to predict how these are connected to each other and the wider hydrographic network. An aerial LiDAR database encompassing at least 16 points per square meter linked with simultaneously collected digital RGB aerial images, is available for Flanders. The potential of detecting agricultural ditches and their connectivity based on point LiDAR data was investigated in a 1.9 km2 study area located in the alluvial valley of the river Demer. The area consists of agricultural parcels and woodland with a ditch network of approximately 17 km. The entire network of open ditches, and the location of culverts were mapped during a field survey to test the effectiveness of the proposed method. In the first step of the proposed method, the LiDAR point data were transformed into a raster DEM with a 1-m resolution to reduce the amount of data to be analyzed. This was done by interpolating the bare earth points using the nearest neighborhood method. In a next step, a morphological approach was used for detecting a preliminary network as traditional flow algorithms are not suitable for detecting small water courses in low-lying areas. This resulted in a preliminary classified raster image with ditch and non-ditch cells. After eliminating small details that are the result of background noise, the resulting classified raster image was vectorized to match the format of the digital watercourse network. As the vectorisation does not always adequately represent the shape of linear features, the results did not meet the high-quality cartographic needs. The spatial accuracy

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

    OpenAIRE

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

    2012-01-01

    In this paper, multipath error on Global Navigation Satellite System (GNSS) signals in urban environments is characterized with the help of Light Detection and Ranging (LiDAR) measurements. For this purpose, LiDAR equipment and Global Positioning System (GPS) receiver implementing a multipath estimating architecture were used to collect data in an urban environment. This paper demonstrates how GPS and LiDAR measurements can be jointly used to model the environment and obtain robust receivers....

  9. 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...

  10. Weibull approximation of LiDAR waveforms for estimating the beam attenuation coefficient.

    Science.gov (United States)

    Montes-Hugo, Martin A; Vuorenkoski, Anni K; Dalgleish, Fraser R; Ouyang, Bing

    2016-10-03

    Tank experiments were performed at different water turbidities to examine relationships between the beam attenuation coefficient (c) and Weibull shape parameters derived from LiDAR waveforms measured with the Fine Structure Underwater LiDAR (FSUIL). Optical inversions were made at 532 nm, within a c range of 0.045-1.52 m-1, and based on a LiDAR system having two field-of-view (15 and 75.7 mrad) and two linear polarizations. Consistently, the Weibull scale parameter or P2 showed the strongest covariation with c and was a more accurate proxy with respect to the LiDAR attenuation coefficient.

  11. Data management based on geocoding index and adaptive visualization for airborne LiDAR

    Science.gov (United States)

    Zhi, Xiaodong

    2008-10-01

    With more surveying practice and deeper application, data post-process for airborne LiDAR system has been extracted lots of attention in data accuracy, post-process, fusion, modeling, automation and visualization. However, post-process and flexible visualization were found to be the bottle-neck which limits the LiDAR data usage for industrial applications. The cause of above bottle-neck problems is great capacity for LiDAR system. Thus in article a geocoding index based multivariate data management and adaptive visualization will be studied for based on the feature of airborne LiDAR's data to improve automatization of post-process and surveying efficiency.

  12. Disposal frequencies of selected recyclable wastes in Dar es Salaam.

    Science.gov (United States)

    Mgaya, Prosper; Nondek, Lubomir

    2004-01-01

    A statistical survey of households based upon questionnaires distributed via primary schools has been carried out in five wards of Dar es Salaam, Tanzania, to estimate disposal frequencies (number of items disposed per week) for newsprint, metal cans, glass and plastic containers and plastic shopping bags. Plastic shopping bags are disposed most frequently while glass containers are disposed least frequently. The statistical distribution of disposal frequencies, which seems to be influenced by household income, is well described by Poisson distribution. Disposal frequencies are mutually correlated at 95% level of probability despite the differences in disposal patterns of individual households.

  13. GEOBIA methods for LiDAR obtained point clouds

    OpenAIRE

    Tomljenović, Ivan

    2012-01-01

    This paper critically analyses the state of the art provided in today’s scientific »market of knowledge« concerning the subject of object delineation from LiDAR obtained 3D point clouds. Such approach became a very popular subject in many scientific fields (forestry, geography, archaeology, etc.). The author will give multiple examples on how other authors deal with object extraction and delineation from 3D point clouds. He will also give a brief introduction and explanation of terms such as ...

  14. LiDAR remote sensing applied to forest resources assessment

    OpenAIRE

    Fernández-Landa, Alfredo

    2015-01-01

    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...

  15. Koulujen sanitaatiotilanne Tansaniassa : Dar es Salaamin ja Moshin alueilla

    OpenAIRE

    Partanen, Lotta

    2013-01-01

    Tutkimuksen tavoitteena oli tehdä selvitys Tansanian koulujen sanitaatiotilanteesta sekä miettiä mahdollisia ratkaisuja sanitaatio-olojen parantamiseksi. Lisäksi tavoitteena oli tutkia kuivakäymälän toimivuutta paikallisissa olosuhteissa sekä pohtia, voisiko menetelmä toimia ratkaisuna koulujen sanitaatio-ongelmiin. Työ suoritettiin syksyllä 2012 Tansaniassa Dar es Salaamin ja Moshin kaupungeissa. Noin 47 miljoonan asukkaan Tansania sijaitsee Itä-Afrikassa Intian valtameren rannalla. Se o...

  16. Acerca de las "ilustraciones" de darío villegas

    OpenAIRE

    SANTIAGO MUTIS

    2004-01-01

    Más de cien dibujos inéditos de Darío Villegas, tomados de sus libretas de apuntes, ilustran todo este número de Desde el Jardín de Freud. Estos dibujos fueron realizados durante los últimos cuatro años, en forma totalmente independiente a la revista, pero que, de alguna manera, la "ilustran" o complementan, por el sólo hecho de haber sido realizados en el país, sacudido a todo lo largo y ancho de su territorio por la violencia, la destruccción, la muerte y sus t...

  17. 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.

  18. Applying the Moment Distance Framework to LiDAR Waveforms

    Science.gov (United States)

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

    2010-12-01

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

  19. IsoDAR - A Definitive Search for Sterile Neutrinos

    Science.gov (United States)

    Barletta, William

    2013-04-01

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

  20. 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...

  1. Comparisons between field- and LiDAR-based measures of stand structrual complexity

    Science.gov (United States)

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

    2010-01-01

    Forest structure, as measured by the physical arrangement of trees and their crowns, is a fundamental attribute of forest ecosystems that changes as forests progress through successional stages. We examined whether LiDAR data could be used to directly assess the successional stage of forests by determining the degree to which the LiDAR data would show the same relative...

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

    NARCIS (Netherlands)

    Van Den Eeckhout, Miet; Kerle, Norman; 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. Object-oriented identification of forested landslides with derivatives of single pulse LiDAR data

    NARCIS (Netherlands)

    Eeckhaut, van den M.; Kerle, N.; Poesen, J.; Hervas, J.

    2012-01-01

    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

  4. Jean Lafitte 2013, 1.0 Meter LiDAR, Classified point cloud

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Jean Lafitte,G13PD00214, 1.0 Meter LiDAR Survey Area in south of New Orleans and encompasses 77...

  5. 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...

  6. 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

  7. 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 Sala

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

    Science.gov (United States)

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

    2016-09-01

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

  9. Have I Been Here Before? A Method for Detecting Loop Closure With LiDAR

    Science.gov (United States)

    2015-01-01

    Have I Been Here Before? A Method for Detecting Loop Closure With LiDAR by John G Rogers III and Jason M Gregory ARL-TR-7165 January...TR-7165 January 2015 Have I Been Here Before? A Method for Detecting Loop Closure With LiDAR John G Rogers III and Jason M Gregory...

  10. 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...

  11. Classification of Spruce and Pine Trees Using Active Hyperspectral LiDAR

    NARCIS (Netherlands)

    Vauhkonen, J.; Hakala, T.; Suomalainen, J.M.; Kaasalainen, S.; Nevalainen, O.; Vastaranta, M.; Holopainen, M.; Hyyppa, J.

    2013-01-01

    Most forest inventories based on the use of remote-sensing data produce the required species-specific information by fusing data from different sources (e.g., Light Detection And Ranging (LiDAR) and spectral data). We tested an active hyperspectral LiDAR instrument in a laboratory measurement of spr

  12. 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 mediu

  13. 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

  14. 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...

  15. 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...

  16. 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

  17. 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...

  18. Tree crown delineation from high resolution airborne LiDAR based on densities of high points

    NARCIS (Netherlands)

    Rahman, M.Z.A.; Gorte, B.G.H.

    2009-01-01

    Tree detection and tree crown delineation from Airborne LiDAR has been focusing mostly on utilizing the canopy height model (CHM). This paper presents a method for individual tree crown delineation based on densities of high points (DHP) from the high resolution Airborne LiDAR. The DHP method relies

  19. 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

  20. 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...

  1. 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.

  2. 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...

  3. Acetazolamide-responsive exercise-induced episodic ataxia associated with a novel homozygous DARS2 mutation.

    Science.gov (United States)

    Synofzik, Matthis; Schicks, Julia; Lindig, Tobias; Biskup, Saskia; Schmidt, Thorsten; Hansel, Jochen; Lehmann-Horn, Frank; Schöls, Ludger

    2011-10-01

    Leukoencephalopathy with brain stem and spinal cord involvement and brain lactate elevation (LBSL) was recently shown to be caused by mutations in the DARS2 gene, encoding a mitochondrial aspartyl-tRNA synthetase. So far, affected individuals were invariably compound heterozygous for two mutations in DARS2, and drug treatments have remained elusive. Prospective 2-year follow-up of the natural history of the main presenting symptoms in a homozygous DARS2 mutation carrier, followed by a 60 day treatment with acetazolamide in two different doses and with two random treatment interruptions. The patient presented with exercise-induced paroxysmal gait ataxia and areflexia as an atypical phenotype associated with a novel homozygous DARS2 mutation. These features showed an excellent dose-dependent, sustained treatment response to a carbonic anhydrase inhibitor. Pathogenic mutations in episodic ataxia genes were excluded, thus making it highly unlikely that this phenotype was because of episodic ataxia as a second disorder besides LBSL. This case demonstrates that DARS2 mutation homozygosity is not lethal, as suggested earlier, but compatible with a rather benign disease course. More importantly, it extends the phenotypic spectrum of LBSL and reveals that at least some DARS2-associated phenotypic features might be readily treatable. However, future observations of paroxsymal ataxia and, possibly, areflexia in other DARS2-mutated patients are warranted to further corroborate our finding that DARS2 mutations can lead to a paroxsymal ataxia phenotype.

  4. Flood Modeling Using a Synthesis of Multi-Platform LiDAR Data

    Directory of Open Access Journals (Sweden)

    Ryan M. Csontos

    2013-09-01

    Full Text Available This study examined the utility of a high resolution ground-based (mobile and terrestrial Light Detection and Ranging (LiDAR dataset (0.2 m point-spacing supplemented with a coarser resolution airborne LiDAR dataset (5 m point-spacing for use in a flood inundation analysis. The techniques for combining multi-platform LiDAR data into a composite dataset in the form of a triangulated irregular network (TIN are described, and quantitative comparisons were made to a TIN generated solely from the airborne LiDAR dataset. For example, a maximum land surface elevation difference of 1.677 m and a mean difference of 0.178 m were calculated between the datasets based on sample points. Utilizing the composite and airborne LiDAR-derived TINs, a flood inundation comparison was completed using a one-dimensional steady flow hydraulic modeling analysis. Quantitative comparisons of the water surface profiles and depth grids indicated an underestimation of flooding extent, volume, and maximum flood height using the airborne LiDAR data alone. A 35% increase in maximum flood height was observed using the composite LiDAR dataset. In addition, the extents of the water surface profiles generated from the two datasets were found to be statistically significantly different. The urban and mountainous characteristics of the study area as well as the density (file size of the high resolution ground based LiDAR data presented both opportunities and challenges for flood modeling analyses.

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Science.gov (United States)

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

    2012-10-30

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

  8. Modelling Sensor and Target effects on LiDAR Waveforms

    Science.gov (United States)

    Rosette, J.; North, P. R.; Rubio, J.; Cook, B. D.; Suárez, J.

    2010-12-01

    The aim of this research is to explore the influence of sensor characteristics and interactions with vegetation and terrain properties on the estimation of vegetation parameters from LiDAR waveforms. This is carried out using waveform simulations produced by the FLIGHT radiative transfer model which is based on Monte Carlo simulation of photon transport (North, 1996; North et al., 2010). The opportunities for vegetation analysis that are offered by LiDAR modelling are also demonstrated by other authors e.g. Sun and Ranson, 2000; Ni-Meister et al., 2001. Simulations from the FLIGHT model were driven using reflectance and transmittance properties collected from the Howland Research Forest, Maine, USA in 2003 together with a tree list for a 200m x 150m area. This was generated using field measurements of location, species and diameter at breast height. Tree height and crown dimensions of individual trees were calculated using relationships established with a competition index determined for this site. Waveforms obtained by the Laser Vegetation Imaging Sensor (LVIS) were used as validation of simulations. This provided a base from which factors such as slope, laser incidence angle and pulse width could be varied. This has enabled the effect of instrument design and laser interactions with different surface characteristics to be tested. As such, waveform simulation is relevant for the development of future satellite LiDAR sensors, such as NASA’s forthcoming DESDynI mission (NASA, 2010), which aim to improve capabilities of vegetation parameter estimation. ACKNOWLEDGMENTS We would like to thank scientists at the Biospheric Sciences Branch of NASA Goddard Space Flight Center, in particular to Jon Ranson and Bryan Blair. This work forms part of research funded by the NASA DESDynI project and the UK Natural Environment Research Council (NE/F021437/1). REFERENCES NASA, 2010, DESDynI: Deformation, Ecosystem Structure and Dynamics of Ice. http

  9. LiDAR Analysis of Hector Mine Fault Scarp Degradation

    Science.gov (United States)

    Zhang, X.; Hudnut, K. W.; Glennie, C. L.; Sousa, F.; Stock, J. M.; Akciz, S. O.

    2014-12-01

    The Mw 7.1 right-lateral strike-slip Hector Mine earthquake occurred on 10/16/1999 and generated an approximately 48 km long surface rupture. The Lavic Lake fault and the central section of the Bullion fault and several lesser faults ruptured, characterized by maximum strike slip of 5.25 ±0.85 m [Treiman, 2002]. As a very remote and un-populated area of the Mojave Desert, southern California, the study area is highly favorable for fault degradation studies with essentially no influence from vegetation or human activity. Airborne LiDAR (light detection and ranging) data and terrestrial laser scanning (TLS) are used to evaluate the form and rate of degradation of scarps along the Hector Mine fault rupture, California, USA. Airborne LiDAR data were acquired in 2000 and 2012 and these data were differenced using a newly developed algorithm for point cloud matching, which is improved over prior methods by accounting for scan geometry error sources. Using the bi-temporal data (scrutinizing profiles from 2000 & 2012), parameters for a fault scarp diffusion model are estimated and then a simulation result is generated to predict the evolved landform shape at the time of the 2014 TLS data set. Results are checked against TLS 2014 data collected at five key sites within the maximum slip field study area. In the past, scarp degradation has been mostly investigated using traditional survey methods (e.g., measuring elevations of points in a line perpendicular to the scarp) that require time-consuming field work and tend to introduce bias and variance due to data limitations. Airborne, mobile and terrestrial LiDAR data offer great potential to precisely document and rigorously determine morphologic degradation of fault scarps [Hilley et al., 2010]. In the present study, a unique set of data have been acquired at three points in time across several classic types of fault scarps and offset fault zone features. This allows progress in assessing the fitting of functions and

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

    Science.gov (United States)

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

    2016-12-01

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

  11. Getting the Most Neutrinos out of IsoDAR

    CERN Document Server

    Ciuffoli, Emilio; Mohammed, Hosam; Zhao, Fengyi; Deliyergiyev, Maksym

    2016-01-01

    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 7Li converter, yielding 8Li 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 7Li is replaced with 7Li 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 percent. The first also substantially reduces the quantity of high purity 7Li which is needed.

  12. Full waveform hyperspectral LiDAR for terrestrial laser scanning.

    Science.gov (United States)

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

    2012-03-26

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

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

    Directory of Open Access Journals (Sweden)

    Stefan Dongus

    2009-05-01

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

  14. 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

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

    Science.gov (United States)

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

    2009-05-01

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

  16. S-DARS broadcast from inclined, elliptical orbits

    Science.gov (United States)

    Briskman, Robert D.; Prevaux, Robert J.

    2004-04-01

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

  17. 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.

  18. 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...... cervical cancer screening can be increased in Dar es Salaam. Special attention should be paid to women of low education and women of high parity. In addition, knowledge and awareness raising campaigns that goes hand in hand with culturally acceptable screening services will likely lead to an increased...

