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Human hypervariable sequences in risk assessment: rare Ha-ras alleles in cancer patients

International Nuclear Information System (INIS)

Krontiris, T.G.; DiMartino, N.A.; Mitcheson, H.D.; Lonergan, J.A.; Begg, C.; Parkinson, D.R.

1987-01-01

A variable tandem repeat (VTR) is responsible for the hyperallelism one kilobase 3' to the human c-Ha-ras-1 (Ha-ras) gene. Thirty-two distinct restriction fragments, comprising 3 allelic classes by frequency of occurrence, have thus far been detected in a sample size of approximately 800 caucasians. Rare Ha-ras alleles, 21 in all, are almost exclusively confined to the genomes of cancer patients. From their data the authors have computed the relative cancer risk associated with possession of a rare Ha-ras allele to be 27. To understand the molecular basis for this phenomenon, they have begun to clone Ha-ras fragments from nontumor DNA of cancer patients. They report here the weak activation, as detected by transfection and transformation of NIH 3T3 mouse cells, of two Ha-ras genes which were obtained from lymphocyte DNA of a melanoma patient. They have mapped the regions that confer this transforming activity to the fragment containing the VTR in one Ha-ras clone and the fragment containing gene coding sequences in the other
Oxidative Stress Posttranslationally Regulates the Expression of Ha-Ras and Ki-Ras in Cultured Astrocytes

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Samantha Messina

2012-01-01

Full Text Available Addition of hydrogen peroxide to cultured astrocytes induced a rapid and transient increase in the expression of Ha-Ras and Ki-Ras. Pull-down experiments with the GTP-Ras-binding domain of Raf-1 showed that oxidative stress substantially increased the activation of Ha-Ras, whereas a putative farnesylated activated form of Ki-Ras was only slightly increased. The increase in both Ha-Ras and Ki-Ras was insensitive to the protein synthesis inhibitor, cycloheximide, and was occluded by the proteasomal inhibitor, MG-132. In addition, exposure to hydrogen peroxide reduced the levels of ubiquitinated Ras protein, indicating that oxidative stress leads to a reduced degradation of both isoforms through the ubiquitin/proteasome pathway. Indeed, the late reduction in Ha-Ras and Ki-Ras was due to a recovery of proteasomal degradation because it was sensitive to MG-132. The late reduction of Ha-Ras levels was abrogated by compound PD98059, which inhibits the MAP kinase pathway, whereas the late reduction of Ki-Ras was unaffected by PD98059. We conclude that oxidative stress differentially regulates the expression of Ha-Ras and Ki-Ras in cultured astrocytes, and that activation of the MAP kinase pathway by oxidative stress itself or by additional factors may act as a fail-safe mechanism limiting a sustained expression of the potentially detrimental Ha-Ras.
Genetic alterations in Ki-ras and Ha-ras genes in Juvenile Nasopharyngeal Angiofibromas and head and neck cancer

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Cláudia Malheiros Coutinho

1999-05-01

Full Text Available CONETXT: Ras gene mutations have been associated to a wide range of human solid tumors. Members of the ras gene family (Ki-ras, Ha-ras and N-ras are structurally related and code for a protein (p21 known to play an important role in the regulation of normal signal transduction and cell growth. The frequency of ras mutations is different from one type of tumor to another, suggesting that point mutations might be carcinogen-specific. OBJECTIVES: To study the occurrence of Ki-ras and Ha-ras mutations. We also studied the relative level of Ha-ras mRNA in 32 of the head and neck tumors. DESIGN: Case series. SETTING: University referral unit. PARTICIPANTS: 60 head and neck tumors and in 28 Juvenile Nasopharyngeal Angiofibromas (JNA. DIAGNOSTIC TEST: Using PCR-SSCP we examined the occurrence of Ki-ras and Ha-ras mutations. The relative level of Ha-ras mRNA was examined by Northern blot analysis. RESULTS: None of the head and neck tumors or JNA samples showed evidence of mutations within codons 12, 13, 59 and 61 of Ki-ras or Ha-ras genes. However, 17 (53% of the tumors where gene expression could be examined exhibited increased levels of Ha-ras mRNA compared with the normal tissue derived from the same patient. CONCLUSIONS: Our results demonstrate for the first time that mutations of Ki-ras and Ha-ras genes are not associated with the development of JNA and confirm previous reports indicating that activating ras mutations are absent or rarely involved in head and neck tumors from western world patients. Furthermore, our findings suggest that overexpression of Ha-ras, rather than mutations, might be an important factor in the development and progression of head and neck tumors.
HARAS. A new method for risk evaluation of working with open radioactive materials

International Nuclear Information System (INIS)

Klaver, T.

1998-01-01

Thumbs of rule with respect to the characteristics and the handling of, and protection facilities for radioactive materials in laboratories are used by everybody involved in radiation protection activities. However, the thumbs of rule must be based on a thorough risk analysis. The so-called HARAS study provides the results of such an analysis, consisting of recommendations to alter the government policy with respect to radionuclide laboratories. HARAS is a Dutch abbreviation for handling of radioactive materials
S4HARA: System for HIV/AIDS resource allocation.

Science.gov (United States)

Lasry, Arielle; Carter, Michael W; Zaric, Gregory S

2008-03-26

HIV/AIDS resource allocation decisions are influenced by political, social, ethical and other factors that are difficult to quantify. Consequently, quantitative models of HIV/AIDS resource allocation have had limited impact on actual spending decisions. We propose a decision-support System for HIV/AIDS Resource Allocation (S4HARA) that takes into consideration both principles of efficient resource allocation and the role of non-quantifiable influences on the decision-making process for resource allocation. S4HARA is a four-step spreadsheet-based model. The first step serves to identify the factors currently influencing HIV/AIDS allocation decisions. The second step consists of prioritizing HIV/AIDS interventions. The third step involves allocating the budget to the HIV/AIDS interventions using a rational approach. Decision-makers can select from several rational models of resource allocation depending on availability of data and level of complexity. The last step combines the results of the first and third steps to highlight the influencing factors that act as barriers or facilitators to the results suggested by the rational resource allocation approach. Actionable recommendations are then made to improve the allocation. We illustrate S4HARA in the context of a primary healthcare clinic in South Africa. The clinic offers six types of HIV/AIDS interventions and spends US$750,000 annually on these programs. Current allocation decisions are influenced by donors, NGOs and the government as well as by ethical and religious factors. Without additional funding, an optimal allocation of the total budget suggests that the portion allotted to condom distribution be increased from 1% to 15% and the portion allotted to prevention and treatment of opportunistic infections be increased from 43% to 71%, while allocation to other interventions should decrease. Condom uptake at the clinic should be increased by changing the condom distribution policy from a pull system to a push
eEcoLiDAR, eScience infrastructure for ecological applications of LiDAR point clouds: reconstructing the 3D ecosystem structure for animals at regional to continental scales

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W. Daniel Kissling

2017-07-01

Full Text Available The lack of high-resolution measurements of 3D ecosystem structure across broad spatial extents impedes major advancements in animal ecology and biodiversity science. We aim to fill this gap by using Light Detection and Ranging (LiDAR technology to characterize the vertical and horizontal complexity of vegetation and landscapes at high resolution across regional to continental scales. The newly LiDAR-derived 3D ecosystem structures will be applied in species distribution models for breeding birds in forests and marshlands, for insect pollinators in agricultural landscapes, and songbirds at stopover sites during migration. This will allow novel insights into the hierarchical structure of animal-habitat associations, into why animal populations decline, and how they respond to habitat fragmentation and ongoing land use change. The processing of these massive amounts of LiDAR point cloud data will be achieved by developing a generic interactive eScience environment with multi-scale object-based image analysis (OBIA and interpretation of LiDAR point clouds, including data storage, scalable computing, tools for machine learning and visualisation (feature selection, annotation/segmentation, object classification, and evaluation, and a PostGIS spatial database. The classified objects will include trees, forests, vegetation strata, edges, bushes, hedges, reedbeds etc. with their related metrics, attributes and summary statistics (e.g. vegetation openness, height, density, vertical biomass distribution etc.. The newly developed eScience tools and data will be available to other disciplines and applications in ecology and the Earth sciences, thereby achieving high impact. The project will foster new multi-disciplinary collaborations between ecologists and eScientists and contribute to training a new generation of geo-ecologists.
Monoterpenoids from the traditional North Italian vegetable Aruncus dioicus (Walter) Fernald var. vulgaris (Maxim.) H.Hara (Rosaceae).

Science.gov (United States)

Granica, Sebastian; Fusani, Pietro; Stanisławska, Iwona; Piwowarski, Jakub P; Melck, Dominique; Motta, Andrea; Zidorn, Christian

2017-04-15

Investigations of young shoots of Aruncus dioicus (Walter) Fernald var. vulgaris (Maxim.) H.Hara (Rosaceae), collected from the wild and used as vegetables in alpine provinces of Italy, yielded eight monoterpenoids. Besides known compounds, aruncin A, aruncide A, and cimicifugolide, five previously undescribed substances, aruncins C, D, and E, and aruncides D and E, were identified. Based on results from the full synthesis of aruncin B, structures of aruncin A and aruncide A were revised. Structures were established by HR mass spectrometry and extensive 1D and 2D NMR spectroscopy and based on data from synthetic aruncin B. An HPLC-DAD-ESI-MS method was developed to investigate the distribution of the monoterpenoids in different organs of Aruncus dioicus var. vulgaris and in aerial parts of A. dioicus var. aethusifolius (H.Lév.) H.Hara [Syn.: Aruncus aethusifolius (H.Lév.) Nakai]. Preliminary bioactivity studies moreover indicated weak cytotoxicity for some of the compounds against human prostrate adenocarcinoma cells. Copyright © 2016 Elsevier Ltd. All rights reserved.
S4HARA: System for HIV/AIDS resource allocation

Directory of Open Access Journals (Sweden)

Carter Michael W

2008-03-01

Full Text Available Abstract Background HIV/AIDS resource allocation decisions are influenced by political, social, ethical and other factors that are difficult to quantify. Consequently, quantitative models of HIV/AIDS resource allocation have had limited impact on actual spending decisions. We propose a decision-support System for HIV/AIDS Resource Allocation (S4HARA that takes into consideration both principles of efficient resource allocation and the role of non-quantifiable influences on the decision-making process for resource allocation. Methods S4HARA is a four-step spreadsheet-based model. The first step serves to identify the factors currently influencing HIV/AIDS allocation decisions. The second step consists of prioritizing HIV/AIDS interventions. The third step involves allocating the budget to the HIV/AIDS interventions using a rational approach. Decision-makers can select from several rational models of resource allocation depending on availability of data and level of complexity. The last step combines the results of the first and third steps to highlight the influencing factors that act as barriers or facilitators to the results suggested by the rational resource allocation approach. Actionable recommendations are then made to improve the allocation. We illustrate S4HARA in the context of a primary healthcare clinic in South Africa. Results The clinic offers six types of HIV/AIDS interventions and spends US$750,000 annually on these programs. Current allocation decisions are influenced by donors, NGOs and the government as well as by ethical and religious factors. Without additional funding, an optimal allocation of the total budget suggests that the portion allotted to condom distribution be increased from 1% to 15% and the portion allotted to prevention and treatment of opportunistic infections be increased from 43% to 71%, while allocation to other interventions should decrease. Conclusion Condom uptake at the clinic should be increased by
Zonation of heme synthesis enzymes in mouse liver and their regulation by β-catenin and Ha-ras.