  19. 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......, 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...

  20. 4D Near Real-Time Environmental Monitoring Using Highly Temporal LiDAR

    Science.gov (United States)

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

    2016-04-01

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

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

    Science.gov (United States)

    2013-05-10

    Survey. Map data ©2013 Google 9 Data Collecting Process 5.3.2 In order to collect data, the LiDAR would be placed on a cart and a MATLAB ...program was used to collect data of one scan, or one 360 degree rotation, of the LiDAR . These scans were saved as MATLAB figures for visual reference...Locations from 3-D LiDAR Scans 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Graves, Mitchell Robert 5d. PROJECT NUMBER

  2. Individual Tree Segmentation from LiDAR Point Clouds for Urban Forest Inventory

    OpenAIRE

    Caiyun Zhang; Yuhong Zhou; Fang Qiu

    2015-01-01

    The objective of this study is to develop new algorithms for automated urban forest inventory at the individual tree level using LiDAR point cloud data. LiDAR data contain three-dimensional structure information that can be used to estimate tree height, base height, crown depth, and crown diameter. This allows precision urban forest inventory down to individual trees. Unlike most of the published algorithms that detect individual trees from a LiDAR-derived raster surface, we worked directly w...

  3. LiDAR-derived snowpack data sets from mixed conifer forests across the Western United States

    Science.gov (United States)

    Harpold, A. A.; Guo, Q.; Molotch, N.; Brooks, P. D.; Bales, R.; Fernandez-Diaz, J. C.; Musselman, K. N.; Swetnam, T. L.; Kirchner, P.; Meadows, M. W.; Flanagan, J.; Lucas, R.

    2014-03-01

    Airborne-based Light Detection and Ranging (LiDAR) offers the potential to measure snow depth and vegetation structure at high spatial resolution over large extents and thereby increase our ability to quantify snow water resources. Here we present airborne LiDAR data products at four Critical Zone Observatories (CZO) in the Western United States: Jemez River Basin, NM, Boulder Creek Watershed, CO, Kings River Experimental Watershed, CA, and Wolverton Basin, CA. We make publicly available snow depth data products (1 m2 resolution) derived from LiDAR with an estimated accuracy of <30 cm compared to limited in situ snow depth observations.

  4. 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

    Elevation data from airborne Light Detection and Ranging (LiDAR) campaigns are used in an attempt to evaluate the accuracy of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM) in Greenland. The LiDAR elevation data set is characterized...... 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...

  5. Frontiers in Using LiDAR to Analyze Urban Landscape Heterogeneity

    Science.gov (United States)

    Singh, Kunwar Krishna Veer

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

  6. 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...

  7. 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....

  8. 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...

  9. 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...

  10. 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...

  11. 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...

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

    National Research Council Canada - National Science Library

    Ariel L. Salas, Eric; M. Henebry, Geoffrey

    2016-01-01

    .... 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...

  13. 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...

  14. 2012 USACE Post Sandy Topographic LiDAR: Rhode Island and Massachusetts Coast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This topographic elevation point data derived from multiple return light detection and ranging (LiDAR) represents 354.272 square miles of coastline for Rhode Island...

  15. 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...

  16. 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)...

  17. 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.

  18. 2008 - 2009 Oregon Department of Geology and Mineral Industries (DOGAMI) South Coast LiDAR Project

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  19. 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....

  20. 2008 - 2009 Oregon Department of Geology and Mineral Industries (DOGAMI) South Coast LiDAR Project

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology and Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  1. 2008 NWFWMD (Northwest Florida Water Management District) Florida 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...

  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 ..... Fourthly, relief materials became a business for political elites to amass wealth. Arising from ... Unpublished PhD Thesis, Department of History,. University of Abuja ...

  3. 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....

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

    DEFF Research Database (Denmark)

    Kopecký, David; Bartos, Jan; Lukaszewski, Adam J

    2009-01-01

    Background Grasses are among the most important and widely cultivated plants on Earth. They provide high quality fodder for livestock, are used for turf and amenity purposes, and play a fundamental role in environment protection. Among cultivated grasses, species within the Festuca-Lolium complex...... predominate, especially in temperate regions. To facilitate high-throughput genome profiling and genetic mapping within the complex, we have developed a Diversity Arrays Technology (DArT) array for five grass species: F. pratensis, F. arundinacea, F. glaucescens, L. perenne and L. multiflorum. Results The DAr......T 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...

  5. 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.

  6. Iron deficiency in sickle cell anaemia patients in Dar es Salaam ...

    African Journals Online (AJOL)

    Iron deficiency in sickle cell anaemia patients in Dar es Salaam, Tanzania. ... Five milliliter of venous blood was taken from all children for serum Ferritin, serum ... of haemoglobin concentration did not significantly influence the body Iron status ...

  7. 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...

  8. 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...

  9. 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...

  10. 2009 National Renewable Energy Labratory/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...

  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. 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...

  13. 2012 USACE Post Hurricane Sandy Topographic LiDAR: Rhode Island and Massachusetts Coast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This topographic elevation point data derived from multiple return light detection and ranging (LiDAR) represents 354.272 square miles of coastline for Rhode Island...

  14. 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...

  15. 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...

  16. LiDAR DTM: artifacts, and correction for river altitudes

    Directory of Open Access Journals (Sweden)

    Jean-François Parrot

    2016-01-01

    Full Text Available Los datos LiDAR permiten generar Modelos Digitales de Elevación (MDE de alta resolución, sin embargo, algunos artefactos resultantes del método de interpolación utilizado afectan su exactitud y precisión. Esta observación concierne, entre otros, a los MDE generados por el Instituto Nacional de Estadística y Geografía (INEGI, especialmente los Modelos Digitales de Terreno (MDT, que se relacionan con la superficie terrestre. Estos artefactos corresponden a facetas triangulares en elevaciones, meandros, y superficies de los ríos. Los tratamientos desarrollados en esta investigación disminuyen y/o eliminan dichos artefactos mejorando los MDT. Cálculos basados en el Error Cuadrá- tico Medio de la Rugosidad y el Error Cuadrático Medio de la elevación muestran que el método presentado en este trabajo mejora la precisión de los productos digitales, lo que permite realizar simulaciones eficaces y mediciones precisas.

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Science.gov (United States)

    2014-03-01

    wetlands and uplands ( Hogg and Hol- land 2008) and better able to model relationships between vegetation and elevation (Moeslund et al. 2011) than DEMs...rugosa) (speckled alder) could not be distinguished from surrounding upland forest by using topographic LiDAR data alone ( Hogg and Holland 2008...gradual transition from upland to wetland ( Hogg and Holland 2008). Therefore, topographic patterns discerned using LiDAR data should be verified in the

  19. Knowledge and attitudes towards obesity among primary school children in Dar es Salaam, Tanzania

    OpenAIRE

    Njelekela, Marina A.; Alfa Muhihi; Mpembeni, Rose N. M.; Amani Anaeli; Omary Chillo; Sulende Kubhoja; Benjamin Lujani; Davis Ngarashi; Mwanamkuu Maghembe

    2015-01-01

    Background: Childhood obesity has increased over the past two decades. Child obesity is likely to persist through adulthood and increases the risk of non-communicable diseases (NCDs) later in life. This study assessed knowledge and attitudes towards obesity among primary school children in Dar es Salaam, Tanzania. Materials and Methods: A cross-sectional study was conducted in randomly selected primary schools in Dar es Salaam. A structured questionnaire was used to assess the knowledge and a...

  20. Joint hierarchical models for sparsely sampled high-dimensional LiDAR and forest variables

    OpenAIRE

    Finley, Andrew O.; Banerjee, Sudipto; Zhou, Yuzhen; Cook, Bruce D; Babcock, Chad

    2016-01-01

    Recent advancements in remote sensing technology, specifically Light Detection and Ranging (LiDAR) sensors, provide the data needed to quantify forest characteristics at a fine spatial resolution over large geographic domains. From an inferential standpoint, there is interest in prediction and interpolation of the often sparsely sampled and spatially misaligned LiDAR signals and forest variables. We propose a fully process-based Bayesian hierarchical model for above ground biomass (AGB) and L...

  1. 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.

  2. Contraceptive Method Choice Among Women Attending at Amtullabhai Family Planning Clinic in Dar es salaam

    OpenAIRE

    Mbando, Apaisaria Humphrey

    2011-01-01

    Contraceptive prevalence in Tanzania is low despite high knowledge of contraception. In order to understand the existing barriers, it is important to find out reasons affecting contraceptive method choices. The objective of this study was to assess contraceptive method choice among women attending at Amtullabhai family planning clinic in Dar es Salaam. A cross- sectional study was conducted between October and November, 2010 at Amtullabhai family planning clinic, Ilala District in Dar es Sala...

  3. 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.

  4. Airborne Dual-Wavelength LiDAR Data for Classifying Land Cover

    Directory of Open Access Journals (Sweden)

    Cheng-Kai Wang

    2014-01-01

    Full Text Available This study demonstrated the potential of using dual-wavelength airborne light detection and ranging (LiDAR data to classify land cover. Dual-wavelength LiDAR data were acquired from two airborne LiDAR systems that emitted pulses of light in near-infrared (NIR and middle-infrared (MIR lasers. The major features of the LiDAR data, such as surface height, echo width, and dual-wavelength amplitude, were used to represent the characteristics of land cover. Based on the major features of land cover, a support vector machine was used to classify six types of suburban land cover: road and gravel, bare soil, low vegetation, high vegetation, roofs, and water bodies. Results show that using dual-wavelength LiDAR-derived information (e.g., amplitudes at NIR and MIR wavelengths could compensate for the limitations of using single-wavelength LiDAR information (i.e., poor discrimination of low vegetation when classifying land cover.

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

    Science.gov (United States)

    Bolkas, Dimitrios; Fotopoulos, Georgia; Glennie, Craig

    2016-09-01

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

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

    Indian Academy of Sciences (India)

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

    2011-04-01

    With an objective to develop a genetic map in pigeon pea (Cajanus spp.), a total of 554 diversity arrays technology (DArT) markers showed polymorphism in a pigeon pea F2 mapping population of 72 progenies derived from an interspecific cross of ICP 28 (Cajanus cajan) and ICPW 94 (Cajanus scarabaeoides). Approximately 13% of markers did not conform to expected segregation ratio. The total number of DArT marker loci segregating in Mendelian manner was 405 with 73.1% ($P \\gt 0.001$) of DArT markers having unique segregation patterns. Two groups of genetic maps were generated using DArT markers. While the maternal genetic linkage map had 122 unique DArT maternal marker loci, the paternal genetic linkage map has a total of 172 unique DArT paternal marker loci. The length of these two maps covered 270.0 cM and 451.6 cM, respectively. These are the first genetic linkage maps developed for pigeon pea, and this is the first report of genetic mapping in any grain legume using diversity arrays technology.

  7. Area-Based Mapping of Defoliation of Scots Pine Stands Using Airborne Scanning LiDAR

    Directory of Open Access Journals (Sweden)

    Hannu Hyyppä

    2013-03-01

    Full Text Available The mapping of changes in the distribution of insect-caused forest damage remains an important forest monitoring application and challenge. Efficient and accurate methods are required for mapping and monitoring changes in insect defoliation to inform forest management and reporting activities. In this research, we develop and evaluate a LiDAR-driven (Light Detection And Ranging approach for mapping defoliation caused by the Common pine sawfly (Diprion pini L.. Our method requires plot-level training data and airborne scanning LiDAR data. The approach is predicated on a forest canopy mask created by detecting forest canopy cover using LiDAR. The LiDAR returns that are reflected from the canopy (that is, returns > half of maximum plot tree height are used in the prediction of the defoliation. Predictions of defoliation are made at plot-level, which enables a direct integration of the method to operational forest management planning while also providing additional value-added from inventory-focused LiDAR datasets. In addition to the method development, we evaluated the prediction accuracy and investigated the required pulse density for operational LiDAR-based mapping of defoliation. Our method proved to be suitable for the mapping of defoliated stands, resulting in an overall mapping accuracy of 84.3% and a Cohen’s kappa coefficient of 0.68.

  8. Classification of LiDAR Data with Point Based Classification Methods

    Science.gov (United States)

    Yastikli, N.; Cetin, Z.

    2016-06-01

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

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

    Institute of Scientific and Technical Information of China (English)

    KWAK; Doo-Ahn; LEE; Woo-Kyun; KAFATOS; Menas; SON; Yowhan; CHO; Hyun-Kook; LEE; Seung-Ho

    2010-01-01

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

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

    Science.gov (United States)

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

    2010-07-01

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

  11. 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.

  12. Registration of Aerial Image with Airborne LiDAR Data Based on Plücker Line

    OpenAIRE

    SHENG Qinghong; Chen, Shuwen; FEI Lijia; Liu, Jianfeng; Wang, Huinan

    2015-01-01

    Registration of aerial image with airborne LiDAR data is a key to feature extraction. A registration model based on Plücker line is proposed. The relative position and attitude relationship between the conjugate lines in LiDAR and image is determined based on Plücker linear equation, which describes line transformation in space, then coplanarity condition equation is established. Finally, coordinate transformation between image point and corresponding LiDAR point is achieved by the ...

  13. Comprehensive Utilization of Temporal and Spatial Domain Outlier Detection Methods for Mobile Terrestrial LiDAR Data

    OpenAIRE

    Baoxin Hu; Jian-guo Wang; Michael Leslar

    2011-01-01

    Terrestrial LiDAR provides many disciplines with an effective and efficient means of producing realistic three-dimensional models of real world objects. With the advent of mobile terrestrial LiDAR, this ability has been expanded to include the rapid collection of three-dimensional models of large urban scenes. For all its usefulness, it does have drawbacks. One of the major problems faced by the LiDAR industry today is the automatic removal of outlying data points from LiDAR point clouds. Thi...

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

    Science.gov (United States)

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

    2011-03-01

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

  15. Extraction of Mangrove Biophysical Parameters Using Airborne LiDAR

    Directory of Open Access Journals (Sweden)

    Poonsak Miphokasap

    2013-04-01

    Full Text Available Tree parameter determinations using airborne Light Detection and Ranging (LiDAR have been conducted in many forest types, including coniferous, boreal, and deciduous. However, there are only a few scientific articles discussing the application of LiDAR to mangrove biophysical parameter extraction at an individual tree level. The main objective of this study was to investigate the potential of using LiDAR data to estimate the biophysical parameters of mangrove trees at an individual tree scale. The Variable Window Filtering (VWF and Inverse Watershed Segmentation (IWS methods were investigated by comparing their performance in individual tree detection and in deriving tree position, crown diameter, and tree height using the LiDAR-derived Canopy Height Model (CHM. The results demonstrated that each method performed well in mangrove forests with a low percentage of crown overlap conditions. The VWF method yielded a slightly higher accuracy for mangrove parameter extractions from LiDAR data compared with the IWS method. This is because the VWF method uses an adaptive circular filtering window size based on an allometric relationship. As a result of the VWF method, the position measurements of individual tree indicated a mean distance error value of 1.10 m. The individual tree detection showed a kappa coefficient of agreement (K value of 0.78. The estimation of crown diameter produced a coefficient of determination (R2 value of 0.75, a Root Mean Square Error of the Estimate (RMSE value of 1.65 m, and a Relative Error (RE value of 19.7%. Tree height determination from LiDAR yielded an R2 value of 0.80, an RMSE value of 1.42 m, and an RE value of 19.2%. However, there are some limitations in the mangrove parameters derived from LiDAR. The results indicated that an increase in the percentage of crown overlap (COL results in an accuracy decrease of the mangrove parameters extracted from the LiDAR-derived CHM, particularly for crown measurements. In this

  16. In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR

    Directory of Open Access Journals (Sweden)

    Shangpeng Sun

    2017-04-01

    Full Text Available A LiDAR-based high-throughput phenotyping (HTP system was developed for cotton plant phenotyping in the field. The HTP system consists of a 2D LiDAR and an RTK-GPS mounted on a high clearance tractor. The LiDAR scanned three rows of cotton plots simultaneously from the top and the RTK-GPS was used to provide the spatial coordinates of the point cloud during data collection. Configuration parameters of the system were optimized to ensure the best data quality. A height profile for each plot was extracted from the dense three dimensional point clouds; then the maximum height and height distribution of each plot were derived. In lab tests, single plants were scanned by LiDAR using 0.5° angular resolution and results showed an R2 value of 1.00 (RMSE = 3.46 mm in comparison to manual measurements. In field tests using the same angular resolution; the LiDAR-based HTP system achieved average R2 values of 0.98 (RMSE = 65 mm for cotton plot height estimation; compared to manual measurements. This HTP system is particularly useful for large field application because it provides highly accurate measurements; and the efficiency is greatly improved compared to similar studies using the side view scan.

  17. Development of LiDAR measurements for the German offshore test site

    Science.gov (United States)

    Rettenmeier, A.; Kühn, M.; Wächter, M.; Rahm, S.; Mellinghoff, H.; Siegmeier, B.; Reeder, L.

    2008-05-01

    The paper introduces the content of the recently started joint research project 'Development of LiDAR measurements for the German Offshore Test Site' which has the objective to support other research projects at the German offshore test site 'alpha ventus'. The project has started before the erection of the offshore wind farm and one aim is to give recommendations concerning LiDAR technology useable for offshore measurement campaigns and data analysis. The work is organized in four work packages. The work package LiDAR technology deals with the specification, acquisition and calibration of a commercial LiDAR system for the measurement campaigns. Power curve measurements are dedicated to power curve assessment with ground-based LiDAR using standard statistical methods. Additionally, it deals with the development of new methods for the measurement of non-steady short-term power curves. Wind field research aims at the development of wake loading simulation methods of wind turbines and the exploration of loading control strategies and nacelle-based wind field measurement techniques. Finally, dissemination of results to the industry takes place in work package Technology transfer.

  18. 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.

  19. 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.

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

    Science.gov (United States)

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

    2010-12-01

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

  1. 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.

  2. Elemental Contents in Hair of Children from Two Regions in Dar Es Salaam

    Directory of Open Access Journals (Sweden)

    Najat K. Mohammed

    2012-01-01

    Full Text Available The work presented in this paper is part of the study which aims at determining the levels of elements in hair of children in Tanzania as a bioindicator of their nutrition and health. In this paper, the levels of trace elements in hair from children living in Dar es Salaam have been analysed. The analysis was carried out by long and short irradiation INAA at the reactor centre of the Institute of Nuclear Physics, Rez Czech Republic. 22 samples were collected from children living at Kiwalani about 12 km from Dar es Salaam city and 16 samples from children living at Mlimani, the main campus of University of Dar es Salaam. A total of 34 elements were found in the hair of the children. There were no big differences between the concentration levels of the essential elements in hair samples collected from the children which might indicate the same food consumption habits.

  3. 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

    High-accuracy wind data for coastal regions is needed today, e.g., for the assessment of wind resources. Synthetic Aperture Radar (SAR) is the only satellite borne sensor that has enough resolution to resolve wind speeds closer than 10 km to shore but the Geophysical Model Functions (GMF) used...... 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...

  4. 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

    -Thr-Arg-Pro-Gln-Pro-Phe-Asn-Phe-Gly-Leu-NH(2)) is the most effective in causing a second messenger cascade (measured as bioluminescence; threshold, 10(-9) M; EC(50), 10(-8) M), whereas the others are less effective and about equally potent (EC(50), 8 x 10(-8) M). Northern blots showed that the DAR-2 gene is expressed in embryos, larvae......, pupae, and adult flies. In adult flies, the receptor is more strongly expressed in the thorax/abdomen than in the head parts, suggesting that DAR-2 is a gut receptor. This is confirmed by Northern blots from 3rd instar larvae, showing that the DAR-2 gene is mainly expressed in the gut and only very...

  5. The IsoDAR High Intensity H$_2^+$ Transport and Injection Tests

    CERN Document Server

    Alonso, Jose; Calabretta, Luciano; Campo, Daniela; Celona, Luigi; Conrad, Janet M; Day, Alexandra; Castro, Giuseppe; Labrecque, Francis; Winklehner, Daniel

    2015-01-01

    This technical report reviews the tests performed at the Best Cyclotron Systems, Inc. facility in regards to developing a cost effective ion source, beam line transport system, and acceleration system capable of high H$_2^+$ current output for the IsoDAR (Isotope Decay At Rest) experiment. We begin by outlining the requirements for the IsoDAR experiment then provide overview of the Versatile Ion Source, Low Energy Beam Transport system, spiral inflector, and cyclotron. The experimental measurements are then discussed and the results are compared with a thorough set of simulation studies. Of particular importance we note that the Versatile Ion Source (VIS) proved to be a reliable ion source capable of generating a large amount of H$_2^+$ current. The results suggest that with further upgrades, the VIS could potentially be a suitable candidate for IsoDAR. The conclusion outlines the key results from our tests and introduces the forthcoming work this technical report has motivated.

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

    Directory of Open Access Journals (Sweden)

    J. Jubanski

    2012-08-01

    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 meter of 2–4 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 46%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong 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. LiDAR data and SAR imagery acquired by an unmanned helicopter for rapid landslide investigation

    Science.gov (United States)

    Kasai, M.; Tanaka, Y.; Yamazaki, T.

    2012-12-01

    When earthquakes or heavy rainfall hits a landslide prone area, initial actions require estimation of the size of damage to people and infrastructure. This includes identifying the number and size of newly collapsed or expanded landslides, and appraising subsequent risks from remobilization of landslides and debris materials. In inapproachable areas, the UAV (Unmanned Aerial Vehicles) is likely to be of greatest use. In addition, repeat monitoring of sites after the event is a way of utilizing UAVs, particularly in terms of cost and convenience. In this study, LiDAR (SkEyesBox MP-1) data and SAR (Nano SAR) imagery, acquired over 0.5 km2 landslide prone area, are presented to assess the practicability of using unmanned helicopters (in this case a 10 year old YAMAHA RMAX G1) in these situations. LiDAR data was taken in July 2012, when tree foliage covered the ground surface. However, imagery was of sufficient quality to identify and measure landslide features. Nevertheless, LiDAR data obtained by a manned helicopter in the same area in August 2008 was more detailed, reflecting the function of the LiDAR scanner. On the other hand, 2 m resolution Nano SAR imagery produced reasonable results to elucidate hillslope condition. A quick method for data processing without loss of image quality was also investigated. In conclusion, the LiDAR scanner and UAV employed here could be used to plan immediate remedial activity of the area, before LiDAR measurement with a manned helicopter can be organized. SAR imagery from UAV is also available for this initial activity, and can be further applied to long term monitoring.

  8. 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.

  9. Optimisation of LiDAR derived terrain models for river flow modelling

    Directory of Open Access Journals (Sweden)

    G. Mandlburger

    2008-12-01

    Full Text Available Airborne LiDAR (Light Detection And Ranging combines cost efficiency, high degree of automation, high point density of typically 1–10 points per m2 and height accuracy of better than ±15 cm. For all these reasons LiDAR is particularly suitable for deriving precise Digital Terrain Models (DTM as geometric basis for hydrodynamic-numerical (HN simulations. The application of LiDAR for river flow modelling requires a series of preprocessing steps. Terrain points have to be filtered and merged with river bed data, e.g. from echo sounding. Then, a smooth Digital Terrain Model of the Watercourse (DTM-W needs to be derived, preferably considering the random measurement error during surface interpolation. In a subsequent step, a hydraulic computation mesh has to be constructed. Hydraulic simulation software is often restricted to a limited number of nodes and elements, thus, data reduction and data conditioning of the high resolution LiDAR DTM-W becomes necessary. We will present a DTM thinning approach based on adaptive TIN refinement which allows a very effective compression of the point data (more than 95% in flood plains and up to 90% in steep areas while preserving the most relevant topographic features (height tolerance ±20 cm. Traditional hydraulic mesh generators focus primarily on physical aspects of the computation grid like aspect ratio, expansion ratio and angle criterion. They often neglect the detailed shape of the topography as provided by LiDAR data. In contrast, our approach considers both the high geometric resolution of the LiDAR data and additional mesh quality parameters. It will be shown that the modelling results (flood extents, flow velocities, etc. can vary remarkably by the availability of surface details. Thus, the inclusion of such geometric details in the hydraulic computation meshes will gain importance for river flow modelling in the future.

  10. The Introduction of a Domestic Airborne LiDAR System SW-LiDAR%国产SW-LiDAR系统的简介

    Institute of Scientific and Technical Information of China (English)

    李志杰; 施昆; 关艳玲; 蒋凤保

    2013-01-01

    This paper introduced the structure, characteristics of a domestic airborne LiDAR systems SW-LiDAR and USES. This paper also provided highlights of inertial navigation principle, the principle of differential GPS and conformation equation, which is integrate theory. The workflow was introduced. Finally, the development trend of the system were prospected.%本文介绍国产机载SW-LiDAR系统的构成、特点和用途。重点阐述了该系统的三个集成原理:惯性导航原理、差分GPS原理和构象方程。介绍了该系统的工作流程。最后展望了该系统的应用前景。

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

    Science.gov (United States)

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

    2015-09-01

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

  12. Direct injection into the IsoDAR Cyclotron using a RFQ

    Science.gov (United States)

    Axani, Spencer; IsoDAR Collaboration

    2015-04-01

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

  13. Diagnóstico Territorial Integral del municipio de Ciudad Darío

    OpenAIRE

    2010-01-01

    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 d...

  14. Modeling rating curves using remotely-sensed LiDAR data

    Science.gov (United States)

    Nathanson, M.; Lyon, S. W.; Kean, J. W.; Grabs, T. J.; Seibert, J.; Laudon, H.

    2010-12-01

    Discharge is important since it integrates water from across the landscape. In remote locations, however, it is often difficult to obtain accurate streamflow information because of the difficulty of obtaining the discharge measurements necessary to define stage-discharge relationships (rating curves). The aim of this study is to investigate the feasibility of defining rating curves indirectly using a fluid-mechanically based model constrained with topographic data from airborne LiDAR scanning. The study is carried out for a small 8-m wide channel in the boreal landscape of northern Sweden. Helicopter-mounted LiDAR data with an approximately 30-cm average point spacing was used to define the channel geometry above a low flow water surface along a 90-m long reach. The channel topography below the surface was estimated using the simple assumption of a flat bed. The roughness for the modeled reach was back-calculated from a single direct measurement of discharge. This topographic and roughness information was then used to calculate a rating curve using the method of Kean and Smith (JGR-Earth Surface, 2010). The rating curve from the LiDAR scan was compared with direct measurements of discharge, as well as with a calculated rating curve developed using more detailed topographic data from a ground survey. In general, there was good agreement between all three methods. The calculated rating curve based on the detailed ground survey was in the best agreement with the direct measurements. The LiDAR-based rating curve was in good agreement with the medium and high flow measurements, but deviated from the direct measurements at low flows. The discrepancy between the LiDAR-based rating curve and the low flow measurements is due to unresolved bed topography, which could not be detected by the scan because of the cover of water. This deficiency can be minimized by scanning during periods of extremely low flow. The results so far suggest that further studies using combined site

  15. Not seeing the forest for the points: Novel LiDAR metrics elucidate forest structure and increase LiDAR usability by managers

    OpenAIRE

    Kramer, Heather Anuhea

    2016-01-01

    Forest and fire ecology have long utilized remote sensing datasets to learn more about landscapes. Advances in gps spatial accuracy, GIS software capabilities, computing power, and remote sensing technology and software, as well as increases in the spatial and temporal resolution of remote sensing products, have made remote sensing a critical component of forest and fire ecology. Aerial light detection and ranging (LiDAR) is a fast-growing active remote-sensing technology that can be mined fo...

  16. Developments for the IsoDAR@KamLAND and DAE{\\delta}ALUS Decay-At-Rest Neutrino Experiments

    CERN Document Server

    ,

    2016-01-01

    Configurations of the IsoDAR and DAE{\\delta}ALUS decay-at-rest neutrino experiments are described. Injector and cyclotron developments aimed at substantial increases in beam current are discussed. The IsoDAR layout and target are described, and this experiment is compared to other programs searching for sterile neutrinos.

  17. 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...

  18. 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...

  19. 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...

  20. Carbazole-based copolymers via direct arylation polymerization (DArP) for Suzuki-convergent polymer solar cell performance

    DEFF Research Database (Denmark)

    Gobalasingham, Nemal S.; Ekiz, Seyma; Pankow, Robert M.

    2017-01-01

    Although direct arylation polymerization (DArP) has recently emerged as an alternative to traditional cross-coupling methods like Suzuki polymerization, the evaluation of DArP polymers in practical applications like polymer solar cells (PSCs) is limited. Because even the presence of minute quanti...

  1. 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...

  2. 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.

  3. 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

  4. The use of airborne LiDAR data for the analysis of debris flow events in Switzerland

    Directory of Open Access Journals (Sweden)

    C. Scheidl

    2008-10-01

    Full Text Available A methodology of magnitude estimates for debris flow events is described using airborne LiDAR data. Light Detection And Ranging (LiDAR is a widely used technology to generate digital elevation information. LiDAR data in alpine regions can be obtained by several commercial companies where the automated filtering process is proprietary and varies from companies to companies. This study describes the analysis of geomorphologic changes using digital terrain models derived from commercial LiDAR data. The estimation of the deposition volumes is based on two digital terrain models covering the same area but differing in their time of survey. In this study two surveyed deposition areas of debris flows, located in the canton of Berne, Switzerland, were chosen as test cases. We discuss different grid interpolating techniques, other preliminary work and the accuracy of the used LiDAR data and volume estimates.

  5. Biology and management of fish stocks in Bahir Dar Gulf, Lake Tana, Ethiopia.

    NARCIS (Netherlands)

    Wudneh, T.

    1998-01-01

    The biology of the fish stocks of the major species in the Bahir Dar Gulf of Lake Tana, the largest lake in Ethiopia, has been studied based on data collected during August 1990 to September 1993. The distribution, reproduction patterns, growth and mortality dynamics and gillnet selectivity of these

  6. 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...

  7. 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…

  8. 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.

  9. 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.

  10. 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...

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Salem Morsy

    2017-04-01

    Full Text Available 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.

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

    Science.gov (United States)

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

    2011-01-01

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

  14. 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...

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

    Science.gov (United States)

    Varga, Timothy A; Asner, Gregory P

    2008-04-01

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

  16. 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.

  17. 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…

  18. 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....

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

    Science.gov (United States)

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

    2015-12-01

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

  20. Dynamic displacement estimation by fusing LDV and LiDAR measurements via smoothing based Kalman filtering

    Science.gov (United States)

    Kim, Kiyoung; Sohn, Hoon

    2017-01-01

    This paper presents a smoothing based Kalman filter to estimate dynamic displacement in real-time by fusing the velocity measured from a laser Doppler vibrometer (LDV) and the displacement from a light detection and ranging (LiDAR). LiDAR can measure displacement based on the time-of-flight information or the phase-shift of the laser beam reflected off form a target surface, but it typically has a high noise level and a low sampling rate. On the other hand, LDV primarily measures out-of-plane velocity of a moving target, and displacement is estimated by numerical integration of the measured velocity. Here, the displacement estimated by LDV suffers from integration error although LDV can achieve a lower noise level and a much higher sampling rate than LiDAR. The proposed data fusion technique estimates high-precision and high-sampling rate displacement by taking advantage of both LiDAR and LDV measurements and overcomes their limitations by adopting a real-time smoothing based Kalman filter. To verify the performance of the proposed dynamic displacement estimation technique, a series of lab-scale tests are conducted under various loading conditions.

  1. 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 remot

  2. 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...

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

    Science.gov (United States)

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

    2016-12-31

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

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

    Science.gov (United States)

    Wang, Jun; Xu, Kevin Kai

    2016-08-31

    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.

  5. Errors in LiDAR-derived shrub height and crown area on sloped terrain

    Science.gov (United States)

    This study developed and tested four methodologies for determining shrub height measurements with LiDAR data in a semiarid shrub-steppe in southwestern Idaho, USA. Unique to this study was the focus of sagebrush height measurements on sloped terrain. The study also developed one of the first metho...

  6. 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...

  7. 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 s

  8. Skeleton-based botanic tree diameter estimation from dense LiDAR data

    NARCIS (Netherlands)

    Bucksch, A.; Lindenbergh, R.; Mementi, M.; Raman, M.Z.

    2009-01-01

    New airborne LiDAR (Light Detection and Ranging) measurement systems, like the FLI-MAP 400 System, make it possible to obtain high density data containing far more information about single objects, like trees, than traditional airborne laser systems. Therefore, it becomes feasible to analyze geometr

  9. Object-Based Classification of Abandoned Logging Roads under Heavy Canopy Using LiDAR

    Directory of Open Access Journals (Sweden)

    Jason Sherba

    2014-05-01

    Full Text Available LiDAR-derived slope models may be used to detect abandoned logging roads in steep forested terrain. An object-based classification approach of abandoned logging road detection was employed in this study. First, a slope model of the study site in Marin County, California was created from a LiDAR derived DEM. Multiresolution segmentation was applied to the slope model and road seed objects were iteratively grown into candidate objects. A road classification accuracy of 86% was achieved using this fully automated procedure and post processing increased this accuracy to 90%. In order to assess the sensitivity of the road classification to LiDAR ground point spacing, the LiDAR ground point cloud was repeatedly thinned by a fraction of 0.5 and the classification procedure was reapplied. The producer’s accuracy of the road classification declined from 79% with a ground point spacing of 0.91 to below 50% with a ground point spacing of 2, indicating the importance of high point density for accurate classification of abandoned logging roads.