Science.gov (United States)

Braeuning, Albert; Schwarz, Michael

2010-11-01

Cytochrome P450 (CYP) hemoproteins play an important role in hepatic biotransformation. Recently, β-catenin and Ha-ras signaling have been identified as players controlling transcription of various CYP genes in mouse liver. The aim of the present study was to analyze the role of β-catenin and Ha-ras in the regulation of heme synthesis. Heme synthesis-related gene expression was analyzed in normal liver, in transgenic mice expressing activated β-catenin or Ha-ras, and in hepatomas. Regulation of the aminolevulinate dehydratase promoter was studied in vitro. Elevated expression of mRNAs and proteins involved in heme biosynthesis was linked to β-catenin activation in perivenous hepatocytes, in transgenic hepatocytes, and in hepatocellular tumors. Stimulation of the aminolevulinate dehydratase promoter by β-catenin was independent of the β-catenin/T-cell-specific transcription factor dimer. By contrast, activation of Ha-ras repressed heme synthesis-related gene expression. The present data suggest that β-catenin enhances the expression of both CYPs and heme synthesis-related genes, thus coordinating the availability of CYP apoprotein and its prosthetic group heme. The reciprocal regulation of heme synthesis by β-catenin and Ha-ras-dependent signaling supports our previous hypothesis that antagonistic action of these pathways plays a major role in the control of zonal gene expression in healthy mouse liver and aberrant expression patterns in hepatocellular tumors.
ANALISIS KADAR HARA PUPUK ORGANIK KASCING DARI LIMBAH KANGKUNG DAN BAYAM

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Elfayetti Elfayetti

2017-04-01

Full Text Available Pertanian organik merupakan sistem pertanian yang holistik yang mendukung dan mempercepat biodeversiti, siklus biologi dan aktivitas biologi tanah(International Federation of Organic Agriculture Movements,2014. Geografi Pertanian merupakan mata kuliah di Jurusan Pendidikan Geografi FIS Unimed. Dalam Kurikulum Berbasis Kompetensi yang diterapkan di Jurusan Pendidikan Geografi FIS Unimed merupakan matakuliah wajib pada semester genap, tepatnya pada semester IV (empat. Penelitian ini bertujuan untuk mengetahui kemampuan pertumbuhan berat cacing tanah pada pupuk kascing dari limbah kangkung dan bayam dan untuk mengetahui kandungan hara N, P, K dan pH kascing dari limbah kangkung dan bayam pada tanah ultisol. Untuk mengatasi permasalahan pada pupuk organik, maka harus diupayakan bagaimana memperoleh pupuk yang memiliki unsur hara yang padat dan pengadaannya relatif murah dan mudah. Pemanfaatan limbah organik untuk budidaya cacing tanah merupakan salah satu tindakan yang tepat untuk mencapai tujuan tersebut. Rendahnya bahan organik, N, P, K menunjukkan bahwa tanah pada percobaan ini membutuhkan bahan organik. Pemberian bahan organik seperti cacing diharapkan dapat meningkatkan Produktivitas Ultisol dimana Kascing mempunyai sifat-sifat kimia, fisika, dan biologi tanah yang baik, sehingga dapat meningkatkan serapan hara dan pertumbuhan tanaman. Berdasarkan hasil penelitian maka dapat disimpulkan bahwa : 1. Jenis makanan berpengaruh terhadap pertumbuhan cacing tanah dan kualitas kascing yang dihasilkan. 2.Terdapat perbedaaan pada bobot cacing tanah yang dihasilkan dengan adanya perbedaan jenis makanan. Jenis makanan bayam memberikan tingkat pertumbuhan cacing tanah terbaik dengan terjadinya pertambahan bobot sebesar 650 gram yang awalnya hanya 250 gram. 3. Dari beberapa parameter sifat kimia dan biologi kascing, maka jenis makanan bayam memberikan nilai N tertinggi yaitu 0,52 dan pada pakan kangkung terdapatnilai p tertinggi yaitu 0,35. Kata Kunci
Poesia y Pintura: Frank O'Hara y el expresinionismo abstracto

OpenAIRE

Alberto Santamaría

2015-01-01

El objetivo de este artículo es analizar las relaciones entre poesía y pintura en el seno del expresionismo abstracto. Para ello tomamos tres nombres de referencia: Clement Greenberg (crítico de arte), Frank O'Hara (poeta) y Willem De Kooning (pintor). A través de estos nombres tratamos de señalar la estrecha relación que existía entre poetas y pintores en la llamada Escuela de Nueva York.
LiDAR Vegetation Investigation and Signature Analysis System (LVISA)

Science.gov (United States)

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

2015-04-01

Our physical environment undergoes constant changes in space and time with strongly varying triggers, frequencies, and magnitudes. Monitoring these environmental changes is crucial to improve our scientific understanding of complex human-environmental interactions and helps us to respond to environmental change by adaptation or mitigation. The three-dimensional (3D) description of the Earth surface features and the detailed monitoring of surface processes using 3D spatial data have gained increasing attention within the last decades, such as in climate change research (e.g., glacier retreat), carbon sequestration (e.g., forest biomass monitoring), precision agriculture and natural hazard management. In all those areas, 3D data have helped to improve our process understanding by allowing quantifying the structural properties of earth surface features and their changes over time. This advancement has been fostered by technological developments and increased availability of 3D sensing systems. In particular, LiDAR (light detection and ranging) technology, also referred to as laser scanning, has made significant progress and has evolved into an operational tool in environmental research and geosciences. The main result of LiDAR measurements is a highly spatially resolved 3D point cloud. Each point within the LiDAR point cloud has a XYZ coordinate associated with it and often additional information such as the strength of the returned backscatter. The point cloud provided by LiDAR contains rich geospatial, structural, and potentially biochemical information about the surveyed objects. To deal with the inherently unorganized datasets and the large data volume (frequently millions of XYZ coordinates) of LiDAR datasets, a multitude of algorithms for automatic 3D object detection (e.g., of single trees) and physical surface description (e.g., biomass) have been developed. However, so far the exchange of datasets and approaches (i.e., extraction algorithms) among LiDAR users
Temporal Analysis and Automatic Calibration of the Velodyne HDL-32E LiDAR System

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T. O. Chan

2013-10-01

Full Text Available 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
Phytochemical Studies on Polygonum barbatum (L. Hara var. barbata (Polygonaceae

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M. Abdul Mazid

2011-01-01

Full Text Available Polygonum barbatum (L. Hara var. barbata (Polygonaceae, commonly known as ‘bekhanjabaj’, is a Bangladeshi perennial herb. A combination of the normal phase column chromatography and preparative thin layer chromatography on silica gel afforded sitosterone (1 from the petroleum ether fraction, and viscozulenic acid (2 and acetophenone (3 from the chloroform fraction of the methanol extract of the aerial parts of this plant . The free-radical-scavenging properties the isolated compounds 1-3 were evaluated by the 2,2-diphenyl-1-picryl-hydrazyl (DPPH assay.
Ha-ras oncogene expression directed by a milk protein gene promoter: tissue specificity, hormonal regulation, and tumor induction in transgenic mice

International Nuclear Information System (INIS)

Andres, A.C.; Schoenenberger, C.A.; Groner, B.; Henninghausen, L.; LeMeur, M.; Gelinger, P.

1987-01-01

The activated human Ha-ras oncogene was subjected to the control of the promoter region of the murine whey acidic protein (Wap) gene, which is expressed in mammary epithelial cells in response to lactogenic hormones. The Wap-ras gene was stably introduced into the mouse germ line of five transgenic mice (one male and four females). Wap-ras expression was observed in the mammary glands of lactating females in two lines derived from female founders. The tissue-directed and hormone-dependent Wap expression was conferred on the Ha-ras oncogene. The signals governing Wap expression are located within 2.5 kilobases of 5' flanking sequence. The other two lines derived from female founders did not express the chimeric gene. In the line derived from the male founder the Wap-ras gene is integrated into the Y chromosome. Expression was found in the salivary gland of male animals only. After a long latency, Wap-ras-expressing mice developed tumors. The tumors arose in tissues expressing Wap-ras - i.e., mammary or salivary glands. Compared to the corresponding nonmalignant tissues, Wap-ras expression was enhanced in the tumors
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
Effects of shading on Vallisneria natans (Lour.) H. Hara growth

DEFF Research Database (Denmark)

Fox, Anthony David; Meng, F; Shen, X

2013-01-01

Effects of surface shading were measured on above- and below-ground biomass and fruit production of Vallisneria natans (Lour.) H. Hara plants grown from seed in replicated microcosm experiments, based on a control (no shading) and four treatments (25%, 50%, 75% and 90% shading). Above- and below-...... spp. at seasonally inundated wetlands in the Yangtze River floodplain could, by shading, have contributed to the reduction in annual biomass and seed production of V. natans, contributing to declines in distribution and abundance....
Complex Urban LiDAR Data Set

OpenAIRE

Jeong, Jinyong; Cho, Younggun; Shin, Young-Sik; Roh, Hyunchul; Kim, Ayoung

2018-01-01

This paper presents a Light Detection and Ranging (LiDAR) data set that targets complex urban environments. Urban environments with high-rise buildings and congested traffic pose a significant challenge for many robotics applications. The presented data set is unique in the sense it is able to capture the genuine features of an urban environment (e.g. metropolitan areas, large building complexes and underground parking lots). Data of two-dimensional (2D) and threedimensional (3D) LiDAR, which...
Influence of Sulfur on the Arsenic Phytoremediation Using Vallisneria natans (Lour.) Hara.

Science.gov (United States)

Chen, Guoliang; Feng, Tao; Li, Zhixian; Chen, Zhang; Chen, Yuanqi; Wang, Haihua; Xiang, Yanci

2017-09-01

Influences of sulfur (S) on the accumulation and detoxification of arsenic (As) in Vallisneria natans (Lour.) Hara, an arsenic hyperaccumulating submerged aquatic plant, were investigated. At low sulfur levels (75%) present in the plant after exposure to As(V). Sulfur plays an important role in the arsenic translocation and detoxification, possibly through stimulating the synthesis of thiols and complexation of arsenite-phytochelatins. This suggests that addition of sulfur to the arsenic-contaminated water may provide a way to promote arsenic bioaccumulation in plants for phytoremediation of arsenic pollution.
Upregulation of DARS2 by HBV promotes hepatocarcinogenesis through the miR-30e-5p/MAPK/NFAT5 pathway.

Science.gov (United States)

Qin, Xian; Li, Changsheng; Guo, Tao; Chen, Jing; Wang, Hai-Tao; Wang, Yi-Tao; Xiao, Yu-Sha; Li, Jun; Liu, Pengpeng; Liu, Zhi-Su; Liu, Quan-Yan

2017-10-19

Infection with the hepatitis B virus (HBV) is closely associated with the development of hepatocellular carcinoma (HCC). The osmoregulatory transcription factor nuclear factor of activated T-cells 5 (NFAT5) has been shown to play an important role in the development of many types of human cancers. The role of NFAT5 in HBV-associated HCC has never previously been investigated. We compared expression profiles of NFAT5, DARS2 and miR-30e-5p in HCC samples, adjacent nontumor tissues and different hepatoma cell lines by quantitative real-time polymerase chain reaction and /or Western blot. Clinical data of HCC patients for up to 80 months were analyzed. The regulatory mechanisms upstream and convergent downstream pathways of NFAT5 in HBV-associated HCC were investigated by ChIP-seq, MSP, luciferase report assay and bioinformation anaylsis. We first found that higher levels of NFAT5 expression predict a good prognosis, suggesting that NFAT5 is a potential tumor-suppressing gene, and verified that NFAT5 promotes hepatoma cell apoptosis and inhibits cell growth in vitro. Second, our results showed that HBV could suppress NFAT5 expression by inducing hypermethylation of the AP1-binding site in the NFAT5 promoter in hepatoma cells. In addition, HBV also inhibited NFAT5 through miR-30e-5p targeted MAP4K4, and miR-30e-5p in turn inhibited HBV replication. Finally, we demonstrated that NFAT5 suppressed DARS2 by directly binding to its promoter. DARS2 was identified as an HCC oncogene that promotes HCC cell cycle progression and inhibits HCC cell apoptosis. HBV suppresses NFAT5 through the miR-30e-5p/mitogen-activated protein kinase (MAPK) signaling pathway upstream of NFAT5 and inhibits the NFAT5 to enhance HCC tumorigenesis via the downstream target genes of DARS2.

AVALIAÇÃO DA ACURÁCIA DO CÁLCULO DE VOLUME DE PILHAS DE REJEITO UTILIZANDO VANT, GNSS E LiDAR

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Cristiano Alves da Silva

Full Text Available Dentre as diversas tecnologias utilizadas para cálculo do volume de materiais na mineração, o Veículo Aéreo Não Tripulado (VANT e o Light Detecting And Ranging (LiDAR, surgem como alternativas rápidas e precisas, em comparação com as técnicas de topografia tradicionais como estação total e Global Navigation Satellite System (GNSS. Diante destas novas tecnologias, este estudo avaliou a acurácia do cálculo de volume, realizado por meio de Modelos Digitais de Terreno (MDTs, gerados a partir das tecnologias VANT, LiDAR e GNSS, em uma pilha de rejeito da extração de calcário laminado, explorado para fabricação de lajotas in natura, comercializado com o nome de "Pedra Cariri", no município de Santana do Cariri, no Estado do Ceará. A avaliação da acurácia foi realizada com base no método de testes de hipóteses, a partir da análise de tendência e precisão, sendo os resultados classificados de acordo com o Padrão de Exatidão Cartográfica dos Produtos Cartográficos Digitais (PEC-PCD. Como resultado, o modelo gerado a partir do VANT apresentou a melhor acurácia no cálculo de volume da pilha de rejeito, objeto deste estudo, seguido pela modelagem obtida pelos levantamentos GNSS e LiDAR.
NPV risk simulation of an open pit gold mine project under the O'Hara cost model by using GAs

Institute of Scientific and Technical Information of China (English)

Franco-Sepulveda Giovanni; Campuzano Carlos; Pineda Cindy

2017-01-01

This paper analyzes an open pit gold mine project based on the O'Hara cost model. Hypothetical data is proposed based on different authors that have studied open pit gold projects, and variations are proposed according to the probability distributions associated to key variables affecting the NPV, like production level, ore grade, price of ore, and others, so as to see what if, in a gold open pit mine project of 3000 metric tons per day of ore. Two case scenarios were analyzed to simulate the NPV, one where there is low certainty data available, and the other where the information available is of high certainty. Results based on genetic algorithm metaheuristic simulations, which combine basically Montecarlo simulations provided by the Palisade Risk software, the O'Hara cost model, net smelter return and financial analysis tools offered by Excel are reported, in order to determine to which variables of the project is more sensitive the NPV.
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...
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...
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...
Doble gesto suicida por hara-kiri: intento de suicidio y posterior consumación

OpenAIRE

Revetria Betancor, Malbinia; Sarkissián, Paula; Rodríguez Alamada, Hugo

2017-01-01

El hara kiri es una forma de suicidio cuyo origen se encuentra en la cultura medieval japonesa. Es muy poco frecuente en el Japón contemporáneo y excepcional en Occidente, generalmente asociados a la esquizofrenia. Se presenta un caso de suicidio por este método ocurrido en Uruguay por un varón adulto sin vinculación con la cultura japonesa, con antecedentes de un intento de suicidio anterior por el mismo método, y se realiza una puesta al día del tema. El análisis de los hallazgos d...
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...
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)...
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...
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)...
eEcoLiDAR, eScience infrastructure for ecological applications of LiDAR point clouds : reconstructing the 3D ecosystem structure for animals at regional to continental scales

NARCIS (Netherlands)

Kissling, W.D.; Seijmonsbergen, A.C.; Foppen, R.P.B.; Bouten, W.

2017-01-01

The lack of high-resolution measurements of 3D ecosystem structure across broad spatial extents impedes major advancements in animal ecology and biodiversity science. We aim to fill this gap by using Light Detection and Ranging (LiDAR) technology to characterize the vertical and horizontal
2014 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Cedar River Watershed (Delivery 2)

Data.gov (United States)

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

Directory of Open Access Journals (Sweden)

Fox A.D.

2013-08-01

Full Text Available Effects of surface shading were measured on above- and below-ground biomass and fruit production of Vallisneria natans (Lour. H. Hara plants grown from seed in replicated microcosm experiments, based on a control (no shading and four treatments (25%, 50%, 75% and 90% shading. Above- and below-ground biomass was significantly reduced at treatments above 50% shading and first pistillate and staminate florescence dates were significantly delayed above 75% and 50% shading, respectively. Ratios of mature to unripe fruits produced (both in number or dry weight did not differ between shading treatments, but dry weight fruit production was significantly reduced at 90% shading. We conclude that above 50% surface shading, V. natans plants suffer reductions in accumulated biomass and investment in sexual reproduction. We contend that recent expansions in the extent of the native floating water chestnut Trapa spp. at seasonally inundated wetlands in the Yangtze River floodplain could, by shading, have contributed to the reduction in annual biomass and seed production of V. natans, contributing to declines in distribution and abundance.
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...
Estimation of the fraction of absorbed photosynthetically active radiation (fPAR) in maize canopies using LiDAR data and hyperspectral imagery.

Science.gov (United States)

Qin, Haiming; Wang, Cheng; Zhao, Kaiguang; Xi, Xiaohuan

2018-01-01

Accurate estimation of the fraction of absorbed photosynthetically active radiation (fPAR) for maize canopies are important for maize growth monitoring and yield estimation. The goal of this study is to explore the potential of using airborne LiDAR and hyperspectral data to better estimate maize fPAR. This study focuses on estimating maize fPAR from (1) height and coverage metrics derived from airborne LiDAR point cloud data; (2) vegetation indices derived from hyperspectral imagery; and (3) a combination of these metrics. Pearson correlation analyses were conducted to evaluate the relationships among LiDAR metrics, hyperspectral metrics, and field-measured fPAR values. Then, multiple linear regression (MLR) models were developed using these metrics. Results showed that (1) LiDAR height and coverage metrics provided good explanatory power (i.e., R2 = 0.81); (2) hyperspectral vegetation indices provided moderate interpretability (i.e., R2 = 0.50); and (3) the combination of LiDAR metrics and hyperspectral metrics improved the LiDAR model (i.e., R2 = 0.88). These results indicate that LiDAR model seems to offer a reliable method for estimating maize fPAR at a high spatial resolution and it can be used for farmland management. Combining LiDAR and hyperspectral metrics led to better performance of maize fPAR estimation than LiDAR or hyperspectral metrics alone, which means that maize fPAR retrieval can benefit from the complementary nature of LiDAR-detected canopy structure characteristics and hyperspectral-captured vegetation spectral information.
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...
Darüşşifas Where Music Threapy was Practiced During Anatolian Seljuks and Ottomans / Selçuklu ve Osmanlı Darüşşifalarında Müzikle Tedavi

Directory of Open Access Journals (Sweden)

Gülşen Erdal

2013-03-01

etki günümüzde açıkça bilinmektedir. Bilinen en eski tedavi yöntemlerinden biri olan Müzikle tedavinin geçmişi binlerce yıl öncesine dayanır. Türklerin, müzikle tedavide İbn Sina, Razî, Farabî, Hasan Şuurî ve Gevrekzade Hasan Efendi gibi bilim adamlarının yaptıkları araştırmaların yer aldığı kitaplardan faydalanarak, Selçuklu ve Osmanlılar döneminde, akıl hastalıklarının tedavisine uygun akustikle inşa edilen hastaneler-darüşşifalarda kullanmaları, ilk ciddi müzikle tedavi uygulamaları olarak değerlendirilir. Darüşşifa, Türk ve İslam dünyasında pratiğe ve gözleme dayalı sağlık hizmetleri veren hastaları tedavi eden sağlık ve eğitim kurumlarına verilen isimlerden birisidir. Darüşşifalar Tıp mesleğinin uygulanmasına yönelik özel mimari anlayış içeren yapıları ile de ayrıcalıklı bir yere sahiptir. Türkler Anadolu’ya yerleşmeleri ile birlikte çeşitli imar faaliyetlerine başlamışlardır. Yapılan bu faaliyetler içerisinde kervansaraylar, medreseler ve camilerle birlikte darüşşifalar da bulunmaktadır. Selçuklu ve Osmanlı darüşşifalarında tıbbi konular araştırmalara ve bilimsel esaslara bağlı kalınarak işleniyor, aynı zamanda tıp medreselerinde cerrah yetiştiriliyordu. Yapılan eğitimler dışında tatbiki uygulamaların da yaptırıldığı bilinmektedir. Darrüşşifalar, Anadolu Selçuklu ve Osmanlı medreseleri plan şemasına uygun olarak tasarlanmıştır. Genelde derslerin verildiği ana eyvan ve farklı ihtiyaçlar için düzenlenmiş avlu etrafında yer alan odalardan oluşmaktaydı. Türk sanat tarihi içerisinde sıklıkla karşılaştığımız tıp siteleri aynı zamanda günümüz tıp fakültesi mantığı ile örtüşmektedir. Buralarda tedavi edici sağlık hizmetleri sunulmaktaydı. Müzikle tedavi yapılan darüşşifalardan günümüze ulaşan ve önem teşkil edenler bu çalışmada sanat tarihi ve müziğin iyileştirici gücünün yüzyıllar �
Specular and diffuse object extraction from a LiDAR derived Digital Surface Model (DSM)

International Nuclear Information System (INIS)

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

2014-01-01

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

Object Classification Using Airborne Multispectral LiDAR Data

Directory of Open Access Journals (Sweden)

PAN Suoyan

2018-02-01

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

Science.gov (United States)

2012-10-15

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

Science.gov (United States)

Fairweather, Ian; Crabtree, Robert; Hager, Stacey

2008-01-01

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

Directory of Open Access Journals (Sweden)

Gülşen Erdal

2013-03-01

günümüzde açıkça bilinmektedir. Bilinen en eski tedavi yöntemlerinden biri olan Müzikle tedavinin geçmişi binlerce yıl öncesine dayanır. Türklerin, müzikle tedavide İbn Sina, Razî, Farabî, Hasan Şuurî ve Gevrekzade Hasan Efendi gibi bilim adamlarının yaptıkları araştırmaların yer aldığı kitaplardan faydalanarak, Selçuklu ve Osmanlılar döneminde, akıl hastalıklarının tedavisine uygun akustikle inşa edilen hastaneler-darüşşifalarda kullanmaları, ilk ciddi müzikle tedavi uygulamaları olarak değerlendirilir. Darüşşifa, Türk ve İslam dünyasında pratiğe ve gözleme dayalı sağlık hizmetleri veren hastaları tedavi eden sağlık ve eğitim kurumlarına verilen isimlerden birisidir. Darüşşifalar Tıp mesleğinin uygulanmasına yönelik özel mimari anlayış içeren yapıları ile de ayrıcalıklı bir yere sahiptir. Türkler Anadolu’ya yerleşmeleri ile birlikte çeşitli imar faaliyetlerine başlamışlardır. Yapılan bu faaliyetler içerisinde kervansaraylar, medreseler ve camilerle birlikte darüşşifalar da bulunmaktadır. Selçuklu ve Osmanlı darüşşifalarında tıbbi konular araştırmalara ve bilimsel esaslara bağlı kalınarak işleniyor, aynı zamanda tıp medreselerinde cerrah yetiştiriliyordu. Yapılan eğitimler dışında tatbiki uygulamaların da yaptırıldığı bilinmektedir. Darrüşşifalar, Anadolu Selçuklu ve Osmanlı medreseleri plan şemasına uygun olarak tasarlanmıştır. Genelde derslerin verildiği ana eyvan ve farklı ihtiyaçlar için düzenlenmiş avlu etrafında yer alan odalardan oluşmaktaydı.Türk sanat tarihi içerisinde sıklıkla karşılaştığımız tıp siteleri aynı zamanda günümüz tıp fakültesi mantığı ile örtüşmektedir. Buralarda tedavi edici sağlık hizmetleri sunulmaktaydı. Müzikle tedavi yapılan darüşşifalardan günümüze ulaşan ve önem teşkil edenler bu çalışmada sanat tarihi ve müziğin iyileştirici gücünün yüzyıllar �
Opposite effects of Ha-Ras and Ki-Ras on radiation-induced apoptosis via differential activation of PI3K/Akt and Rac/p38 mitogen-activated protein kinase signaling

International Nuclear Information System (INIS)

Choi, J.-A.; Kang, C.-M.; Lee, Y.-S.; Lee, S.-J.; Bae, S.-W.; Cho, C.-K.