  10. 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...

  11. 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...

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

    Science.gov (United States)

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

    2015-03-23

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

  13. 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...

  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. Making the African city : Dakar, Dar es Salaam, Kinshasa, 1920-1980

    NARCIS (Netherlands)

    Beeckmans, Luce Manu R.

    2013-01-01

    In her PhD thesis Making the African City, Luce Beeckmans analyses the African city from a comparative perspective. By means of three case studies, the historical development between 1920 and 1980 of three cities in sub-Saharan Africa, Dakar (Senegal), Dar es Salaam (Tanzania) and Kinshasa (Congo),

  16. Making the African city : Dakar, Dar es Salaam, Kinshasa, 1920-1980

    NARCIS (Netherlands)

    Beeckmans, Luce Manu R.

    2012-01-01

    In her PhD thesis Making the African City, Luce Beeckmans analyses the African city from a comparative perspective. By means of three case studies, the historical development between 1920 and 1980 of three cities in sub-Saharan Africa, Dakar (Senegal), Dar es Salaam (Tanzania) and Kinshasa (Congo),

  17. 2009 U.S. Geological Survey (USGS) Topographic LiDAR: Androscoggin County, Maine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — USGS Contract Number: G10PC00026 USGS Task Order: G10PD01737 LiDAR was collected at a 1.0 points per square meter (1.0m GSD) for the county of Androscoggin, Maine...

  18. 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.

  19. 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.

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

    Science.gov (United States)

    Mlozi, Malongo R. S.

    1995-01-01

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

  1. Engineering monitoring of rockfall hazards along transportation corridors: using mobile terrestrial LiDAR

    Directory of Open Access Journals (Sweden)

    M. Lato

    2009-06-01

    Full Text Available Geotechnical hazards along linear transportation corridors are challenging to identify and often require constant monitoring. Inspecting corridors using traditional, manual methods requires the engineer to be unnecessarily exposed to the hazard. It also requires closure of the corridor to ensure safety of the worker from passing vehicles. This paper identifies the use of mobile terrestrial LiDAR data as a compliment to traditional field methods. Mobile terrestrial LiDAR is an emerging remote data collection technique capable of generating accurate fully three-dimensional virtual models while driving at speeds up to 100 km/h. Data is collected from a truck that causes no delays to active traffic nor does it impede corridor use. These resultant georeferenced data can be used for geomechanical structural feature identification and kinematic analysis, rockfall path identification and differential monitoring of rock movement or failure over time. Comparisons between mobile terrestrial and static LiDAR data collection and analysis are presented. As well, detailed discussions on workflow procedures for possible implementation are discussed. Future use of mobile terrestrial LiDAR data for corridor analysis will focus on repeated surveys and developing dynamic four-dimensional models, higher resolution data collection. As well, computationally advanced, spatially accurate, geomechanically controlled three-dimensional rockfall simulations should be investigated.

  2. 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.

  3. Biology and management of fish stocks in Bahir Dar Gulf, Lake Tana, Ethiopia

    NARCIS (Netherlands)

    Wudneh, T.

    1998-01-01

    The biology of the fish stocks of the major species in the Bahir Dar Gulf of Lake Tana, the largest lake in Ethiopia, has been studied based on data collected during August 1990 to September 1993. The distribution, reproduction patterns, growth and mortality dynamics and gillnet selectivity

  4. 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

    2017-08-14

    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.

  5. 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…

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

    Science.gov (United States)

    2012-09-01

    probably be made to improve final results. 14. SUBJECT TERMS Fusion, Multi-Source, Hyperspectral , Multispectral, LiDAR, Urban Classification ...Landsat Thematic Mapper for 1986, 1991, 1998, and 2002. A hybrid supervised- unsupervised classification technique was developed that clustered the...The multispectral spectral resolution is not as high as that of a hyperspectral sensor. Using hyperspectral data, finer classifications could

  7. 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. ... MNL estimation suggest that distance, home ownership, household expenditure ... Key words: Solid waste, garbage, waste disposal, waste management, ...

  8. 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...

  9. Point Density Effects on Digital Elevation Models Generated from LiDAR Data

    Science.gov (United States)

    2009-06-01

    Weighted ( IDW ) and spline-based and geostatistic such as Kriging. Inverse Distance Weighted ( IDW ) assumes that each point has a local influence...the IDW method performs well if sampling data density is high, even for complex terrain (Liu, 2008). D. PREVIOUS DATA ANALYSIS RESULTS LiDAR data

  10. 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.…

  11. A DATA DRIVEN METHOD FOR BUILDING RECONSTRUCTION FROM LiDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    M. Sajadian

    2014-10-01

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

  12. LiDAR-based predictions of flow channels through riparian buffer zones

    Directory of Open Access Journals (Sweden)

    A.G. Solomons

    2015-10-01

    Full Text Available Riparian buffer zones (RBZs are critical for protecting stream water quality. High Resolution Light Detection and Ranging (LiDAR data provides a way to locate channels where water can flow through a RBZ and into a stream. The objectives of this study were to characterize flow channels through riparian buffer zones around Lake Issaqueena, SC, USA, using LiDAR topography models and to validate these predictions using field observations of channel presence, soil moisture content and soil temperature. A LiDAR derived digital elevation model (DEM was utilized to define flow channels and determine forty sample locations. Analysis indicated channel locations and the presence of large forested buffers generally 10 m or greater in the study area. High flow accumulation channels can be accurately predicted by LiDAR data, but lower flow channels were less accurately estimated. Surface soil temperature measurements were relatively uniform showing no difference between predicted channel and control locations. Presented methodologies can serve as a template for future efforts to quantify riparian buffers and their effects on protecting water quality.

  13. 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....

  14. 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.

  15. 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...

  16. 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...

  17. 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…

  18. Processing and accuracy of topobathymetric LiDAR data in land-water transition zones

    OpenAIRE

    M. S. Andersen; A. GERGELY; Al-Hamdani, Z.; Steinbacher, F.; Larsen, L. R.; V. B. Ernstsen

    2016-01-01

    The transition zone between land and water is difficult to map with conventional geophysical systems due to shallow water depth and often harsh environmental conditions. The emerging technology of airborne topobathymetric Light Detection And Ranging (LiDAR) is capable of providing both topographic and bathymetric elevation information, resulting in a seamless coverage of the land-water transition zone. However, there is ...

  19. 2011 U.S. Geological Survey 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. 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...

  1. LiDAR measurements of full scale wind turbine wake characteristics

    DEFF Research Database (Denmark)

    Hansen, Kurt Schaldemose; Larsen, Gunner Chr.; Mann, Jakob

    2009-01-01

    Full scale wind speed measurements, recorded inside the wake of an operating 2MW/80m wind turbine,has been performed during the spring 2009, as part of the EU-TOPFARM project. Longitudinal wind speeds in wake cross sections are measured with a LiDAR system mounted in the rear of the nacelle. The ...

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

    Science.gov (United States)

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

    2016-05-01

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

  3. 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

  4. LiDAR measurements of full scale wind turbine wake characteristics

    DEFF Research Database (Denmark)

    Hansen, Kurt Schaldemose; Larsen, Gunner Chr.; Mann, Jakob;

    2009-01-01

    Full scale wind speed measurements, recorded inside the wake of an operating 2MW/80m wind turbine,has been performed during the spring 2009, as part of the EU-TOPFARM project. Longitudinal wind speeds in wake cross sections are measured with a LiDAR system mounted in the rear of the nacelle...

  5. 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...

  6. Distinguishing grass from ground using LiDAR: Techniques and applications

    Science.gov (United States)

    Pelletier, J. D.; Swetnam, T.; Papuga, S. A.; Nelson, K.; Brooks, P. D.; Harpold, A. A.; Chorover, J.

    2011-12-01

    Standard protocols exist for extracting bare-earth Digital Elevation Models (DEMs) from LiDAR point clouds that include trees and other large woody vegetation. Grasses and other herbaceous plants can also obscure the ground surface, yet methods for optimally distinguishing grass from ground to generate accurate LiDAR-based raster products for geomorphic and ecological applications are still under development. Developing such methods is important because LiDAR-based difference products (e.g. snow thickness) require accurate representations of the ground surface and because raster data for grass height and density have important applications in ecology. In this study, we developed and tested methods for constructing optimal bare-earth and grass height raster layers from LiDAR point clouds and compared the results to high-quality field-based measurements of grass height, density, and species type for nearly 1000 precisely geo-referenced locations collected during the acquisition of a >200 km^2 airborne LiDAR flight of the Valles Caldera National Preserve (New Mexico). In cases of partially bare ground (where the skewness of return heights above a plane fit to the lowest first returns is sufficiently large), a planar fit to the lowest first returns provides a good method of producing an accurate bare-earth DEM and the statistics of the first returns above that planar fit provide good estimates of the mean and variance of grass height. In areas of relatively thick grass cover, however, a fit to the lowest first returns yields a bare-earth DEM that may be a meter or more above the actual ground surface. Here we propose a method to solve this problem using field-measured correlations among the mean, variance, and skewness of grass heights. In this method, the variance and skewness of the differences between LiDAR first returns and a 10m^2 planar fit to the lowest first returns is used, together with field-based correlations of grass height statistics, to estimate the mean

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

    Science.gov (United States)

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

    2012-04-01

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

  8. 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.

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

    Science.gov (United States)

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

    2015-12-01

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

  10. Effects of LiDAR Derived DEM Resolution on Hydrographic Feature Extraction

    Science.gov (United States)

    Yang, P.; Ames, D. P.; Glenn, N. F.; Anderson, D.

    2010-12-01

    This paper examines the effect of LiDAR-derived digital elevation model (DEM) resolution on digitally extracted stream networks with respect to known stream channel locations. Two study sites, Reynolds Creek Experimental Watershed (RCEW) and Dry Creek Experimental Watershed (DCEW), which represent terrain characteristics for lower and intermediate elevation mountainous watersheds in the Intermountain West, were selected as study areas for this research. DEMs reflecting bare earth ground were created from the LiDAR observations at a series of raster cell sizes (from 1 m to 60 m) using spatial interpolation techniques. The effect of DEM resolution on resulting hydrographic feature (specifically stream channel) derivation was studied. Stream length, watershed area, and sinuosity were explored at each of the raster cell sizes. Also, variation from known channel location as estimated by root mean square error (RMSE) between surveyed channel location and extracted channel was computed for each of the DEMs and extracted stream networks. As expected, the results indicate that the DEM based hydrographic extraction process provides more detailed hydrographic features at a finer resolution. RMSE between the known channel location and modeled locations generally increased with larger cell size DEM with a greater effect in the larger RCEW. Sensitivity analyses on sinuosity demonstrated that the resulting shape of streams obtained from LiDAR data matched best with the reference data at an intermediate cell size instead of highest resolution, which is at a range of cell size from 5 to 10 m likely due to original point spacing, terrain characteristics, and LiDAR noise influence. More importantly, the absolute sinuosity deviation displayed a smallest value at the cell size of 10 m in both experimental watersheds, which suggests that optimal cell size for LiDAR-derived DEMs used for hydrographic feature extraction is 10 m.

  11. Object-Based Land Use Classification using Airborne LiDAR

    Science.gov (United States)

    Antonarakis, A. S.; Richards, K. S.; Brasington, J.

    2007-12-01

    Better information on roughness of various types of vegetation is needed for use in resistance equations and eventually in flood modelling. These types include woody riparian species with different structural characteristics. Remote Sensing information such as 3D point cloud data from LiDAR can be used as a tool for extracting simple roughness information relevant for the condition of below canopy flow, as well as roughness relevant for more complex tree morphology that affects the flow when it enters the canopy levels. A strategy for extracting roughness parameters from remote sensing techniques is to use a data fusion object classification model. This means that multiple datasets such as LiDAR, digital aerial photography, ground data and satellite data can be combined to produce roughness parameters estimated for different vegetative patches, which can subsequently be mapped spatially using a classification methodology. Airborne LiDAR is used in this study in order to classify forest and ground types quickly and efficiently without the need for manipulating multispectral image files. LiDAR has the advantage of being able to create elevation surfaces that are in 3D, while also having information on LiDAR intensity values, thus it is a spatial and spectral segmentation tool. This classification method also uses point distribution frequency criteria to differentiate between land cover types. The classification of three meanders of the Garonne and Allier rivers in France has demonstrated overall classification accuracies of 95%. Five types of riparian forest were classified with accuracies between 66-98%. These forest types included planted and natural forest stands of different ages. Classifications of short vegetation and bare earth also produced high accuracies averaging above 90%.

  12. 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.

  13. 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.

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

    Science.gov (United States)

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

    2015-12-01

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

  15. 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

  16. 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.

  17. 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.

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

    Science.gov (United States)

    Bailey, Brian N.; Mahaffee, Walter F.

    2017-06-01

    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.

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

    Science.gov (United States)

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

    2010-10-01

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

  20. Analysis of the Influence of Plot Size and LiDAR Density on Forest Structure Attribute Estimates

    OpenAIRE

    Luis A. Ruiz; Txomin Hermosilla; Francisco Mauro; Miguel Godino

    2014-01-01

    Licencia Creative Commons: Attribution 3.0 Unported (CC BY 3.0) This paper assesses the combined effect of field plot size and LiDAR density on the estimation of four forest structure attributes: volume, total biomass, basal area and canopy cover. A total of 21 different plot sizes were considered, obtained by decreasing the field measured plot radius value from 25 to 5 m with regular intervals of 1 m. LiDAR data densities were simulated by randomly removing LiDAR pulses until ...

  1. 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).

  2. 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). PMID:28091610

  3. IsoDAR@KamLAND: A Conceptual Design Report for the Technical Facility

    CERN Document Server

    Abs, M; Alonso, J R; Axani, S; Barletta, W A; Barlow, R; Bartoszek, L; Bungau, A; Calabretta, L; Calanna, A; Campo, D; Castro, G; Celona, L; Collin, G H; Conrad, J M; Gammino, S; Johnson, R; Karagiorgi, G; Kayser, S; Kleeven, W; Kolano, A; Labrecque, F; Loinaz, W A; Minervini, J; Moulai, M H; Okuno, H; Owen, H; Papavassiliou, V; Shaevitz, M H; Shimizu, I; Shokair, T M; Sorensen, K F; Spitz, J; Toups, M; Vagins, M; Van Bibber, K; Wascko, M O; Winklehner, D; Winslow, L A; Yang, J J

    2015-01-01

    This conceptual design report describes the technical facility for the IsoDAR electron-antineutrino source at KamLAND. The IsoDAR source will allow an impressive program of neutrino oscillation and electroweak physics to be performed at KamLAND. This report provides information on the physics case, the conceptual design for the subsystems, alternative designs considered, specifics of installation at KamLAND, and identified needs for future development. We discuss the risks we have identified and our approach to mitigating those risks with this design. A substantial portion of the conceptual design is based on three years of experimental efforts and on industry experience. This report also includes information on the conventional facilities.

  4. De Quevedo a Darío. Resonancias líricas y actitud vital

    OpenAIRE

    Acereda, A. (Alberto)

    2001-01-01

    Este artículo compara las conexiones poéticas y las actitudes vitales de don Francisco de Quevedo y Rubén Darío. Una lectura atenta de la poesía de Quevedo, más particularmente de los poemas dedicados a «Lisi», presenta una preocupación erótica espiritual y física que se acerca a la poesía dariana. Las menciones de Darío sobre Quevedo en su obra abren un filón para un estudio comparativo de ambos poetas. This article compares the poetic connections and the vital attitudes of Francisco de Quev...

  5. 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.

  6. Ugdymo vientisumas M. Montessori darželyje ir šeimoje

    OpenAIRE

    Červiakova, Vida

    2011-01-01

    Šiame darbe buvo siekiama ištirti ugdymo vientisumo M. Montessori darželyje ir šeimoje ypatumus teoriniu bei praktiniu aspektais. Siekiant šio tikslo pirmiausia atskleista M. Montessori pedagoginės sistemos samprata, apibrėžiamos ugdymo metodų vientisumo apraiškos šeimoje ir darželyje, išskiriamos ugdymo vientisumo įgyvendinimo problemos. Analizuojant, kaip pedagogai ir tėvai suvokia M. Montessori sistemą, koks pedagogų ir tėvų požiūris į vaiką, taip pat lyginant vaiko aplinką, vaiko veiklos ...

  7. LIDAR Products, LiDAR, Published in 2006, 1:1200 (1in=100ft) scale, Dodge County, Wisconsin.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This LIDAR Products dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from LIDAR information as of 2006. It is described as 'LiDAR'. Data...

  8. 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...

  9. 2006 US Army Corps of Engineers(USACE) National Coastal Mapping Program, Great Lakes Topo/Bathy LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Army Corps of Engineers collects and maintains LiDAR data including orthophotos in coastal areas of the United States and its territories. The Corps...