2003-01-01

It has been well known that Ras signaling is involved in various cellular processes, including proliferation, differentiation, and apoptosis. However, distinct cellular functions of Ras isozymes are not fully understood. Here we show the opposing roles of Ha-Ras and Ki-Ras genes in the modulation of cell sensitivity to ionizing radiation. Overexpression of active isoform of Ha-Ras (12V-Ha- Ras) in Rat2 cells increases resistance to the ionizing radiation. Constitutive activation of phosphoinositide-3-kinase (PI3K) and Akt is detected specifically in 12V-Ha-Ras-overexpressing cells. The specific PI3K inhibitor LY294002 inhibits PI3K/Akt signaling and potentiates the radiation-induced apoptosis, suggesting that activation of PI3K/Akt signaling pathway is involved in the increased radio-resistance in cells overexpressing 12V-Ha-Ras. Overexpression of activated Ki-Ras (12V-Ki-Ras), on the other hand, markedly increases radiation sensitivity. The p38 mitogen-activated protein (MAP) kinase activity is selectively enhanced by ionizing radiation in cells overexpressing 12V-Ki-Ras. The specific p38 MAP kinase inhibitor, PD169316, or dominant-negative p38 MAP kinase decreases radiation-induced cell death. We further show that the mechanism that underlies potentiation of cell death in cells overexpressing 12V-Ki-Ras involves Bax translocation to the mitochondrial membrane. Elevated Bax translocation following ionizing irradiation in 12V-Ki-Ras-overexpressing cells is completely inhibited by PD169316 or dominant-negative p38 MAP kinase. In addition, introduction of cells with RacN17, a dominant negative mutant of Rac, resulted in a marked inhibition of radiation-induced Bax translocation and apoptotic cell death as well as p38 MAP kinase activation. Taken together, these findings explain the opposite effects of Ha-Ras and Ki-Ras on modulation of radio-sensitivity, and suggest that differential activation of PI3K/Akt and Rac/p38 MAP kinase signaling by Ha-Ras and Ki-Ras may
2012-2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Hoh River Watershed, Washington (Deliveries 1 and 2)

Data.gov (United States)

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

NARCIS (Netherlands)

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

2014-01-01

Remote sensing of the atmospheric variables with the use of LiDAR is a relatively new technique for wind resource assessment and oncoming wind prediction in wind energy. The validation of LiDAR measurements and comparisons with other sensing elements thus, is of high importance for further
The Dar es Salaam Seascape: A Case Study of an Environmental ...

African Journals Online (AJOL)

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

Science.gov (United States)

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

2017-12-01

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

Science.gov (United States)

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

2010-01-01

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

Energy Technology Data Exchange (ETDEWEB)

Koop, J.E. [Manitoba Hydro, Winnipeg, MB (Canada)

2003-04-01

LiDAR (Light Detection and Ranging) technology is described as an example of techniques used by hydro companies to increase their capacity with existing plants, and within tight budget constraints. LiDAR was chosen by Manitoba Hydro primarily because LiDAR's data collection method offers very fast turn-around time from collection to delivery, and most importantly because of LiDAR's highly accurate ability to map terrain and wire catenary shape in every span. The article describes a case study of the 'Nip and Tuck' method of wire re-tensioning based on LiDAR data, which was used by Manitoba Hydro to create a computer model of Saskatchewan Hydro's transmission line capacity on its 138 kV transmission line between Saskatoon and North Battleford. The model was needed to analyze the existing line conditions in an effort to minimize cascading failures on the 40-year old line. Using the 'Nip and Tuck' technology in combination with LiDAR, SaskPower engineers were able to complete the required modifications to raise transmission wire operating temperatures on the 135 km long line to 66 degree C in only 36 days, and at a cost that was 80 per cent less than the cost would have been using conventional techniques ($232,000 instead of the estimated $1.25 million).
The study of Forest Hara Biosphere Reserve in coast of Persian Gulf and the importance of heavy metal accumulation; Case study: feathers of great cormorant

Directory of Open Access Journals (Sweden)

MIR MEHRDAD MIRSANJARI

2014-11-01

Full Text Available Mirsanjari MM, Sheybanifar F, Arjmand F. 2014. The study of forest Hara Biosphere Reserve in coast of Persian Gulf and the importance of heavy metal accumulation; Case study: feathers of great cormorant. Nusantara Bioscience 6: 159-164. In recent years, concerns about the long term effects of heavy metals as environmental polluters have arisen, since considerable quantities of heavy metals have been released into the environment as a result of extensive human activities. Heavy metal has been determined as a serious threat to the stability of ecosystems. In this study, we examined the levels of zinc‚ copper‚ lead, and cadmium in the feathers of twenty great cormorants (Phalacrocorax carbo, collected from Hara Biosphere Reserve during November and December in 2012. The results revealed that the mean concentration of heavy metals in the feathers of males is significantly higher than females (P < 0.05. In addition‚ no significant difference was observed in heavy metal concentration between juvenile and adult birds. Moreover, according to the results, the high concentration of heavy metals in some samples indicated this fact that birds are potentially exposed to the risk of heavy metals in their habitat.
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
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,...
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.

High resolution, topobathymetric LiDAR coastal zone characterization in Denmark

DEFF Research Database (Denmark)

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

2016-01-01

Coastal and tidal environments are valuable ecosystems, which, however, are under pressure in many areas around the world due to globalization and/or climate change. Detailed mapping of these environments is required in order to manage the coastal zone in a sustainable way. However, historically...... locations with different environmental settings. We demonstrate the potential of using airborne topobathymetric LiDAR for seamless mapping of land-water transition zones in challenging coastal environments, e.g. in an environment with high water column turbidity and continuously varying water levels due...... 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...
Waveform LiDAR across forest biomass gradients

Science.gov (United States)

Montesano, P. M.; Nelson, R. F.; Dubayah, R.; Sun, G.; Ranson, J.

2011-12-01

Detailed information on the quantity and distribution of aboveground biomass (AGB) is needed to understand how it varies across space and changes over time. Waveform LiDAR data is routinely used to derive the heights of scattering elements in each illuminated footprint, and the vertical structure of vegetation is related to AGB. Changes in LiDAR waveforms across vegetation structure gradients can demonstrate instrument sensitivity to land cover transitions. A close examination of LiDAR waveforms in footprints across a forest gradient can provide new insight into the relationship of vegetation structure and forest AGB. In this study we use field measurements of individual trees within Laser Vegetation Imaging Sensor (LVIS) footprints along transects crossing forest to non-forest gradients to examine changes in LVIS waveform characteristics at sites with low (field AGB measurements to original and adjusted LVIS waveforms to detect the forest AGB interval along a forest - non-forest transition in which the LVIS waveform lose the ability to discern differences in AGB. Our results help identify the lower end the forest biomass range that a ~20m footprint waveform LiDAR can detect, which can help infer accumulation of biomass after disturbances and during forest expansion, and which can guide the use of LiDAR within a multi-sensor fusion biomass mapping approach.
Kadar N, P, K, Ca Jaringan Sawi Pada Lahan Yang Diberi Air Bm Sapi Dan Bokashi Dengan Penambahan Beberapa Bahan Peningkat Hara

OpenAIRE

Walunguru, Lena; Lende, Aloysius Ng; Hasan, Mochammad

2009-01-01

Degree of N, P, K, Ca Mustard Green Network In Tune That Given Water Bm Cow And Bokashi With Add Several Ingredients To Increase Hara. Organic farming use organic fertilizer such as compost, bokashi, and cattle BM fertilizer. Input of organic fertilizer can decrease by increae the quality of bokashi by apply ash, eggshell powder, and cow crine. Ash to increase potassium, eggshell powder is source of calcium, and cow crine source of nitrogen. The research used Completely Randomized Block De...
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...
“Once Upon A Time”: The Efficiency of Storytelling in Shaping Drama Series, A Case Study on Bab El Hara

Directory of Open Access Journals (Sweden)

Joelle Chamieh

2016-12-01

Full Text Available We all know the enigma that compels us to dive into the excitement and vivacity of a certain story we are reading or a series we are watching. The characters become a part of us and the streets, café shops, etc., design our thoughts and dreams as they display the ‘vitrines’ of our reality. All is triggered by a simple word “once upon a time.” In this article, we go in-depth by analyzing storytelling and by exploring the significant role of the character as positioned in a text. However, our main concern is the possibility of being able to decipher values transmitted by a text, where the character plays a major role in terms of reflecting empathy/sympathy towards audiences’ perceptions. We, therefore, came with the idea of designing an innovative value analysis framework – based on Pierre Glaudes’s and Yves Reuter’s grid analysis pattern for value depiction – where two studies that analyze the famous series Bab El Hara, are cross referenced. Then, in order to test the validity of the framework, an original qualitative analysis based on a focus group session is conducted on ten Lebanese respondents (aged between 35 and 45 who relate their personal opinions and beliefs in terms of what they perceive in Bab El Hara, giving, therefore, indication to what values they identify with the most. Effectively, the values which respondents did identify with seemed to correspond perfectly with the value analysis framework which has shown to be a suitable base for value depiction.
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...
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...
Assessing LiDAR elevation data for KDOT applications.

Science.gov (United States)

2013-02-01

LiDAR-based elevation surveys are a cost-effective means for mapping topography over large areas. LiDAR : surveys use an airplane-mounted or ground-based laser radar unit to scan terrain. Post-processing techniques are : applied to remove vegetation ...
20-year LiDAR observations of stratospheric sudden warming over a mid-latitude site, Observatoire de Haute Provence (44°N, 6°E): Case study and statistical characteristics

CSIR Research Space (South Africa)

Charyulu, DV

2007-11-01

Full Text Available The present study delineates the characteristics of Stratospheric Sudden Warming (SSW) events observed over the Observatoire de Haute Provence (OHP: 44°N, 6°E). The study uses 20 years of Rayleigh LiDAR temperature measurements for the 1982...
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.
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.
Diversity arrays technology (DArT) markers in apple for genetic linkage maps

OpenAIRE

Schouten, H.J.; Weg, van de, W.E.; Carling, J.; Khan, S.A.; McKay, S.J.; Kaauwen, van, M.P.W.