  10. 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...

  11. 2005 US Army Corps of Engineers (USACE) Post-Hurricane Katrina LiDAR: Mississippi and Western Alabama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data was acquired for the U.S. Army Corps of Engineers (USACE), Mobile District in September-October 2005 along the coastline of Hancock, Harrison, Jackson...

  12. 2005 US Army Corps of Engineers (USACE) Post-Hurricane Katrina LiDAR: Mississippi and Western Alabama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data was acquired for the U.S. Army Corps of Engineers (USACE), Mobile District in September-October 2005 along the coastline of Hancock, Harrison, Jackson...

  13. LiDAR Data Collection for the James River Watershed and Adjacent Areas in South Dakota and North Dakota

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The collection of LiDAR data for the James River basin began in 2010. The detailed surface elevation data will be used for conservation planning, design, research,...

  14. Saltwater intrusion in the quaternary aquifer of the Dar es Salaam region, Tanzania

    OpenAIRE

    Mtoni, Y.; Walraevens, K.

    2010-01-01

    Groundwater is a last-resort source of domestic water supply in Dar es Salaam City because of the scarcity of surface water sources. The Tanzania Government, Non Government Organizations (NGOs), Community Based Organizations (CBOs) and international aid organizations have promoted the drilling of boreholes. From 1997 until the present, boreholes drilling has increased tremendously and the trend is expected to increase even more in the future. Initial assessment of the current state of water q...

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

    Science.gov (United States)

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

    2016-08-01

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

  16. SUBTROPICAL FOREST BIOMASS ESTIMATION USING AIRBORNE LiDAR AND HYPERSPECTRAL DATA

    OpenAIRE

    Pang, Yong; Li, Zengyuan

    2016-01-01

    Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF’s (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province...

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

    Science.gov (United States)

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

    2015-12-01

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

  18. Estimating Tree Frontal Area in Urban Areas Using Terrestrial LiDAR Data

    Directory of Open Access Journals (Sweden)

    Yitong Jiang

    2016-05-01

    Full Text Available Surface roughness parameters, such as roughness length and displacement height, impact the estimation of surface moisture, and the frontal areas of buildings and trees are two components that contribute to surface roughness in urban areas. Research on tree frontal area has not been conducted in urban areas before, and we hope to fill that gap in the literature with this study by using Terrestrial Light Detection and Ranging (LiDAR data to estimate tree frontal areas in Warren Township, Indianapolis, IN, USA. We first estimated the frontal areas of individual trees based on their morphology, then calibrated a regression model to estimate the tree frontal area in 30 m pixels using parameters derived from LiDAR data and tree inventory data. The parameters included tree crown base area, height, width, conditions, defects, maintenances, genera, and land use. The validation shows that R2 yielded values ranging from 0.84 to 0.88, and RMSEs varied with tree category. The tree categories were identified based on the height and broadness of the canopy, which indicated the degree of resistance to air flow. This type of model can be used to empirically determine local roughness values at the tree-level for any city with a complete tree inventory. With the strong correlation between trees’ frontal area and crown base area, this model may also be used to determine local roughness value at 30 m resolution with NLCD (National Land Cover Database tree canopy cover data as a component. A proper tree categorization according to the vertical air resistance, e.g., height and canopy density, was effective to reduce the RMSE in tree frontal area estimation. Geometric parameters, such as height, crown base height, and crown base area extracted from Airborne LiDAR, which demand less storage and computation capacity, may also be sufficient for tree frontal area estimation in the areas where Terrestrial LiDAR is not available.

  19. 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.

  20. Step by step error assessment in braided river sediment budget using airborne LiDAR data

    Science.gov (United States)

    Lallias-Tacon, S.; Liébault, F.; Piégay, H.

    2014-06-01

    Sequential airborne LiDAR surveys were used to reconstruct the sediment budget of a 7-km-long braided river channel in southeastern France following a 14-year return period flood and to improve its accuracy step by step. Data processing involved (i) surface matching of the sequential point clouds, (ii) spatially distributed propagation of uncertainty based on surface conditions of the channel, and (iii) water depth subtraction from the digital elevation models based on water depths measured in the field. The respective influence of each processing step on sediment budget computation was systematically documented. This showed that surface matching and water depth subtraction both have a considerable effect on the net sediment budget. Although DEM of difference thresholding based on uncertainty analysis on absolute elevation values had a smaller effect on the sediment budget, this step is crucial for the production of a comprehensive map of channel deformations. A large independent data set of RTK-GPS checkpoints was used to control the quality of the LiDAR altimetry. The results showed that high density (7-9 points/m2) airborne LiDAR surveys can provide a very high level of detection of elevation changes on the exposed surfaces of the channel, with a 95% confidence interval level of detection between 19 and 30 cm. Change detection from LiDAR data revealed that 54% of the pre-flood active channel was reworked by the flood. The braided channel pattern was highly disturbed by the flood owing to the occurrence of several channel avulsions.

  1. 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.

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

    Science.gov (United States)

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

    2013-01-01

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

  3. Rafael Núñez visto por Rubén Darío

    Directory of Open Access Journals (Sweden)

    Alberto Miramón

    1966-12-01

    Full Text Available Entre los grandes timbres que nadie escatima al contradictorio filósofo del Cabrero, está el haber comprendido y ayudado a los maestros del modernismo de América en sus comienzos - José Asunción Silva y Rubén Darío-. Ambos lo conocieron y trataron en su retiro de Cartagena de Indias; ambos escribieron sus impresiones sobre este trato directo y personal.

  4. 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...

  5. Accuracy Management of LiDAR Data Using GPS Ground Control Points

    OpenAIRE

    BAŞ, Nuray; ÇELİK, Hakan; COŞKUN, H. Gonca

    2016-01-01

    Nowadays, both faster and more accurate data acquisition studies are gradually gaining speed, different of traditional land surveying technics in order to obtain land data having high accuration and geometric resolution on mapping. In this study, it is aimed that, to test with RTK/GPS (Real Time Kinematic-Global Positioning System) data of LiDAR (Light Detection and Ranging) Technology, as Remote Sensing Technic, making detection at 1.064nm near infrared region of electromagnetic spectrum in ...

  6. 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.

  7. 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.

  8. La alternancia dar/hacer en construcciones con verbo de apoyo y nombre de comunicación

    Directory of Open Access Journals (Sweden)

    Begoña Sanromán Vilas

    2014-11-01

    Full Text Available En este artículo defendemos que la selección de un verbo de apoyo por parte del nombre que lo acompaña, dentro del contexto de una construcción con verbo de apoyo, se basa en criterios semánticos. En concreto, el objetivo del estudio será el de descubrir qué componente(s del significado del nombre determina(n la selección de dar y cuál(es, la de hacer, dos de los verbos de apoyo más frecuentes en español. Para llevar a cabo esta tarea, analizamos nombres pertenecientes al campo semántico de la comunicación verbal que pueden coocurrir con ambos verbos, dar y hacer (dar/hacer una sugerencia, y los contrastamos con otros dos grupos de nombres de comunicación: 1 los que se combinan con dar, pero rechazan *hacer (dar/*hacer una respuesta y 2 los coocurren con hacer, pero no con *dar (*dar/hacer una pregunta. En la comparación de los grupos trataremos de probar dos hipótesis: una que opera a nivel paradigmático, describiendo los vínculos semánticos entre los verbos de apoyo y los correspondientes verbos plenos y otra, a nivel sintagmático, analizando qué otros verbos, aparte de dar y/o hacer, constituyen la coocurrencia léxica restringida de los nombres de comunicación objeto de estudio.

  9. 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.

  10. 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.

  11. Petrography and geochemistry of Paleocene-Eocene limestones in the Ching-dar syncline, eastern Iran

    Institute of Scientific and Technical Information of China (English)

    S. Halimeh Hashemi Azizi; Gholamreza Mirab Shabestari; Ahmadreza Khazaei

    2014-01-01

    The Ching-dar syncline is located to the west of the city of Birjand, in the east of Iran. The ca. 500 m thick studied section at the eastern flank of the syncline contains a sequence of almost continuous shallow-marine limestones that exhibit no major sedimentary breaks or evidence for volcanic activity. Skeletal grains consist of large benthic foraminifera and green algae whereas non-skeletal grains are mostly peloids and intraclasts. They were deposited on a shallow-marine carbonate ramp. The limestones have undergone extensive diagenetic processes with varying intensities, the most important of which are micritization, cementation, compaction (chemical and mechanical), internal filling and stylolitization. Chemical analysis of the limestone samples revealed high calcium and low magnesium content. Major and minor element values were used to determine the original carbonate mineralogy of these lime-stones. Petrographic evidence and elemental values indicate that calcite was the original carbonate mineral in the limestones of the Ching-dar syncline. The elemental composition of the Ching-dar car-bonates also demonstrates that they have stabilized in a meteoric phreatic environment. Variation of Sr/Ca vs. Mn values suggests that diagenetic alteration occurred in an open geochemical system.

  12. 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.

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

    Science.gov (United States)

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

    2016-06-01

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

  14. A Global Corrected SRTM DEM Product Over Vegetated Areas Using LiDAR Data

    Science.gov (United States)

    Zhao, X.; Guo, Q.; Su, Y.; Hu, T.

    2016-12-01

    The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is one of the most complete and frequently used global-scale DEM products in various applications. However, previous studies have shown that the SRTM DEM is systematically higher than the actual land surface in vegetated mountain areas. The objective of this study is to propose a procedure to calibrate the SRTM DEM over global vegetated mountain areas. To address this, we firstly collected airborne LiDAR data over 200,000 km2 globally used as ground truth data to analyze the uncertainty of the SRTM DEM. The Geoscience Laser Altimeter System (GLAS)/ICESat (Ice, Cloud, and land Elevation Satellite) data were used as complementary data in areas lack of airborne LiDAR data. Secondly, we modelled the SRTM DEM error for each vegetation type using regression methods. Tree height, canopy cover, and terrain slope were used as dependent variables to model the SRTM DEM error. Finally, these regression models were used to estimate the SRTM DEM error in vegetated mountain areas without LiDAR data coverage, and therefore correct the SRTM DEM. Our results show that the new corrected SRTM DEM can significantly reduce the systematic bias of the SRTM DEM in vegetated mountain areas.

  15. Registration of Urban Aerial Image and LiDAR Based on Line Vectors

    Directory of Open Access Journals (Sweden)

    Qinghong Sheng

    2017-09-01

    Full Text Available In a traditional registration of a single aerial image with airborne light detection and ranging (LiDAR data using linear features that regard line direction as a control or linear features as constraints in the solution, lacking the constraint of linear position leads to the error propagation of the adjustment model. To solve this problem, this paper presents a line vector-based registration mode (LVR in which image rays and LiDAR lines are expressed by a line vector that integrates the line direction and the line position. A registration equation of line vector is set up by coplanar imaging rays and corresponding control lines. Three types of datasets consisting of synthetic, theInternational Society for Photogrammetry and Remote Sensing (ISPRS test project, and real aerial data are used. A group of progressive experiments is undertaken to evaluate the robustness of the LVR. Experimental results demonstrate that the integrated line direction and the line position contributes a great deal to the theoretical and real accuracies of the unknowns, as well as the stability of the adjustment model. This paper provides a new suggestion that, for a single image and LiDAR data, registration in urban areas can be accomplished by accommodating rich line features.

  16. 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.

  17. 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.

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

    Science.gov (United States)

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

    2012-11-05

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

  19. Extracting cross sections and water levels of vegetated ditches from LiDAR point clouds

    Science.gov (United States)

    Roelens, Jennifer; Dondeyne, Stefaan; Van Orshoven, Jos; Diels, Jan

    2016-12-01

    The hydrologic response of a catchment is sensitive to the morphology of the drainage network. Dimensions of bigger channels are usually well known, however, geometrical data for man-made ditches is often missing as there are many and small. Aerial LiDAR data offers the possibility to extract these small geometrical features. Analysing the three-dimensional point clouds directly will maintain the highest degree of information. A longitudinal and cross-sectional buffer were used to extract the cross-sectional profile points from the LiDAR point cloud. The profile was represented by spline functions fitted through the minimum envelop of the extracted points. The cross-sectional ditch profiles were classified for the presence of water and vegetation based on the normalized difference water index and the spatial characteristics of the points along the profile. The normalized difference water index was created using the RGB and intensity data coupled to the LiDAR points. The mean vertical deviation of 0.14 m found between the extracted and reference cross sections could mainly be attributed to the occurrence of water and partly to vegetation on the banks. In contrast to the cross-sectional area, the extracted width was not influenced by the environment (coefficient of determination R2 = 0.87). Water and vegetation influenced the extracted ditch characteristics, but the proposed method is still robust and therefore facilitates input data acquisition and improves accuracy of spatially explicit hydrological models.

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

    Science.gov (United States)

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

    2015-12-01

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

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

    Science.gov (United States)

    Ndetto, Emmanuel L.; Matzarakis, Andreas

    2017-01-01

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

  2. A signal denoising method for full-waveform LiDAR data

    Science.gov (United States)

    Azadbakht, M.; Fraser, C. S.; Zhang, C.; Leach, J.

    2013-10-01

    The lack of noise reduction methods resistant to waveform distortion can hamper correct and accurate decomposition in the processing of full-waveform LiDAR data. This paper evaluates a time-domain method for smoothing and reducing the noise level in such data. The Savitzky-Golay (S-G) approach approximates and smooths data by taking advantage of fitting a polynomial of degree d, using local least-squares. As a consequence of the integration of this method with the Singular Value Decomposition (SVD) approach, and applying this filter on the singular vectors of the SVD, satisfactory denoising results can be obtained. The results of this SVD-based S-G approach have been evaluated using two different LiDAR datasets and also compared with those of other popular methods in terms of the degree of preservation of the moments of the signal and closeness to the noisy signal. The results indicate that the SVD-based S-G approach has superior performance in denoising full-waveform LiDAR data.

  3. 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.

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

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    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.

  5. [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.

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

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    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

  7. 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

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

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    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

  9. Surface Water Detection Using Fused Synthetic Aperture Radar, Airborne LiDAR and Optical Imagery

    Science.gov (United States)

    Braun, A.; Irwin, K.; Beaulne, D.; Fotopoulos, G.; Lougheed, S. C.

    2016-12-01

    Each remote sensing technique has its unique set of strengths and weaknesses, but by combining techniques the classification accuracy can be increased. The goal of this project is to underline the strengths and weaknesses of Synthetic Aperture Radar (SAR), LiDAR and optical imagery data and highlight the opportunities where integration of the three data types can increase the accuracy of identifying water in a principally natural landscape. The study area is located at the Queen's University Biological Station, Ontario, Canada. TerraSAR-X (TSX) data was acquired between April and July 2016, consisting of four single polarization (HH) staring spotlight mode backscatter intensity images. Grey-level thresholding is used to extract surface water bodies, before identifying and masking zones of radar shadow and layover by using LiDAR elevation models to estimate the canopy height and applying simple geometry algorithms. The airborne LiDAR survey was conducted in June 2014, resulting in a discrete return dataset with a density of 1 point/m2. Radiometric calibration to correct for range and incidence angle is applied, before classifying the points as water or land based on corrected intensity, elevation, roughness, and intensity density. Panchromatic and multispectral (4-band) imagery from Quickbird was collected in September 2005 at spatial resolutions of 0.6m and 2.5m respectively. Pixel-based classification is applied to identify and distinguish water bodies from land. A classification system which inputs SAR-, LiDAR- and optically-derived water presence models in raster formats is developed to exploit the strengths and weaknesses of each technique. The total percentage of water detected in the sample area for SAR backscatter, LiDAR intensity, and optical imagery was 27%, 19% and 18% respectively. The output matrix of the classification system indicates that in over 72% of the study area all three methods agree on the classification. Analysis was specifically targeted

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

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    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

  11. 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

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

    Science.gov (United States)

    Franceschi, Silvia; Antonello, Andrea; Tonon, Giustino

    2015-04-01

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

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

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    Sandip Pal

    2014-09-01

    Full Text Available 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 detector through the field stop in the receiver optics. Thus, the LiDAR signal below the height of full overlap remains erroneous. In effect, it is not possible to derive the atmospheric boundary layer (ABL top (zi below the height of full overlap using lidar measurements alone. This problem makes determination of the nocturnal zi almost impossible, as the nocturnal zi is often lower than the minimum possible retrieved height due to incomplete overlap of lidar. Detailed studies of the nocturnal boundary layer or of variability of low zi would require changes in the LiDAR configuration such that a complete transceiver overlap could be achieved at a much lower height. Otherwise, improvements in the system configuration or deployment (e.g., scanning LiDAR are needed. However, these improvements are challenging due to the instrument configuration and the need for Raman channel signal, eye-safe laser transmitter for scanning deployment, etc. This paper presents a brief review of some of the challenges and opportunities in overcoming the partial overlap of the LiDAR transceiver to determine zi below the height of full-overlap using complementary approaches to derive low zi. A comprehensive discussion focusing on four different techniques is presented. These are based on the combined (1 ceilometer and LiDAR; (2 tower-based trace gas (e.g., CO2 concentration profiles and LiDAR measurements; (3 222Rn budget approach and LiDAR-derived results; and (4 encroachment model

  14. 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.

  15. Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon

    Science.gov (United States)

    Burns, W.J.; Coe, J.A.; Kaya, B.S.; Ma, L.

    2010-01-01

    We examined elevation changes detected from two successive sets of Light Detection and Ranging (LiDAR) data in the northern Coast Range of Oregon. The first set of LiDAR data was acquired during leafon conditions and the second set during leaf-off conditions. We were able to successfully identify and map active landslides using a differential digital elevation model (DEM) created from the two LiDAR data sets, but this required the use of thresholds (0.50 and 0.75 m) to remove noise from the differential elevation data, visual pattern recognition of landslideinduced elevation changes, and supplemental QuickBird satellite imagery. After mapping, we field-verified 88 percent of the landslides that we had mapped with high confidence, but we could not detect active landslides with elevation changes of less than 0.50 m. Volumetric calculations showed that a total of about 18,100 m3 of material was missing from landslide areas, probably as a result of systematic negative elevation errors in the differential DEM and as a result of removal of material by erosion and transport. We also examined the accuracies of 285 leaf-off LiDAR elevations at four landslide sites using Global Positioning System and total station surveys. A comparison of LiDAR and survey data indicated an overall root mean square error of 0.50 m, a maximum error of 2.21 m, and a systematic error of 0.09 m. LiDAR ground-point densities were lowest in areas with young conifer forests and deciduous vegetation, which resulted in extensive interpolations of elevations in the leaf-on, bare-earth DEM. For optimal use of multi-temporal LiDAR data in forested areas, we recommend that all data sets be flown during leaf-off seasons.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    OpenAIRE

    Huang, Huabing; Gong, Peng; CHENG, XIAO; Clinton, Nick; Li, Zengyuan

    2009-01-01

    Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to ...

  18. 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

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

    Science.gov (United States)

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

    2015-12-01

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

  20. 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.

  1. 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.

  2. Extracting More Data from LiDAR in Forested Areas by Analyzing Waveform Shape

    Directory of Open Access Journals (Sweden)

    Peter Beets

    2012-03-01

    Full Text Available Light Detection And Ranging (LiDAR in forested areas is used for constructing Digital Terrain Models (DTMs, estimating biomass carbon and timber volume and estimating foliage distribution as an indicator of tree growth and health. All of these purposes are hindered by the inability to distinguish the source of returns as foliage, stems, understorey and the ground except by their relative positions. The ability to separate these returns would improve all analyses significantly. Furthermore, waveform metrics providing information on foliage density could improve forest health and growth estimates. In this study, the potential to use waveform LiDAR was investigated. Aerial waveform LiDAR data were acquired for a New Zealand radiata pine plantation forest, and Leaf Area Density (LAD was measured in the field. Waveform peaks with a good signal-to-noise ratio were analyzed and each described with a Gaussian peak height, half-height width, and an exponential decay constant. All parameters varied substantially across all surface types, ruling out the potential to determine source characteristics for individual returns, particularly those with a lower signal-to-noise ratio. However, pulses on the ground on average had a greater intensity, decay constant and a narrower peak than returns from coniferous foliage. When spatially averaged, canopy foliage density (measured as LAD varied significantly, and was found to be most highly correlated with the volume-average exponential decay rate. A simple model based on the Beer-Lambert law is proposed to explain this relationship, and proposes waveform decay rates as a new metric that is less affected by shadowing than intensity-based metrics. This correlation began to fail when peaks with poorer curve fits were included.

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

    Science.gov (United States)

    Vlaminck, Michiel; Luong, Hiep; Goeman, Werner; Philips, Wilfried

    2016-11-16

    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.

  4. 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.

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

    Science.gov (United States)

    Luciani, Giulia; Sappa, Giuseppe; Cella, Antonella

    2016-04-01

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

  6. Object-Based Tree Species Classification in Urban Ecosystems Using LiDAR and Hyperspectral Data

    Directory of Open Access Journals (Sweden)

    Zhongya Zhang

    2016-06-01

    Full Text Available In precision forestry, tree species identification is key to evaluating the role of forest ecosystems in the provision of ecosystem services, such as carbon sequestration and assessing their effects on climate regulation and climate change. In this study, we investigated the effectiveness of tree species classification of urban forests using aerial-based HyMap hyperspectral imagery and light detection and ranging (LiDAR data. First, we conducted an object-based image analysis (OBIA to segment individual tree crowns present in LiDAR-derived Canopy Height Models (CHMs. Then, hyperspectral values for individual trees were extracted from HyMap data for band reduction through Minimum Noise Fraction (MNF transformation which allowed us to reduce the data to 20 significant bands out of 118 bands acquired. Finally, we compared several different classifications using Random Forest (RF and Multi Class Classifier (MCC methods. Seven tree species were classified using all 118 bands which resulted in 46.3% overall classification accuracy for RF versus 79.6% for MCC. Using only the 20 optimal bands extracted through MNF, both RF and MCC achieved an increase in overall accuracy to 87.0% and 88.9%, respectively. Thus, the MNF band selection process is a preferable approach for tree species classification when using hyperspectral data. Further, our work also suggests that RF is heavily disadvantaged by the high-dimensionality and noise present in hyperspectral data, while MCC is more robust when handling high-dimensional datasets with small sample sizes. Our overall results indicated that individual tree species identification in urban forests can be accomplished with the fusion of object-based LiDAR segmentation of crowns and hyperspectral characterization.

  7. 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.

  8. 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.

  9. UAV-LiDAR accuracy and comparison to Structure from Motion photogrammetry

    Science.gov (United States)

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

    2016-12-01

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

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

    Science.gov (United States)

    Beuth, Thorsten; Fox, Maik; Stork, Wilhelm

    2015-06-01

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

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

    Science.gov (United States)

    Sookhan, Shane; Eyles, Nick; Putkinen, Niko

    2016-06-01

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

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

    Science.gov (United States)

    Giannaka, Olga; Dimopoulou, Efi; Georgopoulos, Andreas

    2014-08-01

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

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

    Science.gov (United States)

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

    2007-12-01

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

  14. Modeling of a sensitive time-of-flight flash LiDAR system

    Science.gov (United States)

    Fathipour, V.; Wheaton, S.; Johnson, W. E.; Mohseni, H.

    2016-09-01

    used for monitoring and profiling structures, range, velocity, vibration, and air turbulence. Remote sensing in the IR region has several advantages over the visible region, including higher transmitter energy while maintaining eye-safety requirements. Electron-injection detectors are a new class of detectors with high internal avalanche-free amplification together with an excess-noise-factor of unity. They have a cutoff wavelength of 1700 nm. Furthermore, they have an extremely low jitter. The detector operates in linear-mode and requires only bias voltage of a few volts. This together with the feedback stabilized gain mechanism, makes formation of large-format high pixel density electron-injection FPAs less challenging compared to other detector technologies such as avalanche photodetectors. These characteristics make electron-injection detectors an ideal choice for flash LiDAR application with mm scale resolution at longer ranges. Based on our experimentally measured device characteristics, a detailed theoretical LiDAR model was developed. In this model we compare the performance of the electron-injection detector with commercially available linear-mode InGaAs APD from (Hamamatsu G8931-20) as well as a p-i-n diode (Hamamatsu 11193 p-i-n). Flash LiDAR images obtained by our model, show the electron-injection detector array (of 100 x 100 element) achieves better resolution with higher signal-to-noise compared with both the InGaAs APD and the p-i-n array (of 100 x 100 element).

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

    Science.gov (United States)

    Levick, Shaun R; Hessenmöller, Dominik; Schulze, E-Detlef

    2016-12-01

    Monitoring and managing carbon stocks in forested ecosystems requires accurate and repeatable quantification of the spatial distribution of wood volume at landscape to regional scales. Grid-based forest inventory networks have provided valuable records of forest structure and dynamics at individual plot scales, but in isolation they may not represent the carbon dynamics of heterogeneous landscapes encompassing diverse land-management strategies and site conditions. Airborne LiDAR has greatly enhanced forest structural characterisation and, in conjunction with field-based inventories, it provides avenues for monitoring carbon over broader spatial scales. Here we aim to enhance the integration of airborne LiDAR surveying with field-based inventories by exploring the effect of inventory plot size and number on the relationship between field-estimated and LiDAR-predicted wood volume in deciduous broad-leafed forest in central Germany. Estimation of wood volume from airborne LiDAR was most robust (R(2) = 0.92, RMSE = 50.57 m(3) ha(-1) ~14.13 Mg C ha(-1)) when trained and tested with 1 ha experimental plot data (n = 50). Predictions based on a more extensive (n = 1100) plot network with considerably smaller (0.05 ha) plots were inferior (R(2) = 0.68, RMSE = 101.01 ~28.09 Mg C ha(-1)). Differences between the 1 and 0.05 ha volume models from LiDAR were negligible however at the scale of individual land-management units. Sample size permutation tests showed that increasing the number of inventory plots above 350 for the 0.05 ha plots returned no improvement in R(2) and RMSE variability of the LiDAR-predicted wood volume model. Our results from this study confirm the utility of LiDAR for estimating wood volume in deciduous broad-leafed forest, but highlight the challenges associated with field plot size and number in establishing robust relationships between airborne LiDAR and field derived wood volume. We are moving into a forest management era where

  16. 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....

  17. 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...

  18. 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

  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. Using High-Resolution Airborne LiDAR-Data for Landslide Mapping in the Eastern Alps

    Science.gov (United States)

    Kamp, N.

    2012-04-01

    Due to the increasing frequency of natural disasters like floods and landslides, the active remote sensing technique LiDAR (Light Detection and Ranging), has become a topic of great interest to the Federal State Government of Styria, Federal Republic of Austria. In a perennial project from 2008 to 2012 high-resolution 3D Airborne LiDAR Data of the Province of Styria, an area about 16.000km2 in south-eastern Austria were collected. These data were processed to create Digital Terrain Models (DTM) and Digital Surface Models (DSM) at 1m resolution with a vertical accuracy of 15 [cm] and a positional accuracy of 40 [cm]. High resolution DTMs can be used in different geo-related applications like geomorphological mapping or natural hazard mapping. DTMs show because of its high accuracy various natural and anthropogenic terrain features such as erosion scarps, alluvial fans, landslides, old creeks, topographic edges and karstforms, as well as walking paths and roads and in addition to that LiDAR data allows the detection and outlining of these different geomorphological and anthropogenic features with the help of ArcGIS 10 geoprocessing and analysing techniques, mathematical, statistical and image processing methods and the open source scripting language Python. As a result complex workflows and new geoprocessing tools can be implemented in an ArcGIS 10 workspace and are provided as easy to use toolbox contents. The landslide phenomena take in centre stage of the research work of the author. Thereby the main focus is targeted on sliding movements out of soils and bedrock. Factors like gravity take effect on slope stability directly and cause complex mass movements with a downslope directed, gliding movement of bed- and/or loose-rock as well as soil material. In this paper the author presents the result of her master thesis, an automatic ArcGIS 10 landslide mapping tool using high-resolution LiDAR data in the rock masses of the Eastern Alps (Province of Styria, Austria

  1. Tratando de dar respuesta a un problema de todos: el maltrato infantil

    OpenAIRE

    Prozorowska, Marta

    2015-01-01

    Con este trabajo de fin de grado (TFG) hemos pretendido acercarnos a una de las problemáticas más graves para los menores de nuestra sociedad y que preocupa a la comunidad educativa. Para ello, hemos elaborado una propuesta que pretende dar ciertas pautas a los maestros sobre cómo prevenir el maltrato infantil y el acoso escolar, ayudarles a detectar situaciones de abuso y aportarles una forma de actuación para intervenir en la búsqueda de una solución que ponga fin a este gran problema.

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

    Science.gov (United States)

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

    2013-10-01

    At the end of the first quarter of 2012, more than 600 Velodyne LiDAR systems had been sold worldwide for various robotic and high-accuracy survey applications. The ultra-compact Velodyne HDL-32E LiDAR has become a predominant sensor for many applications that require lower sensor size/weight and cost. For high accuracy applications, cost-effective calibration methods with minimal manual intervention are always desired by users. However, the calibrations are complicated by the Velodyne LiDAR's narrow vertical field of view and the very highly time-variant nature of its measurements. In the paper, the temporal stability of the HDL-32E is first analysed as the motivation for developing a new, automated calibration method. This is followed by a detailed description of the calibration method that is driven by a novel segmentation method for extracting vertical cylindrical features from the Velodyne point clouds. The proposed segmentation method utilizes the Velodyne point cloud's slice-like nature and first decomposes the point clouds into 2D layers. Then the layers are treated as 2D images and are processed with the Generalized Hough Transform which extracts the points distributed in circular patterns from the point cloud layers. Subsequently, the vertical cylindrical features can be readily extracted from the whole point clouds based on the previously extracted points. The points are passed to the calibration that estimates the cylinder parameters and the LiDAR's additional parameters simultaneously by constraining the segmented points to fit to the cylindrical geometric model in such a way the weighted sum of the adjustment residuals are minimized. The proposed calibration is highly automatic and this allows end users to obtain the time-variant additional parameters instantly and frequently whenever there are vertical cylindrical features presenting in scenes. The methods were verified with two different real datasets, and the results suggest that up to 78

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

    Science.gov (United States)

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

    2009-12-01

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

  4. Gold - A novel deconvolution algorithm with optimization for waveform LiDAR processing

    Science.gov (United States)

    Zhou, Tan; Popescu, Sorin C.; Krause, Keith; Sheridan, Ryan D.; Putman, Eric

    2017-07-01

    Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: (1) direct decomposition, (2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms - the Richardson-Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from the corresponding reference data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference (<1.22 m for DTMs, <0.77 m for CHMs) and root mean square error (RMSE) (<1.26 m for DTMs, <1.93 m for CHMs). More specifically, the Gold algorithm is superior to others with smaller root mean square error (RMSE) (<1.01 m), while the direct decomposition

  5. Topobathymetric LiDAR point cloud processing and landform classification in a tidal environment

    Science.gov (United States)

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

    2017-04-01

    Historically it has been difficult to create high resolution Digital Elevation Models (DEMs) in land-water transition zones due to shallow water depth and often challenging environmental conditions. This gap of information has been reflected as a "white ribbon" with no data in the land-water transition zone. In recent years, the technology of airborne topobathymetric Light Detection and Ranging (LiDAR) has proven capable of filling out the gap by simultaneously capturing topographic and bathymetric elevation information, using only a single green laser. We collected green LiDAR point cloud data in the Knudedyb tidal inlet system in the Danish Wadden Sea in spring 2014. Creating a DEM from a point cloud requires the general processing steps of data filtering, water surface detection and refraction correction. However, there is no transparent and reproducible method for processing green LiDAR data into a DEM, specifically regarding the procedure of water surface detection and modelling. We developed a step-by-step procedure for creating a DEM from raw green LiDAR point cloud data, including a procedure for making a Digital Water Surface Model (DWSM) (see Andersen et al., 2017). Two different classification analyses were applied to the high resolution DEM: A geomorphometric and a morphological classification, respectively. The classification methods were originally developed for a small test area; but in this work, we have used the classification methods to classify the complete Knudedyb tidal inlet system. References Andersen MS, Gergely Á, Al-Hamdani Z, Steinbacher F, Larsen LR, Ernstsen VB (2017). Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment. Hydrol. Earth Syst. Sci., 21: 43-63, doi:10.5194/hess-21-43-2017. Acknowledgements This work was funded by the Danish Council for Independent Research | Natural Sciences through the project "Process-based understanding and

  6. A signal denoising method for full-waveform LiDAR data

    OpenAIRE

    M.Azadbakht; Fraser, C.S.; Zhang, C.; Leach, J

    2013-01-01

    The lack of noise reduction methods resistant to waveform distortion can hamper correct and accurate decomposition in the processing of full-waveform LiDAR data. This paper evaluates a time-domain method for smoothing and reducing the noise level in such data. The Savitzky-Golay (S-G) approach approximates and smooths data by taking advantage of fitting a polynomial of degree d, using local least-squares. As a consequence of the integration of this method with the Singular Value Deco...

  7. 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

  8. a Darío Bentancurt, el de la novísima historia

    Directory of Open Access Journals (Sweden)

    Javier Guerreo Barrón

    2010-10-01

    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. 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

  10. Unveiling topographical changes using LiDAR mapping capability: case study of Belaga in Sarawak, East-Malaysia

    Science.gov (United States)

    Ganendra, T. R.; Khan, N. M.; Razak, W. J.; Kouame, Y.; Mobarakeh, E. T.