2012-01-01

Diversity Arrays Technology (DArT) provides a high-throughput whole-genome genotyping platform for the detection and scoring of hundreds of polymorphic loci without any need for prior sequence information. The work presented here details the development and performance of a DArT genotyping array for apple. This is the first paper on DArT in horticultural trees. Genetic mapping of DArT markers in two mapping populations and their integration with other marker types showed that DArT is a powerf...
Diversity arrays technology (DArT) markers in apple for genetic linkage maps

OpenAIRE

Schouten, Henk J.; van de Weg, W. Eric; Carling, Jason; Khan, Sabaz Ali; McKay, Steven J.; van Kaauwen, Martijn P. W.; Wittenberg, Alexander H. J.; Koehorst-van Putten, Herma J. J.; Noordijk, Yolanda; Gao, Zhongshan; Rees, D. Jasper G.; Van Dyk, Maria M.; Jaccoud, Damian; Considine, Michael J.; Kilian, Andrzej

2011-01-01

Diversity Arrays Technology (DArT) provides a high-throughput whole-genome genotyping platform for the detection and scoring of hundreds of polymorphic loci without any need for prior sequence information. The work presented here details the development and performance of a DArT genotyping array for apple. This is the first paper on DArT in horticultural trees. Genetic mapping of DArT markers in two mapping populations and their integration with other marker types showed that DArT is a powerf...
Portable and Airborne Small Footprint LiDAR: Forest Canopy Structure Estimation of Fire Managed Plots

Directory of Open Access Journals (Sweden)

Claudia M.C.S. Listopad

2011-06-01

Full Text Available This study used an affordable ground-based portable LiDAR system to provide an understanding of the structural differences between old-growth and secondary-growth Southeastern pine. It provided insight into the strengths and weaknesses in the structural determination of portable systems in contrast to airborne LiDAR systems. Portable LiDAR height profiles and derived metrics and indices (e.g., canopy cover, canopy height were compared among plots with different fire frequency and fire season treatments within secondary forest and old growth plots. The treatments consisted of transitional season fire with four different return intervals: 1-yr, 2-yr, 3-yr fire return intervals, and fire suppressed plots. The remaining secondary plots were treated using a 2-yr late dormant season fire cycle. The old growth plots were treated using a 2-yr growing season fire cycle. Airborne and portable LiDAR derived canopy cover were consistent throughout the plots, with significantly higher canopy cover values found in 3-yr and fire suppressed plots. Portable LiDAR height profile and metrics presented a higher sensitivity in capturing subcanopy elements than the airborne system, particularly in dense canopy plots. The 3-dimensional structures of the secondary plots with varying fire return intervals were dramatically different to old-growth plots, where a symmetrical distribution with clear recruitment was visible. Portable LiDAR, even though limited to finer spatial scales and specific biases, is a low-cost investment with clear value for the management of forest canopy structure.
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,...
Study on environmental test technology of LiDAR used for vehicle

Science.gov (United States)

Wang, Yi; Yang, Jianfeng; Ou, Yong

2018-03-01

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

African Journals Online (AJOL)

Assessment on Vulnerable Youths Integration to Dar es Salaam Solid Waste ... existing municipal solid waste management crisis facing Dar es Salaam City using ... enabling environment of turning rampant solid waste collection a commercial ...
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 Li......DAR measurements and predict possible error in different wind directions for a certain terrain we have analyzed two experiment data sets from Greece. In both sites LiDAR and met. mast data have been collected and the same conditions are simulated with Riso/DTU software, WAsP Engineering 2.0. Finally measurement...
LiDAR data for the Delta Area of California

Data.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

Shezhou Luo

2015-12-01

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

Science.gov (United States)

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

2012-01-01

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

Directory of Open Access Journals (Sweden)

César D Petroli

Full Text Available Diversity Arrays Technology (DArT provides a robust, high throughput, cost-effective method to query thousands of sequence polymorphisms in a single assay. Despite the extensive use of this genotyping platform for numerous plant species, little is known regarding the sequence attributes and genome-wide distribution of DArT markers. We investigated the genomic properties of the 7,680 DArT marker probes of a Eucalyptus array, by sequencing them, constructing a high density linkage map and carrying out detailed physical mapping analyses to the Eucalyptus grandis reference genome. A consensus linkage map with 2,274 DArT markers anchored to 210 microsatellites and a framework map, with improved support for ordering, displayed extensive collinearity with the genome sequence. Only 1.4 Mbp of the 75 Mbp of still unplaced scaffold sequence was captured by 45 linkage mapped but physically unaligned markers to the 11 main Eucalyptus pseudochromosomes, providing compelling evidence for the quality and completeness of the current Eucalyptus genome assembly. A highly significant correspondence was found between the locations of DArT markers and predicted gene models, while most of the 89 DArT probes unaligned to the genome correspond to sequences likely absent in E. grandis, consistent with the pan-genomic feature of this multi-Eucalyptus species DArT array. These comprehensive linkage-to-physical mapping analyses provide novel data regarding the genomic attributes of DArT markers in plant genomes in general and for Eucalyptus in particular. DArT markers preferentially target the gene space and display a largely homogeneous distribution across the genome, thereby providing superb coverage for mapping and genome-wide applications in breeding and diversity studies. Data reported on these ubiquitous properties of DArT markers will be particularly valuable to researchers working on less-studied crop species who already count on DArT genotyping arrays but for
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...
2003 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Lewis 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 100 square miles and covers part of...
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.
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...
Object-oriented identification of forested landslides with derivatives of single pulse LiDAR data

Science.gov (United States)

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

2012-11-01

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

Directory of Open Access Journals (Sweden)

M. Abdul Mazid

Full Text Available The antinociceptive, anti-inflammatory and diuretic properties of the extracts of P. barbatum (L. Hara var. barbata, Polygonaceae, at the doses of 200 and 400 mg/kg body weight, were evaluated in mice/rat models using, respectively, the acetic-acid-induced writhing method, the carrageenan-induced edema test and the Lipschitz method. In the acetic-acid-induced writhing test in mice, all extracts displayed a dose dependent analgesic effect. The most potent analgesic activity was observed with the petroleum ether extract at the dose of 400 mg/kg body weight with an inhibition of writhing response 46.8% compared to 62.2% for the positive control aminopyrine. Petroleum ether extract at the dose of 400 mg/kg body weight also displayed the highest levels of anti-inflammatory activity after 2 h with the 39.3% inhibition of paw edema, and this effect was better than the effect observed by the conventional anti-inflammatory agent phenylbutazone (maximum inhibition of 38.3% after 4 h. All extracts increased urine volume in a dose-dependent manner, and the ethyl acetate extract showed a significant level of diuresis comparable to that of the standard diuretic agent furosemide.
Bridging gaps: On the performance of airborne LiDAR to model wood mouse-habitat structure relationships in pine forests.

Science.gov (United States)

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

2017-01-01

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

Science.gov (United States)

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

2012-04-01

Field measurements of the wake flow produced from the interaction between atmospheric boundary layer and a wind turbine are performed with three wind LiDARs. The tested wind turbine is a 2 MW Enercon E-70 located in Collonges, Switzerland. First, accuracy of mean values and frequency resolution of the wind measurements are surveyed as a function of the number of laser rays emitted for each measurement. Indeed, measurements performed with one single ray allow maximizing sampling frequency, thus characterizing wake turbulence. On the other hand, if the number of emitted rays is increased accuracy of mean wind is increased due to the longer sampling period. Subsequently, two-dimensional measurements with a single LiDAR are carried out over vertical sections of the wind turbine wake and mean wake flow is obtained by averaging 2D measurements consecutively performed. The high spatial resolution of the used LiDAR allows characterizing in details velocity defect present in the central part of the wake and its downstream recovery. Single LiDAR measurements are also performed by staring the laser beam at fixed directions for a sampling period of about ten minutes and maximizing the sampling frequency in order to characterize wake turbulence. From these tests wind fluctuation peaks are detected in the wind turbine wake at blade top-tip height for different downstream locations. The magnitude of these turbulence peaks is generally reduced by moving downstream. This increased turbulence level at blade top-tip height observed for a real wind turbine has been already detected from previous wind tunnel tests and Large Eddy simulations, thus confirming the presence of a source of dangerous fatigue loads for following wind turbines within a wind farm. Furthermore, the proper characterization of wind fluctuations through LiDAR measurements is proved by the detection of the inertial subrange from spectral analysis of these velocity signals. Finally, simultaneous measurements with two
Evaluating UAV and LiDAR Retrieval of Snow Depth in a Coniferous Forest in Arizona

Science.gov (United States)

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

2017-12-01

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

DEFF Research Database (Denmark)

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

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

Science.gov (United States)

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

2010-01-01

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

Science.gov (United States)

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

2013-01-01

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

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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.
Nitrogen concentration estimation with hyperspectral LiDAR

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O. Nevalainen

2013-10-01

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

'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
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

the consistency of the developed ontologies, and logical reasoning is performed to infer implicit relations between defined concepts. The ontology for the definition of building is specified using the Ontology Web Language (OWL). It is the most widely used ontology language that is based on Description Logics (DL). DL allows the description of internal properties of modelled concepts (roof typology, shape, area, height etc.) and relationships between objects (IS_A, MEMBER_OF/INSTANCE_OF). It captures terminological knowledge (TBox) as well as assertional knowledge (ABox) - that represents facts about concept instances, i.e. the buildings in airborne LiDAR data. To assess the classification accuracy, ground truth data generated by visual interpretation and calculated classification results in terms of precision and recall are used. The advantages of this approach are: (i) flexibility, (ii) transferability, and (iii) extendibility - i.e. ontology can be extended with further concepts, data properties and object properties.
The application of LiDAR to investigate foredune morphology and vegetation

Science.gov (United States)

Doyle, Thomas B.; Woodroffe, Colin D.

2018-02-01

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

Science.gov (United States)

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

2017-09-01

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

Directory of Open Access Journals (Sweden)

Jian Yang

2015-11-01

Full Text Available Delineating canopy gaps and quantifying gap characteristics (e.g., size, shape, and dynamics are essential for understanding regeneration dynamics and understory species diversity in structurally complex forests. Both high spatial resolution optical and light detection and ranging (LiDAR remote sensing data have been used to identify canopy gaps through object-based image analysis, but few studies have quantified the pros and cons of integrating optical and LiDAR for image segmentation and classification. In this study, we investigate whether the synergistic use of optical and LiDAR data improves segmentation quality and classification accuracy. The segmentation results indicate that the LiDAR-based segmentation best delineates canopy gaps, compared to segmentation with optical data alone, and even the integration of optical and LiDAR data. In contrast, the synergistic use of two datasets provides higher classification accuracy than the independent use of optical or LiDAR (overall accuracy of 80.28% ± 6.16% vs. 68.54% ± 9.03% and 64.51% ± 11.32%, separately. High correlations between segmentation quality and object-based classification accuracy indicate that classification accuracy is largely dependent on segmentation quality in the selected experimental area. The outcome of this study provides valuable insights of the usefulness of data integration into segmentation and classification not only for canopy gap identification but also for many other object-based applications.
IsoDAR@KamLAND:A Conceptual Design Report for the Conventional Facilities arXiv

CERN Document Server

Alonso, Jose R.

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

African Journals Online (AJOL)

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

Science.gov (United States)

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

2013-10-01

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

Science.gov (United States)

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

2018-03-01

Numerous airborne LiDAR-derived metrics have been proposed for classifying tree species. Yet an in-depth ecological and biological understanding of the significance of these metrics for tree species mapping remains largely unexplored. In this paper, we evaluated the performance of 37 frequently used LiDAR metrics derived under leaf-on and leaf-off conditions, respectively, for discriminating six different tree species in a natural forest in Germany. We firstly assessed the correlation between these metrics. Then we applied a Random Forest algorithm to classify the tree species and evaluated the importance of the LiDAR metrics. Finally, we identified the most important LiDAR metrics and tested their robustness and transferability. Our results indicated that about 60% of LiDAR metrics were highly correlated to each other (|r| > 0.7). There was no statistically significant difference in tree species mapping accuracy between the use of leaf-on and leaf-off LiDAR metrics. However, combining leaf-on and leaf-off LiDAR metrics significantly increased the overall accuracy from 58.2% (leaf-on) and 62.0% (leaf-off) to 66.5% as well as the kappa coefficient from 0.47 (leaf-on) and 0.51 (leaf-off) to 0.58. Radiometric features, especially intensity related metrics, provided more consistent and significant contributions than geometric features for tree species discrimination. Specifically, the mean intensity of first-or-single returns as well as the mean value of echo width were identified as the most robust LiDAR metrics for tree species discrimination. These results indicate that metrics derived from airborne LiDAR data, especially radiometric metrics, can aid in discriminating tree species in a mixed temperate forest, and represent candidate metrics for tree species classification and monitoring in Central Europe.
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...
PERFORMANCE EVALUATION OF sUAS EQUIPPED WITH VELODYNE HDL-32E LiDAR SENSOR

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G. Jozkow

2017-08-01

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

Science.gov (United States)

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

2017-08-01

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

Science.gov (United States)

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

2012-01-01

Scientists at NASA's Goddard Space Flight Center have developed an ultra-portable, low-cost, multi-sensor remote sensing system for studying the form and function of terrestrial ecosystems. G-LiHT integrates two LIDARs, a 905 nanometer single beam profiler and 1550 nm scanner, with a narrowband (1.5 nanometers) VNIR imaging spectrometer and a broadband (8-14 micrometers) thermal imager. The small footprint (approximately 12 centimeters) LIDAR data and approximately 1 meter ground resolution imagery are advantageous for high resolution applications such as the delineation of canopy crowns, characterization of canopy gaps, and the identification of sparse, low-stature vegetation, which is difficult to detect from space-based instruments and large-footprint LiDAR. The hyperspectral and thermal imagery can be used to characterize species composition, variations in biophysical variables (e.g., photosynthetic pigments), surface temperature, and responses to environmental stressors (e.g., heat, moisture loss). Additionally, the combination of LIDAR optical, and thermal data from G-LiHT is being used to assess forest health by sensing differences in foliage density, photosynthetic pigments, and transpiration. Low operating costs (approximately $1 ha) have allowed us to evaluate seasonal differences in LiDAR, passive optical and thermal data, which provides insight into year-round observations from space. Canopy characteristics and tree allometry (e.g., crown height:width, canopy:ground reflectance) derived from G-LiHT data are being used to generate realistic scenes for radiative transfer models, which in turn are being used to improve instrument design and ensure continuity between LiDAR instruments. G-LiHT has been installed and tested in aircraft with fuselage viewports and in a custom wing-mounted pod that allows G-LiHT to be flown on any Cessna 206, a common aircraft in use throughout the world. G-LiHT is currently being used for forest biomass and growth estimation
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...
Interactions between bees and Ludwigia elegans (Camb. Hara (Onagraceae flowers at different altitudes in São Paulo, Brazil

Directory of Open Access Journals (Sweden)

Miriam Gimenes

2002-09-01

Full Text Available Populations of Ludwigia elegans (Carnb. Hara were examined in Aluminio (600m and Campos do Jordão (1520m, in the State of São Paulo. Flowers of both populations are self-incompatible and dependent on bees for pollination. Flowers of Ludwigia elegans at the Aluminio site were visited by about 30 different species of bees, and those at Campos do Jordão by 10. These results can be related to climatic differences at the two sites, especially temperature, due to their difference in altitude. Inspite of the difference in the absolute number of bee species seen at each site, Tetraglossula anthracina (Michener, 1989 (Colletidae can be considered a specialized and efficient pollinator in both areas, since it visited these flowers frequently and showed many morphological and behavioral adaptations for pollen and nectar collection.
3D turbulence measurements in inhomogeneous boundary layers with three wind LiDARs

Science.gov (United States)

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

2014-05-01

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

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)
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,...
Calibration and Validation of a Detailed Architectural Canopy Model Reconstruction for the Simulation of Synthetic Hemispherical Images and Airborne LiDAR Data

Directory of Open Access Journals (Sweden)

Magnus Bremer

2017-02-01

Full Text Available Canopy density measures such as the Leaf Area Index (LAI have become standardized mapping products derived from airborne and terrestrial Light Detection And Ranging (aLiDAR and tLiDAR, respectively data. A specific application of LiDAR point clouds is their integration into radiative transfer models (RTM of varying complexity. Using, e.g., ray tracing, this allows flexible simulations of sub-canopy light condition and the simulation of various sensors such as virtual hemispherical images or waveform LiDAR on a virtual forest plot. However, the direct use of LiDAR data in RTMs shows some limitations in the handling of noise, the derivation of surface areas per LiDAR point and the discrimination of solid and porous canopy elements. In order to address these issues, a strategy upgrading tLiDAR and Digital Hemispherical Photographs (DHP into plausible 3D architectural canopy models is suggested. The presented reconstruction workflow creates an almost unbiased virtual 3D representation of branch and leaf surface distributions, minimizing systematic errors due to the object–sensor relationship. The models are calibrated and validated using DHPs. Using the 3D models for simulations, their capabilities for the description of leaf density distributions and the simulation of aLiDAR and DHP signatures are shown. At an experimental test site, the suitability of the models, in order to systematically simulate and evaluate aLiDAR based LAI predictions under various scan settings is proven. This strategy makes it possible to show the importance of laser point sampling density, but also the diversity of scan angles and their quantitative effect onto error margins.
Development of LiDAR measurements for the German offshore test site

International Nuclear Information System (INIS)

Rettenmeier, A; Kuehn, M; Waechter, M; Rahm, S; Mellinghoff, H; Siegmeier, B; Reeder, L

2008-01-01

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

Science.gov (United States)

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

2014-01-01

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

Science.gov (United States)

Jeffrey S. Evans; Andrew T. Hudak

2007-01-01

One prerequisite to the use of light detection and ranging (LiDAR) across disciplines is differentiating ground from nonground returns. The objective was to automatically and objectively classify points within unclassified LiDAR point clouds, with few model parameters and minimal postprocessing. Presented is an automated method for classifying LiDAR returns as ground...
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 competitive bidding. 25.401 Section 25.401 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Competitive Bidding Procedures for DARS § 25.401...
Analysis of heavy metals concentration in water and sediment in the Hara biosphere reserve, southern Iran.

Science.gov (United States)

Nowrouzi, Mohsen; Mansouri, Borhan; Nabizadeh, Sahar; Pourkhabbaz, Alireza

2014-02-01

This study determined the concentration of heavy metals (Al, Cr, Cu, and Zn) in water and sediments at nine sites in the Hara biosphere reserve of southern Iran during the summer and winter 2010. Determination of Al, Cr, Cu, and Zn in water was carried out by graphite furnace atomic absorption spectrometer (Shimadzu, AA 610s) and in sediment by flame atomic absorption spectrometer (Perkin Elmer, AA3030). Results showed that the heavy metal concentrations in the water samples decreased in the sequence of Zn > Al > Cu > Cr, while in sediment samples were Cr > Zn > Cu > Al. Data analysis indicated that with the exception of Al, there was a Pearson's correlation coefficient between pH and Cu, Zn, and Cr at α = 0.01, 0.05, and 0.001 in sediment (in winter), respectively. There were also significant differences between heavy metals of Cr, Cu, and Zn during the two seasons (p < 0.001) in the water and sediment.
Akselerasi Pertumbuhan Cendana (Santalum album dengan Aplikasi Unsur Hara Makro Ensensial pada Tiga Jenis Tanah

Directory of Open Access Journals (Sweden)

Eny Faridah

2014-01-01

Full Text Available Cendana (Santalum album Linn. merupakan satu dari pilihan penting untuk digunakan dalam program rehabilitasi lahan-lahan kritis di Indonesia. Upaya untuk mempercepat tingkat pertumbuhannya menjadi sangat penting karena pertumbuhannya yang lambat mengganggu tingkat keberhasilan program rehabilitasi hutan. Mempertimbangkan permasalahan tersebut, studi ini dilakukan dengan tujuan mendapatkan formulasi pendekatan untuk mempercepat pertumbuhan cendana melalui aplikasi unsur hara makro esensial yang dibutuhkan cendana pada tiga tipe tanah, dalam bentuk pupuk biologi seperti biofosfo dan biosulfo. Secara spesifik, penelitian ini bertujuan untuk: 1 Pengaruh jenis media tanah (Grumusol (Vertisol, Mediteran (Alfisol dan Regosol (Entisol terhadap pertumbuhan semai cendana, 2 Pengaruh jenis dan dosis pupuk (biosulfo, biofosfo, dan NPK terhadap pertumbuhan semai cendana, dan 3 Pengaruh jenis media tanah, jenis serta dosis pupuk terhadap ketersediaan hara pada tanah dan jaringan daun tanaman. Penelitian dilakukan di Lab. Silvikultur Intensif, Klebengan, Fakultas Kehutanan UGM dengan menggunakan anakan cendana umur enam bulan. Desain Rancangan Acak Lengkap (RAL digunakan dengan perlakuan berupa 3 tipe tanah (Grumusol (Vertisol, Mediterran (Alfisol dan Regosol (Entisol, 3 tipe pupuk (biosulfo, biofosfo, dan NPK, serta 5 dosis pupuk (0; 2,5; 5; 7,5 dan 10 g dengan 5 ulangan untuk setiap unit eksperimen. Parameter yang diukur meliputi tingkat pertumbuhan tanaman (pertumbuhan tinggi & diameter, panjang akar dan tingkat kandungan hara pada tanah dan jaringan daun tanaman. Hasil penelitian menunjukkan bahwa tanah Mediteran secara positif mempengaruhi semua parameter pertumbuhan diikuti oleh Regosol dan Grumusol, sementara aplikasi jenis dan dosis pupuk yang berbeda tidak memberikan pengaruh yang nyata terhadap semua parameter pertumbuhan. Tanah Mediteran memiliki kandungan N dan K paling tinggi dibandingkan dengan jenis tanah Regosol dan Grumusol, sementara tanah
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...
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.
Automated Tree Crown Delineation and Biomass Estimation from Airborne LiDAR data: A Comparison of Statistical and Machine Learning Methods

Science.gov (United States)

Gleason, C. J.; Im, J.

2011-12-01

Airborne LiDAR remote sensing has been used effectively in assessing forest biomass because of its canopy penetrating effects and its ability to accurately describe the canopy surface. Current research in assessing biomass using airborne LiDAR focuses on either the individual tree as a base unit of study or statistical representations of a small aggregation of trees (i.e., plot level), and both methods usually rely on regression against field data to model the relationship between the LiDAR-derived data (e.g., volume) and biomass. This study estimates biomass for mixed forests and coniferous plantations (Picea Abies) within Heiberg Memorial Forest, Tully, NY, at both the plot and individual tree level. Plots are regularly spaced with a radius of 13m, and field data include diameter at breast height (dbh), tree height, and tree species. Field data collection and LiDAR data acquisition were seasonally coincident and both obtained in August of 2010. Resulting point cloud density was >5pts/m2. LiDAR data were processed to provide a canopy height surface, and a combination of watershed segmentation, active contouring, and genetic algorithm optimization was applied to delineate individual trees from the surface. This updated delineation method was shown to be more accurate than traditional watershed segmentation. Once trees had been delineated, four biomass estimation models were applied and compared: support vector regression (SVR), linear mixed effects regression (LME), random forest (RF), and Cubist regression. Candidate variables to be used in modeling were derived from the LiDAR surface, and include metrics of height, width, and volume per delineated tree footprint. Previously published allometric equations provided field estimates of biomass to inform the regressions and calculate their accuracy via leave-one-out cross validation. This study found that for forests such as found in the study area, aggregation of individual trees to form a plot-based estimate of
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.
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.
The Typology of Female Sex Workers in Dar-es-Salaam ...

African Journals Online (AJOL)

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

Science.gov (United States)

Lato, Matthew J.

Natural hazards related to ground movement that directly affect the safety of motorists and highway infrastructure include, but are not limited to, rockfalls, rockslides, debris flows, and landslides. This thesis specifically deals with the evaluation of rockfall hazards through the evaluation of LiDAR data. Light Detection And Ranging (LiDAR) is an imaging technology that can be used to delineate and evaluate geomechanically-controlled hazards. LiDAR has been adopted to conduct hazard evaluations pertaining to rockfall, rock-avalanches, debris flows, and landslides. Characteristics of LiDAR surveying, such as rapid data acquisition rates, mobile data collection, and high data densities, pose problems to traditional CAD or GIS-based mapping methods. New analyses methods, including tools specifically oriented to geomechanical analyses, are needed. The research completed in this thesis supports development of new methods, including improved survey techniques, innovative software workflows, and processing algorithms to aid in the detection and evaluation of geomechanically controlled rockfall hazards. The scientific research conducted between the years of 2006-2010, as presented in this thesis, are divided into five chapters, each of which has been published by or is under review by an international journal. The five research foci are: (i) geomechanical feature extraction and analysis using LiDAR data in active mining environments; (ii) engineered monitoring of rockfall hazards along transportation corridors: using mobile terrestrial LiDAR; (iii) optimization of LiDAR scanning and processing for automated structural evaluation of discontinuities in rockmasses; (iv) location orientation bias when using static LiDAR data for geomechanical analysis; and (v) evaluating roadside rockmasses for rockfall hazards from LiDAR data: optimizing data collection and processing protocols. The research conducted pertaining to this thesis has direct and significant implications with
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
KML-Based Access and Visualization of High Resolution LiDAR Topography

Science.gov (United States)

Crosby, C. J.; Blair, J. L.; Nandigam, V.; Memon, A.; Baru, C.; Arrowsmith, J. R.