    2016-06-01

    The use of Light Detection and Ranging (LiDAR) remote sensing technology to scan and map landscapes has proven to be one of the most popular techniques to accurately map topography. Thus, LiDAR technology is the ultimate method of unveiling the surface feature under dense vegetation, and, this paper intends to emphasize the diverse techniques that can be utilized to elucidate topographical changes over the study area, using multi-temporal airborne full waveform LiDAR datasets collected in 2012 and 2014. Full waveform LiDAR data offers access to an almost unlimited number of returns per shot, which enables the user to explore in detail topographical changes, such as vegetation growth measurement. The study also found out topography changes at the study area due to earthwork activities contributing to soil consolidation, soil erosion and runoff, requiring cautious monitoring. The implications of this study not only concurs with numerous investigations undertaken by prominent researchers to improve decision making, but also corroborates once again that investigations employing multi-temporal LiDAR data to unveil topography changes in vegetated terrains, produce more detailed and accurate results than most other remote sensing data.

  11. 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.

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    Yanbin Gao

    2015-09-01

    Full Text Available 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.

  14. 3D Power Line Reconstruction from Airborne LiDAR Point Cloud of Overhead Electric Power Transmission Corridors

    Directory of Open Access Journals (Sweden)

    LIN Xiangguo

    2016-03-01

    Full Text Available 3D power line reconstruction is one of the main tasks in power line patrols using LiDAR systems mounted on helicopters. A 3D reconstruction method is proposed to reconstruct the power lines from the airborne LiDAR point clouds of the overhead electric power transmission corridors. Firstly, the pylons' LiDAR points and the initial routine trajectory of the transmission lines are employed to derive the precise information such as the locations and number of the pylons, the real routine trajectory, and the total number of spans. Secondly, the power line corridor is divided into a number of spans, the scope of each span in the XOY plane is determined, and the powerline LiDAR points are allocated into the corresponding spans where they are located. Thirdly, the powerline points of each span are clustered by the k-means algorithm in a normalized projection space, and each cluster corresponds to one power line. Finally, each power line is reconstructed based on a combination of a line model and a parabola model. Two experiments suggest that the proposed method is capable of automatically and correctly reconstructing 3D models of the long power lines with high accuracy. Moreover, it is robust to many factors such as the changing number, types, arrangements, blunders of the power lines, the changing length of the spans, and the irregular breakage of the LiDAR point clouds.

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

    Science.gov (United States)

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

    2016-04-01

    Rockfall activity in steep alpine landscapes is often difficult to survey due to its infrequent nature. Classic approaches are limited by temporal and spatial resolution. In contrast, seismic monitoring provides access to catchment-wide analysis of activity patterns in rockfall-dominated environments. The deglaciated U-shaped Lauterbrunnen Valley in the Bernese Oberland, Switzerland, is a perfect example of such landscapes. It was instrumented with up to six broadband seismometers and repeatedly surveyed by terrestrial LiDAR to provide independent validation data. During August-October 2014 and April-June 2015 more than 23 (LiDAR) to hundred (seismic) events were detected. Their volumes range from conditions that control such processes in a comprehensive way. Taken together, the combined LiDAR and seismic monitoring approach provides high fidelity spatial and temporal resolution of individual events.

  16. Identification of hydrothermal alterations using Dar-Zarouk parameters and concept of anisotropy for 2D resistivity data

    Science.gov (United States)

    Permatasari, A. O.; Supriyanto, Kuswanto, A.

    2017-07-01

    Measurement of geoelectric methods is commonly performed by using homogeneous and isotropy approaches. However, these approaches are not entirely the same due to the earth's real condition. Therefore, it needs to be measured with inhomogeneous and anisotropy approach. This approach uses the parameter of Dar-Zarouk. The parameter of Dar-Zarouk is used to calculate the values of the resistivity of media and the coefficient of anisotropy. This research is intended for identifying the hydrothermal alteration that is not uniform in the field. The inhomogeneous and anisotropy approach is very appropriate to be used and expected to give a clearer cross section of true resistivity in subsurface imaging. The results of the model using the parameter of Dar-Zarouk sharpen the anomaly, hence the existence of alteration could be more visible and easier identified.

  17. Arrangements for enhanced measurements of a large turbine near-wake using LiDAR from the nacelle

    Science.gov (United States)

    Trujillo, J. J.; Rettenmeier, A.; Schlipf, D.

    2008-05-01

    New LiDAR techniques are being tested and developed to support the development of large offshore wind turbines. Our interest in this paper is concentrated in wake measurements; therefore, a pulsed standard LiDAR is adapted for fullscale wind field measurements from the nacelle of a large wind turbine. We show the conceptual framework for planned adaptations to a Windcube® LiDAR for operation at the nacelle of a 5 MW wind turbine. The standard scanning mode is to be modified to properly obtain downstream and also upstream wind speeds. The wind field measurements are intended for verification of models for near-wake wind speed, wake meandering and new predictive control estrategies.

  18. Registration of Aerial Image with Airborne LiDAR Data Based on Plücker Line

    Directory of Open Access Journals (Sweden)

    SHENG Qinghong

    2015-07-01

    Full Text Available Registration of aerial image with airborne LiDAR data is a key to feature extraction. A registration model based on Plücker line is proposed. The relative position and attitude relationship between the conjugate lines in LiDAR and image is determined based on Plücker linear equation, which describes line transformation in space, then coplanarity condition equation is established. Finally, coordinate transformation between image point and corresponding LiDAR point is achieved by the spiral movement of Plücker lines in the image. The registration model of Plücker linear coplanarity condition equation is simple, and jointly describes the rotation and translation to avoid coupling error between them, so the accuracy is approved. This research provides technical support for high-quality earth spatial information acquisition.

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2016-10-01

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

  1. 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.

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

    Science.gov (United States)

    Xu, Z.

    2015-12-01

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

  3. Use of Airborne LiDAR To Estimate Forest Stand Characteristics

    Science.gov (United States)

    Li, Qi; Zhou, Wei; Li, Chang

    2014-03-01

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

  4. 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.

  5. Landscape metrics of coastal dunefields from LiDAR and hyper-spectral remote sensing

    Science.gov (United States)

    Zhang, L.; Baas, A. C.

    2010-12-01

    This paper presents an upscaling study extracting landscape metrics of coastal dunefields, calculated from local topography and vegetation-type abundance, from high-resolution LiDAR and collocated hyper-spectral remote-sensing imagery, at coastal sites in Wales, UK. The hyper-spectral data (Eagle & Hawk instruments on NERC’s ARSF aircraft in 2009) are analysed in combination with spectrometer ground-truthing to determine relative within-pixel (down-scaled) abundance maps of different vegetation types, using a novel method that combines linear spectral mixture modelling with a maximum likelihood classification. The resulting landscape metrics are the same state variables that have been used for classifying simulated dunefield landscapes in the DECAL model and for tracking the evolution of the ecogeomorphology in a 3D state space. The landscape metrics of the dunefields can now be plotted in the same space on the same ordinates to establish a direct and quantitative comparison beween simulated and real-world landscapes. For the Kenfig Dunefield in Wales, LiDAR and hyperspectral analysis has also been accomplished on archived (1997) data to investigate the changes in metrics over a 12-year period.

  6. 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.

  7. Characterization of the OPAL LiDAR under controlled obscurant conditions

    Science.gov (United States)

    Cao, Xiaoying; Church, Philip; Matheson, Justin

    2016-05-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  9. New SHARE 2010 HSI-LiDAR dataset: re-calibration, detection assessment and delivery

    Science.gov (United States)

    Ientilucci, Emmett J.

    2016-09-01

    This paper revisits hyperspectral data collected from the SpecTIR hyperspectral airborne Rochester Experiment (SHARE) in 2010. It has been determined that there were calibration issues in the SWIR portion of the data. This calibration issue is discussed and has been rectified. Approaches for calibration to radiance and compensation to reflectance are discussed based on in-scene information and radiative transfer codes. In addition to the entire flight line, a much large target detection test and evaluation chip has been created which includes an abundance of potential false alarms. New truth masks are created along with results from target detection algorithms. Co-registered LiDAR data is also presented. Finally, all ground truth information (ground photos, metadata, MODTRAN tape5, ASD ground spectral measurements, target truth masks, etc.), in addition to the HSI flight lines and co-registered LiDAR data, has been organized, packaged and uploaded to the Center for Imaging Science / Digital Imaging and Remote Sensing Lab web server for public use.

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

    Science.gov (United States)

    Peng, Daifeng; Zhang, Yongjun

    2016-06-01

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

  11. 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.

  12. Irrigation network extraction methodology from LiDAR DTM using Whitebox and ArcGIS

    Science.gov (United States)

    Mahor, M. A. P.; De La Cruz, R. M.; Olfindo, N. T.; Perez, A. M. C.

    2016-10-01

    Irrigation networks are important in distributing water resources to areas where rainfall is not enough to sustain agriculture. They are also crucial when it comes to being able to redirect vast amounts of water to decrease the risks of flooding in flat areas, especially near sources of water. With the lack of studies about irrigation feature extraction, which range from wide canals to small ditches, this study aims to present a method of extracting these features from LiDAR-derived digital terrain models (DTMs) using Geographic Information Systems (GIS) tools such as ArcGIS and Whitebox Geospatial Analysis Tools (Whitebox GAT). High-resolution LiDAR DTMs with 1-meter horizontal and 0.25-meter vertical accuracies were processed to generate the gully depth map. This map was then reclassified, converted to vector, and filtered according to segment length, and sinuosity to be able to isolate these irrigation features. Initial results in the test area show that the extraction completeness is greater than 80% when compared with data obtained from the National Irrigation Administration (NIA).

  13. 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.

  14. 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.

  15. 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

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

  17. 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.

  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. Automatic detection of zebra crossings from mobile LiDAR data

    Science.gov (United States)

    Riveiro, B.; González-Jorge, H.; Martínez-Sánchez, J.; Díaz-Vilariño, L.; Arias, P.

    2015-07-01

    An algorithm for the automatic detection of zebra crossings from mobile LiDAR data is developed and tested to be applied for road management purposes. The algorithm consists of several subsequent processes starting with road segmentation by performing a curvature analysis for each laser cycle. Then, intensity images are created from the point cloud using rasterization techniques, in order to detect zebra crossing using the Standard Hough Transform and logical constrains. To optimize the results, image processing algorithms are applied to the intensity images from the point cloud. These algorithms include binarization to separate the painting area from the rest of the pavement, median filtering to avoid noisy points, and mathematical morphology to fill the gaps between the pixels in the border of white marks. Once the road marking is detected, its position is calculated. This information is valuable for inventorying purposes of road managers that use Geographic Information Systems. The performance of the algorithm has been evaluated over several mobile LiDAR strips accounting for a total of 30 zebra crossings. That test showed a completeness of 83%. Non-detected marks mainly come from painting deterioration of the zebra crossing or by occlusions in the point cloud produced by other vehicles on the road.

  20. 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.

  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. 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

  3. 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.

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

    Science.gov (United States)

    Sim, Sungdae; Sock, Juil; Kwak, Kiho

    2016-06-22

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

  5. 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.

  6. 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.

  7. 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.

  8. 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)

  9. 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.

  10. Using LiDAR to Estimate Total Aboveground Biomass of Redwood Stands in the Jackson Demonstration State Forest, Mendocino, California

    Science.gov (United States)

    Rao, M.; Vuong, H.

    2013-12-01

    The overall objective of this study is to develop a method for estimating total aboveground biomass of redwood stands in Jackson Demonstration State Forest, Mendocino, California using airborne LiDAR data. LiDAR data owing to its vertical and horizontal accuracy are increasingly being used to characterize landscape features including ground surface elevation and canopy height. These LiDAR-derived metrics involving structural signatures at higher precision and accuracy can help better understand ecological processes at various spatial scales. Our study is focused on two major species of the forest: redwood (Sequoia semperirens [D.Don] Engl.) and Douglas-fir (Pseudotsuga mensiezii [Mirb.] Franco). Specifically, the objectives included linear regression models fitting tree diameter at breast height (dbh) to LiDAR derived height for each species. From 23 random points on the study area, field measurement (dbh and tree coordinate) were collected for more than 500 trees of Redwood and Douglas-fir over 0.2 ha- plots. The USFS-FUSION application software along with its LiDAR Data Viewer (LDV) were used to to extract Canopy Height Model (CHM) from which tree heights would be derived. Based on the LiDAR derived height and ground based dbh, a linear regression model was developed to predict dbh. The predicted dbh was used to estimate the biomass at the single tree level using Jenkin's formula (Jenkin et al 2003). The linear regression models were able to explain 65% of the variability associated with Redwood's dbh and 80% of that associated with Douglas-fir's dbh.

  11. Comparison of Canopy Volume Measurements of Scattered Eucalypt Farm Trees Derived from High Spatial Resolution Imagery and LiDAR

    Directory of Open Access Journals (Sweden)

    Niva Kiran Verma

    2016-05-01

    Full Text Available Studies estimating canopy volume are mostly based on laborious and time-consuming field measurements; hence, there is a need for easier and convenient means of estimation. Accordingly, this study investigated the use of remotely sensed data (WorldView-2 and LiDAR for estimating tree height, canopy height and crown diameter, which were then used to infer the canopy volume of remnant eucalypt trees at the Newholme/Kirby ‘SMART’ farm in north-east New South Wales. A regression model was developed with field measurements, which was then applied to remote-sensing-based measurements. LiDAR estimates of tree dimensions were generally lower than the field measurements (e.g., 6.5% for tree height although some of the parameters (such as tree height may also be overestimated by the clinometer/rangefinder protocols used. The WorldView-2 results showed both crown projected area and crown diameter to be strongly correlated to canopy volume, and that crown diameter yielded better results (Root Mean Square Error RMSE 31% than crown projected area (RMSE 42%. Although the better performance of LiDAR in the vertical dimension cannot be dismissed, as suggested by results obtained from this study and also similar studies conducted with LiDAR data for tree parameter measurements, the high price and complexity associated with the acquisition and processing of LiDAR datasets mean that the technology is beyond the reach of many applications. Therefore, given the need for easier and convenient means of tree parameters estimation, this study filled a gap and successfully used 2D multispectral WorldView-2 data for 3D canopy volume estimation with satisfactory results compared to LiDAR-based estimation. The result obtained from this study highlights the usefulness of high resolution data for canopy volume estimations at different locations as a possible alternative to existing methods.

  12. 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.

  13. QTL mapping for fruit quality in Citrus using DArTseq markers.

    Science.gov (United States)

    Curtolo, Maiara; Cristofani-Yaly, Mariângela; Gazaffi, Rodrigo; Takita, Marco Aurélio; Figueira, Antonio; Machado, Marcos Antonio

    2017-04-12

    Citrus breeding programs have many limitations associated with the species biology and physiology, requiring the incorporation of new biotechnological tools to provide new breeding possibilities. Diversity Arrays Technology (DArT) markers, combined with next-generation sequencing, have wide applicability in the construction of high-resolution genetic maps and in quantitative trait locus (QTL) mapping. This study aimed to construct an integrated genetic map using full-sib progeny derived from Murcott tangor and Pera sweet orange and DArTseq™ molecular markers and to perform QTL mapping of twelve fruit quality traits. A controlled Murcott x Pera crossing was conducted at the Citrus Germplasm Repository at the Sylvio Moreira Citrus Centre of the Agronomic Institute (IAC) located in Cordeirópolis, SP, in 1997. In 2012, 278 F1 individuals out of a family of 312 confirmed hybrid individuals were analyzed for fruit traits and genotyped using the DArTseq markers. Using OneMap software to obtain the integrated genetic map, we considered only the DArT loci that showed no segregation deviation. The likelihood ratio and the genomic information from the available Citrus sinensis L. Osbeck genome were used to determine the linkage groups (LGs). The resulting integrated map contained 661 markers in 13 LGs, with a genomic coverage of 2,774 cM and a mean density of 0.23 markers/cM. The groups were assigned to the nine Citrus haploid chromosomes; however, some of the chromosomes were represented by two LGs due the lack of information for a single integration, as in cases where markers segregated in a 3:1 fashion. A total of 19 QTLs were identified through composite interval mapping (CIM) of the 12 analyzed fruit characteristics: fruit diameter (cm), height (cm), height/diameter ratio, weight (g), rind thickness (cm), segments per fruit, total soluble solids (TSS, %), total titratable acidity (TTA, %), juice content (%), number of seeds, TSS/TTA ratio and number of fruits per

  14. 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

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

    Science.gov (United States)

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

    2009-12-01

    Ground-based LiDAR (Light Detection and Ranging) survey techniques are enabling remote visualization and quantitative analysis of geologic features at unprecedented levels of detail. For example, digital terrain models computed from LiDAR data have been used to measure displaced landforms along active faults and to quantify fault-surface roughness. But how accurately do terrestrial LiDAR data represent the true ground surface, and in particular, how internally consistent and precise are the mosaiced LiDAR datasets from which surface models are constructed? Addressing this question is essential for designing survey workflows that capture the necessary level of accuracy for a given project while minimizing survey time and equipment, which is essential for effective surveying of remote sites. To address this problem, we seek to define a metric that quantifies how scan registration error changes as a function of survey workflow. Specifically, we are using a Trimble GX3D laser scanner to conduct a series of experimental surveys to quantify how common variables in field workflows impact the precision of scan registration. Primary variables we are testing include 1) use of an independently measured network of control points to locate scanner and target positions, 2) the number of known-point locations used to place the scanner and point clouds in 3-D space, 3) the type of target used to measure distances between the scanner and the known points, and 4) setting up the scanner over a known point as opposed to resectioning of known points. Precision of the registered point cloud is quantified using Trimble Realworks software by automatic calculation of registration errors (errors between locations of the same known points in different scans). Accuracy of the registered cloud (i.e., its ground-truth) will be measured in subsequent experiments. To obtain an independent measure of scan-registration errors and to better visualize the effects of these errors on a registered point

  16. 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

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

    DEFF Research Database (Denmark)

    Ernstsen, Verner Brandbyge; Andersen, Mikkel S.; Gergely, Aron;

    of the Wadden Sea National Park and UNESCO World Heritage, and in the Ribe Vesterå, a fluvial environment in the Ribe Å river catchment discharging into the Knudedyb tidal basin. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the MBES and the LiDAR point...... clouds, which both have point densities in the order of 20 points/m2. Morphometric analyses of the DEMs enabled the identification and mapping of the different landforms within the coastal and fluvial environments. Hereby, we demonstrate that vessel borne MBES and airborne topobathymetric LiDAR, here...