2008-12-01

Over the past decade, there has been dramatic growth in the acquisition of LiDAR (Light Detection And Ranging) high-resolution topographic data for earth science studies. Capable of providing digital elevation models (DEMs) more than an order of magnitude higher resolution than those currently available, LiDAR data allow earth scientists to study the processes that contribute to landscape evolution at resolutions not previously possible yet essential for their appropriate representation. These datasets also have significant implications for earth science education and outreach because they provide an accurate representation of landforms and geologic hazards. Unfortunately, the massive volume of data produced by LiDAR mapping technology can be a barrier to their use. To make these data available to a larger user community, we have been exploring the use of Keyhole Markup Language (KML) and Google Earth to provide access to LiDAR data products and visualizations. LiDAR digital elevation models are typically delivered in a tiled format that lends itself well to a KML-based distribution system. For LiDAR datasets hosted in the GEON OpenTopography Portal (www.opentopography.org) we have developed KML files that show the extent of available LiDAR DEMs and provide direct access to the data products. Users interact with these KML files to explore the extent of the available data and are able to select DEMs that correspond to their area of interest. Selection of a tile loads a download that the user can then save locally for analysis in their software of choice. The GEON topography system also has tools available that allow users to generate custom DEMs from LiDAR point cloud data. This system is powerful because it enables users to access massive volumes of raw LiDAR data and to produce DEM products that are optimized to their science applications. We have developed a web service that converts the custom DEM models produced by the system to a hillshade that is delivered to

Advances in animal ecology from 3D ecosystem mapping with LiDAR

Science.gov (United States)

Davies, A.; Asner, G. P.

2015-12-01

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

Directory of Open Access Journals (Sweden)

Josianne Katherine Pereira

2014-08-01

Full Text Available A funcionalidade é uma dimensão crucial da saúde da pessoa idosa. O objetivo desse trabalho é investigar os elementos que participam da construção dos significados da incapacidade para o idoso residente na cidade de Bambuí (MG. Trata-se de uma abordagem qualitativa na qual o modelo de signos, significados e ações foi utilizado na coleta e análise dos dados. Foram entrevistados 57 idosos (30 mulheres; 27 homens com idades entre 61 e 96 anos, cadastrados nas Unidades Básicas de Saúde (SUS da cidade. Os idosos compreendem a funcionalidade/incapacidade (disease, como o "dar conta/não dar conta" ou "dar trabalho" (illness. "Não dar conta" refere-se às perdas funcionais inexoráveis atribuídas à velhice, enquanto "Dar trabalho" a uma condição definitiva que gera dor e sofrimento à pessoa e a quem dela cuida. As maneiras de lidar com o "não dar conta" passam por se conformar, enquanto com o "dar trabalho", orar. A religiosidade e o conformismo podem ajudar nos momentos de crise; mas, revelam a carência de recursos e de alternativas de apoio e de intervenção nos casos mais graves.
Incremental and Enhanced Scanline-Based Segmentation Method for Surface Reconstruction of Sparse LiDAR Data

Directory of Open Access Journals (Sweden)

Weimin Wang

2016-11-01

Full Text Available The segmentation of point clouds is an important aspect of automated processing tasks such as semantic extraction. However, the sparsity and non-uniformity of the point clouds gathered by the popular 3D mobile LiDAR devices pose many challenges for existing segmentation methods. To improve the segmentation results of point clouds from mobile LiDAR devices, we propose an optimized segmentation method based on Scanline Continuity Constraint (SLCC in this work. Unlike conventional scanline-based segmentation methods, SLCC clusters scanlines using the continuity constraints in terms of the distance as well as the direction of two consecutive points. In addition, scanline clusters are agglomerated not only into primitive geometrical shapes but also irregular shapes. Another downside to existing segmentation methods is that they are not capable of incremental processing. This causes unnecessary memory and time consumption for applications that require frame-wise segmentation or when new point clouds are added. In order to address this, we propose an incremental scheme—the Incremental Recursive Segmentation (IRIS, that can be easily applied to any segmentation method. IRIS is achieved by combining the segments of newly added point clouds and the previously segmented results. Furthermore, as an example application, we construct a processing pipeline consisting of plane fitting and surface reconstruction using the segmentation results. Finally, we evaluate the proposed methods on three datasets acquired from a handheld Velodyne HDL-32E LiDAR device. The experimental results verify the efficiency of IRIS for any segmentation method and the advantages of SLCC for processing mobile LiDAR data.
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
Mapping of past stand-level forest disturbances and estimation of time since disturbance using simulated spaceborne LiDAR data

Science.gov (United States)

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

2017-12-01

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

OpenAIRE

Shangpeng Sun; Changying Li; Andrew H. Paterson

2017-01-01

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

Science.gov (United States)

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

2012-01-01

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized
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.
University of Dar es Salaam Library Journal

African Journals Online (AJOL)

University of Dar es Salaam Library Journal. ... PROMOTING ACCESS TO AFRICAN RESEARCH ... These include organization and dissemination of information, library education and training, information technology and its application in ...
Real-time computational photon-counting LiDAR

Science.gov (United States)

Edgar, Matthew; Johnson, Steven; Phillips, David; Padgett, Miles

2018-03-01

The availability of compact, low-cost, and high-speed MEMS-based spatial light modulators has generated widespread interest in alternative sampling strategies for imaging systems utilizing single-pixel detectors. The development of compressed sensing schemes for real-time computational imaging may have promising commercial applications for high-performance detectors, where the availability of focal plane arrays is expensive or otherwise limited. We discuss the research and development of a prototype light detection and ranging (LiDAR) system via direct time of flight, which utilizes a single high-sensitivity photon-counting detector and fast-timing electronics to recover millimeter accuracy three-dimensional images in real time. The development of low-cost real time computational LiDAR systems could have importance for applications in security, defense, and autonomous vehicles.
Using LiDAR to as a Potential Method for Detection Plastics in Water

Science.gov (United States)

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

2010-12-01

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

Science.gov (United States)

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

2013-07-03

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

Science.gov (United States)

Schouten, Henk J; van de Weg, W Eric; Carling, Jason; Khan, Sabaz Ali; McKay, Steven J; van Kaauwen, Martijn P W; Wittenberg, Alexander H J; Koehorst-van Putten, Herma J J; Noordijk, Yolanda; Gao, Zhongshan; Rees, D Jasper G; Van Dyk, Maria M; Jaccoud, Damian; Considine, Michael J; Kilian, Andrzej

2012-03-01

Diversity Arrays Technology (DArT) provides a high-throughput whole-genome genotyping platform for the detection and scoring of hundreds of polymorphic loci without any need for prior sequence information. The work presented here details the development and performance of a DArT genotyping array for apple. This is the first paper on DArT in horticultural trees. Genetic mapping of DArT markers in two mapping populations and their integration with other marker types showed that DArT is a powerful high-throughput method for obtaining accurate and reproducible marker data, despite the low cost per data point. This method appears to be suitable for aligning the genetic maps of different segregating populations. The standard complexity reduction method, based on the methylation-sensitive PstI restriction enzyme, resulted in a high frequency of markers, although there was 52-54% redundancy due to the repeated sampling of highly similar sequences. Sequencing of the marker clones showed that they are significantly enriched for low-copy, genic regions. The genome coverage using the standard method was 55-76%. For improved genome coverage, an alternative complexity reduction method was examined, which resulted in less redundancy and additional segregating markers. The DArT markers proved to be of high quality and were very suitable for genetic mapping at low cost for the apple, providing moderate genome coverage. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11032-011-9579-5) contains supplementary material, which is available to authorized users.
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.
Canopy wake measurements using multiple scanning wind LiDARs

Science.gov (United States)

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

2014-12-01

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

NARCIS (Netherlands)

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

2002-01-01

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

, 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......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...

Geospatial revolution and remote sensing LiDAR in Mesoamerican archaeology

Science.gov (United States)

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

2012-01-01

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

Science.gov (United States)

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

2012-01-01

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

Science.gov (United States)

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

2018-03-01

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

Science.gov (United States)

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

2017-02-01

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

NARCIS (Netherlands)

Schouten, H.J.; Weg, van de W.E.; Carling, J.; Khan, S.A.; McKay, S.J.; Kaauwen, van M.P.W.

2012-01-01

Diversity Arrays Technology (DArT) provides a high-throughput whole-genome genotyping platform for the detection and scoring of hundreds of polymorphic loci without any need for prior sequence information. The work presented here details the development and performance of a DArT genotyping array for
Effect of Tree Phenology on LiDAR Measurement of Mediterranean Forest Structure

Directory of Open Access Journals (Sweden)

William Simonson

2018-04-01

Full Text Available Retrieval of forest biophysical properties using airborne LiDAR is known to differ between leaf-on and leaf-off states of deciduous trees, but much less is understood about the within-season effects of leafing phenology. Here, we compare two LiDAR surveys separated by just six weeks in spring, in order to assess whether LiDAR variables were influenced by canopy changes in Mediterranean mixed-oak woodlands at this time of year. Maximum and, to a slightly lesser extent, mean heights were consistently measured, whether for the evergreen cork oak (Quercus suber or semi-deciduous Algerian oak (Q. canariensis woodlands. Estimates of the standard deviation and skewness of height differed more strongly, especially for Algerian oaks which experienced considerable leaf expansion in the time period covered. Our demonstration of which variables are more or less affected by spring-time leafing phenology has important implications for analyses of both canopy and sub-canopy vegetation layers from LiDAR surveys.
Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry

Directory of Open Access Journals (Sweden)

Zhigang Pan

2015-04-01

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

Science.gov (United States)

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

2013-01-01

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

Science.gov (United States)

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

2018-02-21

Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed for understanding and managing processes involved in the carbon cycle and supporting international policies for climate change mitigation and adaption. Furthermore, these products provide important baseline data for the development of sustainable management strategies to local stakeholders. The use of remote sensing data can provide spatially explicit information of AGB from local to global scales. In this study, we mapped national Mexican forest AGB using satellite remote sensing data and a machine learning approach. We modelled AGB using two scenarios: (1) extensive national forest inventory (NFI), and (2) airborne Light Detection and Ranging (LiDAR) as reference data. Finally, we propagated uncertainties from field measurements to LiDAR-derived AGB and to the national wall-to-wall forest AGB map. The estimated AGB maps (NFI- and LiDAR-calibrated) showed similar goodness-of-fit statistics (R 2 , Root Mean Square Error (RMSE)) at three different scales compared to the independent validation data set. We observed different spatial patterns of AGB in tropical dense forests, where no or limited number of NFI data were available, with higher AGB values in the LiDAR-calibrated map. We estimated much higher uncertainties in the AGB maps based on two-stage up-scaling method (i.e., from field measurements to LiDAR and from LiDAR-based estimates to satellite imagery) compared to the traditional field to satellite up-scaling. By removing LiDAR-based AGB pixels with high uncertainties, it was possible to estimate national forest AGB with similar uncertainties as calibrated with NFI data only. Since LiDAR data can be acquired much faster and for much larger areas compared to field inventory data, LiDAR is attractive for repetitive large scale AGB mapping. In this study, we showed that two-stage up-scaling methods for AGB estimation over large areas need to be analyzed and validated
Estimating forest structural characteristics using the airborne LiDAR scanning system and a near-real time profiling laser system

Science.gov (United States)

Zhao, Kaiguang

LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatially-explicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for real-time remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real-time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real-time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for real-time forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of
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...
University of Dar es Salaam Library Journal - Vol 9, No 1 (2007)

African Journals Online (AJOL)

Gender Analysis Of Electronic Information Resource Use: The Case Of The University Of Dar Es Salaam, Tanzania · EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT DOWNLOAD FULL ... A Bibliometric Study Of Research On Dar Es Salaam Region: 1980 To 2003 · EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT
3D turbulence measurements using three intersecting Doppler LiDAR beams: validation against sonic anemometry

Science.gov (United States)

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

2013-04-01

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

Science.gov (United States)

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

2013-01-01

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

Directory of Open Access Journals (Sweden)

Wei Gong

2015-09-01

Full Text Available The abilities of multispectral LiDAR (MSL as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%–39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image.
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...