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

    Science.gov (United States)

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

    2017-06-01

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

  19. Diameter at breast height estimation in Mt. Makiling, Laguna, Philippines using metrics derived from airborne LiDAR data and Worldview-2 bands

    Science.gov (United States)

    Tandoc, Fe Andrea M.; Paringit, Enrico C.; Bantayan, Nathaniel C.; Argamosa, Reginald Jay L.; Faelga, Regine Anne G.; Ibañez, Carlyn Ann G.; Posilero, Mark Anthony V.; Zaragosa, Gio P.; Malabanan, Matthew V.

    2016-05-01

    Airborne LiDAR is fast becoming an innovation for forest inventory. It aids in obtaining forest characteristics in areas or cases where actual field inventory would be very tedious. This study aims to estimate diameter at breast height (DBH) using airborne LiDAR point-cloud parameters with Worldview-2 satellite images, and to validate these with actual measurements done in the field. The study site is a field plot with forest inventory at Mt. Makiling, Laguna, Philippines that was surveyed into 20m, 10m and 5m subplots or grids. The estimation of DBH was carried out by extracting the said parameters from the LiDAR point-cloud, and extracting different bands from the Worldview image and performing linear and log-linear regression of these values. The regressions were done in four different cases, namely: LiDAR parameters without intensity (case1), LiDAR parameters without intensity with Worldview bands (case 2), intensity of LiDAR points (case 3), and LiDAR parameters with intensity and Worldview bands (case 4). From these it was found that the best case for estimating DBH is with the use of LiDAR parameters with intensity and Worldview bands in a 10x10 grid, in Log-Linear regression with a root mean squared error of 1.96 cm and an adjusted R2 value of 0.65. This was further improved through stepwise regression, and adjusted R2 value was 0.71.

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

    Science.gov (United States)

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

    2014-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Luciane Yumie Sato

    2016-10-01

    Full Text Available 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 measurements of vegetation vertical arrangement, which can be directly associated with aboveground biomass. This work aims, for the first time, to quantify post-fire changes in forest canopy height and biomass using airborne LiDAR in western Amazonia. For this, the present study evaluated four areas located in the state of Acre, called Rio Branco, Humaitá, Bonal and Talismã. Rio Branco and Humaitá burned in 2005 and Bonal and Talismã burned in 2010. In these areas, we inventoried a total of 25 plots (0.25 ha each in 2014. Humaitá and Talismã are located in an open forest with bamboo and Bonal and Rio Branco are located in a dense forest. Our results showed that even ten years after the fire event, there was no complete recovery of the height and biomass of the burned areas (p < 0.05. The percentage difference in height between control and burned sites was 2.23% for Rio Branco, 9.26% for Humaitá, 10.03% for Talismã and 20.25% for Bonal. All burned sites had significantly lower biomass values than control sites. In Rio Branco (ten years after fire, Humaitá (nine years after fire, Bonal (four years after fire and Talismã (five years after fire biomass was 6.71%, 13.66%, 17.89% and 22.69% lower than control sites, respectively. The total amount of biomass lost for the studied sites was 16,706.3 Mg, with an average loss of 4176.6 Mg for sites burned in 2005 and 2890 Mg for sites burned in 2010, with an average loss of 3615 Mg. Fire impact associated with tree mortality was clearly detected using LiDAR data up to ten years after the fire event. This study indicates that fire disturbance

  2. 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

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

    Science.gov (United States)

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

    2015-12-01

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

  4. The Method of Building Extraction from LiDAR Point Clouds Using Aerial Images Assits%利用影像辅助 LiDAR 点云数据的建筑物提取方法研究

    Institute of Scientific and Technical Information of China (English)

    谭金石

    2015-01-01

    As a new earth observation technology, Airborne LiDAR can quickly obtain information of three -dimensional surface.Howto extract buildings from massive LiDAR point cloud data is a key work of data processing .Combined with LiDAR data and aerial imagerydata, this paper proposed a method of building extraction from LiDAR point clouds method using aerial images assists .First, extractthe contour of buildings from aerial imagery with object -oriented method, and then building outline information for reference ,extract building data from LiDAR point cloud.Finally, experiments demonstrate the effectiveness and feasibility of the method , andhave some practical value.%机载LiDAR作为一种新兴的对地观测技术,能够快速地获取地表三维信息。如何从海量LiDAR点云数据中提取建筑物是数据处理中的一项关键工作。本文结合LiDAR数据和航空影像的数据特点,提出了一种航空影像辅助的LiDAR点云建筑物提取方法,首先,采用面向对象方法从航空影像中提取建筑物的轮廓;然后,以建筑轮廓信息为参考,从LiDAR点云中提取建筑物的点云数据;最后,通过实验证明该方法的有效性与可行性。

  5. 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.

  6. 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.

  7. An historically consistent and broadly applicable MRV system based on LiDAR sampling and Landsat time-series

    Science.gov (United States)

    W. Cohen; H. Andersen; S. Healey; G. Moisen; T. Schroeder; C. Woodall; G. Domke; Z. Yang; S. Stehman; R. Kennedy; C. Woodcock; Z. Zhu; J. Vogelmann; D. Steinwand; C. Huang

    2014-01-01

    The authors are developing a REDD+ MRV system that tests different biomass estimation frameworks and components. Design-based inference from a costly fi eld plot network was compared to sampling with LiDAR strips and a smaller set of plots in combination with Landsat for disturbance monitoring. Biomass estimation uncertainties associated with these different data sets...

  8. 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...

  9. 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...

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

    Science.gov (United States)

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

    2016-09-06

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

  11. A new method for individual tree delineation and undergrowth removal from high resolution airborne LiDAR

    NARCIS (Netherlands)

    Abd Rahman, M.Z.; Gorte, B.G.H.; Bucksch, A.K.

    2009-01-01

    High density airborne LiDAR, for example FLI-MAP 400 data, has opened an opportunity for individual tree measurement. This paper presents a method for individual tree delineation and undergrowth vegetation removal in forest area. The delineation of individual trees involves two steps namely 1) tree

  12. 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 a

  13. 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...

  14. 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...

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

    Science.gov (United States)

    Feng, Dengchao; Yuan, Xiaohui

    2016-05-01

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

  16. Analysis of LiDAR point data and derived elevation models for mapping and characterizing bouldery landforms

    Science.gov (United States)

    Maxwell, Aaron Edward

    This thesis assessed the viability of using LiDAR-derived elevation data in accurately mapping and characterizing bouldery geomorphic features in a study area in the Allegheny Mountains. This study showed that the ground returns classification process conducted by the Canaan Valley Institute (CVI) for their property using the TerraScan software generally removed 5 to 10 m scale local topographic variability and bouldery landforms in creating the CVI classified ground returns data. In open areas, last returns elevation and intensity data were successfully used in this study to map bouldery landforms in the study area. Identifying and describing boulders under a tree canopy required a relatively reliable ground classification of LiDAR points. This study's classifications conducted within Prologic LiDAR Explorer provided a more useful representation than the CVI classified ground data for mapping bouldery landforms and generalized rugged topography. Index overlay for likelihood of presence of bouldery landforms using supervised classified aerial imagery and LiDAR-derived parameters in a raster environment was explored as an alternative means of detecting bouldery landforms because hillshade imagery derived from CVI classified ground data were inadequate for mapping bouldery landforms.

  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 on the Level 2 Global Land Surface Altimetry Data product and the other using Level 1A Global Altimetry Data (GLA01) with terrain correction. Both methods use Gaussian decomposition of the full waveform. Airborne LiDAR (AL) was also used to quantify terrain...

  18. 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

    2017-12-06

    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.

  19. 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.

  20. A new method for individual tree delineation and undergrowth removal from high resolution airborne LiDAR

    NARCIS (Netherlands)

    Abd Rahman, M.Z.; Gorte, B.G.H.; Bucksch, A.K.

    2009-01-01

    High density airborne LiDAR, for example FLI-MAP 400 data, has opened an opportunity for individual tree measurement. This paper presents a method for individual tree delineation and undergrowth vegetation removal in forest area. The delineation of individual trees involves two steps namely 1) tree

  1. 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...

  2. 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...

  3. Demand for orthodontic treatment among 9-18 year-olds seeking dental care in Dar-es-Salaam, Tanzania.

    NARCIS (Netherlands)

    Mugonzibwa, E.A.; Kuijpers-Jagtman, A.M.; Hof, M.A. van 't; Kikwilu, E.

    2004-01-01

    OBJECTIVE: To investigate the demand for orthodontic treatment among 9-18 olds seeking dental care in Dar-es-Salaam, Tanzania. DESIGN: Case-control, interview and clinical study. SETTINGS: Children seeking dental care. MAIN OUTCOME MEASURES: Demand for orthodontic treatment. RESULTS: Most of the chi

  4. 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...

  5. Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure

    Directory of Open Access Journals (Sweden)

    François Pimont

    2015-06-01

    Full Text Available Leaf biomass distribution is a key factor for modeling energy and carbon fluxes in forest canopies and for assessing fire behavior. We propose a new method to estimate 3D leaf bulk density distribution, based on a calibration of indices derived from T-LiDAR. We applied the method to four contrasted plots in a mature Quercus pubescens forest. Leaf bulk densities were measured inside 0.7 m-diameter spheres, referred to as Calibration Volumes. Indices were derived from LiDAR point clouds and calibrated over the Calibration Volume bulk densities. Several indices were proposed and tested to account for noise resulting from mixed pixels and other theoretical considerations. The best index and its calibration parameter were then used to estimate leaf bulk densities at the grid nodes of each plot. These LiDAR-derived bulk density distributions were used to estimate bulk density vertical profiles and loads and above four meters compared well with those assessed by the classical inventory-based approach. Below four meters, the LiDAR-based approach overestimated bulk densities since no distinction was made between wood and leaf returns. The results of our method are promising since they demonstrate the possibility to assess bulk density on small plots at a reasonable operational cost.

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

    Science.gov (United States)

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

    2012-04-01

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

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

    Science.gov (United States)

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

    2015-04-01

    Malaysia has faced a substantial number of landslide events every year. Cameron Highlands, Pahang is one of the badly areas affected by slope failures characterized by extreme climate, rugged topographic and weathered geological structures in a tropical environment. A high frequency of landslide occurrence in the hilly areas is predominantly due to the geological materials, tropical monsoon seasons and uncontrolled agricultural activities. Therefore the Government of Malaysia through the Prime Minister Department has allocated a special budget to conduct national level hazard and risk mapping project through Minerals and Geoscience Department Malaysia, the Ministry of Natural Resources and Environment. The primary aim of this project is to provide slope hazard risk information for a better slope management in Malaysia. In addition this project will establish national infrastructure for geospatial information on the geological terrain and slope by emphasizing the disaster risk throughout the country. The areas of interest are located in the three different selected areas i.e. Cameron Highlands (275 square kilometers), Ipoh (200 square kilometers) and Cheras Kajang -- Batang kali (650 square kilometers). These areas are selected based on National Slope Master Plan (2009 -- 2023) that endorsed by Malaysia Government Cabinet. The national hazard and risk mapping project includes six parts of major tasks: (1) desk study and mobilization, (2) airborne LiDAR data acquisition and analysis, (3) field data acquisition and verification, (4) hazard and risk for natural terrain, (5) hazard and risk analysis for man-made slope and (6) Man-made slope mitigation/preventive measures. The project was authorized in September, 2014 and will be ended in March, 2016. In this paper, the main focus is to evaluate the suitability of integrated capability of airborne- and terrestrial LiDAR data acquisition and analysis, and also digital photography for regional landslide assessment. The

  9. Potential Landslide Detection with Fractal and Roughness by LiDAR Data in Taiwan

    Science.gov (United States)

    Cheng, Youg-Sin; Yu, Teng-To

    2015-04-01

    The purpose of this study is to detect the potential landslides since they would be triggered by heavy rain, earthquake and/or larger degree of geomorphology alteration under different terrain characteristics. Not only the newly area but also the past landslide area would generate landslide after serious events. To gather the newly landslides and past landslides overwhelmed by thick vegetation, LiDAR could produce the high resolution DEM, denote actual surface terrain information and identify landform with a spatial resolution of 1m in different time interval. The 1-m interval DEM of Laonong watershed of southern Taiwan is utilized by fractal and roughness calculating with MATLAB code. DEM, aspect, and slope images are adopted to improve the accuracy of potential landslide detection with the random forest (RF) classifier. In present study, we provide the analysis results of the potential landslide area including these features calculation.

  10. A Denoising Method for LiDAR Full-Waveform Data

    Directory of Open Access Journals (Sweden)

    Xudong Lai

    2015-01-01

    Full Text Available Decomposition of LiDAR full-waveform data can not only enhance the density and positioning accuracy of a point cloud, but also provide other useful parameters, such as pulse width, peak amplitude, and peak position which are important information for subsequent processing. Full-waveform data usually contain some random noises. Traditional filtering algorithms always cause distortion in the waveform. λ/μ filtering algorithm is based on Mean Shift method. It can smooth the signal iteratively and will not cause any distortion in the waveform. In this paper, an improved λ/μ filtering algorithm is proposed, and several experiments on both simulated waveform data and real waveform data are implemented to prove the effectiveness of the proposed algorithm.

  11. 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

    to the numerical CFD model. A sensitivity analysis with regards to the resolution of the structured forest height grid obtained from the implemented digital elevation model (DEM) was carried out. CFD calculations were conducted with the forest height grid taken as input and the complete methodology results......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...... are finally briefly compared to the wind measurements of the site with regards to the calculated wind field prediction accuracy....

  12. 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.

  13. Understanding household behavioral risk factors for diarrheal disease in Dar es Salaam: a photovoice community assessment.

    Science.gov (United States)

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

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Natalie Badowski

    2011-01-01

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

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

    Science.gov (United States)

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

    2013-12-01

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

  16. 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. 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.

  18. Modeling spatiotemporal patterns of understory light intensity using airborne laser scanner (LiDAR)

    Science.gov (United States)

    Peng, Shouzhang; Zhao, Chuanyan; Xu, Zhonglin

    2014-11-01

    This study described a spatiotemporally explicit 3D raytrace model to provide spatiotemporal patterns of understory light (light intensity in the forest floor and along the vertical gradient). The model was built based on voxels derived from LiDAR and field investigation data, geographical information (elevation and location), and solar position (azimuth and altitude angles). We calculated the distance (L, in meters) traveled by solar ray in the crowns based on the model, and then calibrated and verified the light attenuation function using L based on Beer's law. L and the ratio of below canopy light intensity to above canopy light intensity showed obviously exponential relationship, with R2 = 0.94 and P competition, soil evaporation, plant transpiration, and snowmelt in the forest.

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

    Science.gov (United States)

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

    2009-04-01

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

  20. 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

    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...... comprehensive and formalized regulatory tools to draw from. Different cities around the world are now deciding how to fit urban agriculture into the urban agenda; however, in many places urban agriculture continues to operate in the absence of legitimization due to its relatively mobile and dynamic nature....... 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...