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

Science.gov (United States)

Huang, Rongyong; Zheng, Shunyi; Hu, Kun

2018-06-01

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

Directory of Open Access Journals (Sweden)

Wuming Zhang

2016-06-01

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

Science.gov (United States)

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

2017-12-01

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

Science.gov (United States)

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

2012-01-01

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

International Nuclear Information System (INIS)

Bailey, Brian N; Mahaffee, Walter F

2017-01-01

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

Science.gov (United States)

Kopecký, David; Bartoš, Jan; Lukaszewski, Adam J; Baird, James H; Černoch, Vladimír; Kölliker, Roland; Rognli, Odd Arne; Blois, Helene; Caig, Vanessa; Lübberstedt, Thomas; Studer, Bruno; Shaw, Paul; Doležel, Jaroslav; Kilian, Andrzej

2009-01-01

Background Grasses are among the most important and widely cultivated plants on Earth. They provide high quality fodder for livestock, are used for turf and amenity purposes, and play a fundamental role in environment protection. Among cultivated grasses, species within the Festuca-Lolium complex predominate, especially in temperate regions. To facilitate high-throughput genome profiling and genetic mapping within the complex, we have developed a Diversity Arrays Technology (DArT) array for five grass species: F. pratensis, F. arundinacea, F. glaucescens, L. perenne and L. multiflorum. Results The DArTFest array contains 7680 probes derived from methyl-filtered genomic representations. In a first marker discovery experiment performed on 40 genotypes from each species (with the exception of F. glaucescens for which only 7 genotypes were used), we identified 3884 polymorphic markers. The number of DArT markers identified in every single genotype varied from 821 to 1852. To test the usefulness of DArTFest array for physical mapping, DArT markers were assigned to each of the seven chromosomes of F. pratensis using single chromosome substitution lines while recombinants of F. pratensis chromosome 3 were used to allocate the markers to seven chromosome bins. Conclusion The resources developed in this project will facilitate the development of genetic maps in Festuca and Lolium, the analysis on genetic diversity, and the monitoring of the genomic constitution of the Festuca × Lolium hybrids. They will also enable marker-assisted selection for multiple traits or for specific genome regions. PMID:19832973
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.
LOCALIZED SEGMENT BASED PROCESSING FOR AUTOMATIC BUILDING EXTRACTION FROM LiDAR DATA

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G. Parida

2017-05-01

Full Text Available 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.
Multispectral LiDAR Data for Land Cover Classification of Urban Areas

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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.
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.
Serosurvey of antibodies against spotted fever group Rickettsia spp. in horse farms in Northern Paraná, Brazil Soroprevalência de anticorpos contra Rickettsia spp. do grupo febre maculosa em equinos de haras no Norte do Paraná, Brasil

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Katia Tamekuni

2010-12-01

Full Text Available Brazilian spotted fever (BSF is an emerging disease most likely caused by Rickettsia rickettsii. The objective of the present study was to estimate the seroprevalence of BSF rickettsia infections in equines from six horse farms located in Londrina County, Paraná, Southern Brazil. Six owners of horse farms situated in Cambé, Santa Fé, Guaraci and Londrina municipalities participated in the study. All farms were located in areas where BSF has not been reported. A total of 273 horses were sampled and their sera were tested by indirect Immunofluorescence assay (IFA using R. rickettsii and R. parkeri antigens. Titers equal to and greater than 64 were considered positive. Of 273 sera tested, 15 (5.5% reacted to R. rickettsii and 5 (1.8% to R. parkeri. Five out of the six farms studied revealed seropositive animals and seropositivity rate ranged from 0 to 13%. The titers ranged from 64 to 512, and four samples had a titer of 512. Nine animals reacted to R. rickettsii with titers four-fold higher than those for R. parkeri. These results suggest that horses in Northern Paraná may have been exposed to rickettsiae identical or closely related to R. rickettsii.Febre Maculosa Brasileira (FMB é uma doença emergente, sendo Rickettsia rickettsii o seu principal agente etiológico. O objetivo deste estudo foi determinar a soroprevalência de rickettsia do grupo da febre maculosa em equinos de seis haras localizados nos municípios de Cambé, Santa Fé, Guaraci e Londrina. As propriedades eram localizadas na região Norte do Paraná onde casos de FMB ainda não foram diagnosticados. Foram colhidas amostras de sangue de 273 equinos, e os soros foram testados pela RIFI, usando R. rickettsii e R. parkeri como antígenos, considerando-se como positivos títulos >64. Entre 273 soros, 15 (5,5% reagiram contra R. rickettsii e 5 (1,8% para R. parkeri. Cinco de seis haras estudados tinham animais reativos, e a taxa de sororreatividade variou de 0 a 13%. Os t
Anti-diabetic drugs in the private and public sector in Dar es Salaam ...

African Journals Online (AJOL)

Objectives: To compare availability, cost, affordability and sources of anti-diabetic drugs between private and public health facilities in Dar es Salaam, Tanzania. Design: Cross sectional descriptive study. Setting: Diabetic clinics in private and public health facilities in Dar es Salaam, Tanzania. Subjects: Eighty patients ...
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...
Parallel Landscape Driven Data Reduction & Spatial Interpolation Algorithm for Big LiDAR Data

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

Science.gov (United States)

Chirayath, Ved

2018-01-01

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

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Chuanfa Chen

2015-09-01

Full Text Available Light detection and ranging (LiDAR technique is currently one of the most important tools for collecting elevation points with a high density in the context of digital elevation model (DEM construction. However, the high density data always leads to serious time and memory consumption problems in data processing. In this paper, we have developed a thin plate spline (TPS-based feature-preserving (TPS-F method for LiDAR-derived ground data reduction by selecting a certain amount of significant terrain points and by extracting geomorphological features from the raw dataset to maintain the accuracy of constructed DEMs as high as possible, while maximally keeping terrain features. We employed four study sites with different topographies (i.e., flat, undulating, hilly and mountainous terrains to analyze the performance of TPS-F for LiDAR data reduction in the context of DEM construction. These results were compared with those of the TPS-based algorithm without features (TPS-W and two classical data selection methods including maximum z-tolerance (Max-Z and the random method. Results show that irrespective of terrain characteristic, the two versions of TPS-based approaches (i.e., TPS-F and TPS-W are always more accurate than the classical methods in terms of error range and root means square error. Moreover, in terms of streamline matching rate (SMR, TPS-F has a better ability of preserving geomorphological features, especially for the mountainous terrain. For example, the average SMR of TPS-F is 89.2% in the mountainous area, while those of TPS-W, max-Z and the random method are 56.6%, 34.7% and 35.3%, respectively.

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

Science.gov (United States)

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

2016-01-01

The conventional approach to LiDAR-based forest inventory modeling depends on field sample data from fixed-radius plots (FRP). Because FRP sampling is cost intensive, combining variable-radius plot (VRP) sampling and LiDAR data has the potential to improve inventory efficiency. The overarching goal of this study was to evaluate the integration of LiDAR and VRP data....
Generalised small signal analysis of a DAR /Double Avalanche Region/ IMPATT diode

Science.gov (United States)

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

1982-06-01

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

Science.gov (United States)

2009-02-01

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

Directory of Open Access Journals (Sweden)

Studer Bruno

2009-10-01

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

Science.gov (United States)

2012-09-01

37 D. MASK CREATION .......................................................................................39 viii 1. LiDAR-based Masks...in Quick Terrain Modeler 2. WorldView-2 The image used in this project was collected by WorldView-2 on November 8, 2011 at Zulu time 19:34:42...OBSERVATIONS A. PROCESS OVERVIEW The focus of this thesis was to create a robust technique for fusing LiDAR and spectral imagery for creation of a
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
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...
Surface characteristics modeling and performance evaluation of urban building materials using LiDAR data.

Science.gov (United States)

Li, Xiaolu; Liang, Yu

2015-05-20

Analysis of light detection and ranging (LiDAR) intensity data to extract surface features is of great interest in remote sensing research. One potential application of LiDAR intensity data is target classification. A new bidirectional reflectance distribution function (BRDF) model is derived for target characterization of rough and smooth surfaces. Based on the geometry of our coaxial full-waveform LiDAR system, the integration method is improved through coordinate transformation to establish the relationship between the BRDF model and intensity data of LiDAR. A series of experiments using typical urban building materials are implemented to validate the proposed BRDF model and integration method. The fitting results show that three parameters extracted from the proposed BRDF model can distinguish the urban building materials from perspectives of roughness, specular reflectance, and diffuse reflectance. A comprehensive analysis of these parameters will help characterize surface features in a physically rigorous manner.
Improving low-relief coastal LiDAR DEMs with hydro-conditioning of fine-scale and artificial drainages

Directory of Open Access Journals (Sweden)

Thomas Richard Allen

2015-11-01

Full Text Available Improvements in Light Detection and Ranging (LiDAR technology and spatial analysis of high-resolution digital elevation models (DEMs have advanced the accuracy and diversity of applications for coastal hazards and natural resources management. This article presents a concise synthesis of LiDAR analysis for coastal flooding and management applications in low-relief coastal plains and a case study demonstration of a new, efficient drainage mapping algorithm. The impetus for these LiDAR applications follows historic flooding from Hurricane Floyd in 1999, after which the State of North Carolina and the Federal Emergency Management Agency undertook extensive LiDAR data acquisition and technological developments for high-resolution floodplain mapping. An efficient algorithm is outlined for hydro-conditioning bare earth LiDAR DEMs using available US Geological Survey National Hydrography Dataset canal and ditch vectors. The methodology is illustrated in Moyock, North Carolina, for refinement of hydro-conditioning by combines pre-existing bare earth DEMs with spatial analysis of LiDAR point clouds in segmented and buffered ditch and canal networks. The methodology produces improved maps of fine-scale drainage, reduced omission of areal flood inundation, and subwatershed delineations that typify heavily ditched and canalled drainage areas. These preliminary results illustrate the capability of the technique to improve the representation of ditches in DEMs as well as subsequent flow and inundation modeling that could spur further research on low-relief coastal LiDAR applications.
Application of LiDAR to hydrologic flux estimation in Australian eucalypt forests (Invited)

Science.gov (United States)

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

2013-12-01

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

OpenAIRE

Yin, Peng; He, Yuqing; Xu, Lingyun; Peng, Yan; Han, Jianda; Xu, Weiliang

2018-01-01

Loop Closure Detection (LCD) is the essential module in the simultaneous localization and mapping (SLAM) task. In the current appearance-based SLAM methods, the visual inputs are usually affected by illumination, appearance and viewpoints changes. Comparing to the visual inputs, with the active property, light detection and ranging (LiDAR) based point-cloud inputs are invariant to the illumination and appearance changes. In this paper, we extract 3D voxel maps and 2D top view maps from LiDAR ...
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

Perennial ryegrass is the principal forage grass species used in temperate agriculture. In recent years, significant efforts have been made to develop molecular marker strategies to allow cost-effective characterization of a large number of loci simultaneously. One such strategy involves using DAr......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...
Utilizing LiDAR Datasets From Experimental Watersheds to Advance Ecohydrological Understanding in Seasonally Snow-Covered Forests

Science.gov (United States)

Harpold, A. A.; Broxton, P. D.; Guo, Q.; Barlage, M. J.; Gochis, D. J.

2014-12-01

The Western U.S. is strongly reliant on snowmelt from forested areas for ecosystem services and downstream populations. The ability to manage water resources from snow-covered forests faces major challenges from drought, disturbance, and regional changes in climate. An exciting avenue for improving ecohydrological process understanding is Light Detection and Ranging (LiDAR) because the technology simultaneously observes topography, forest properties, and snow/ice at high-resolution (100 km2). The availability and quality of LiDAR datasets is increasing rapidly, however they remain under-utilized for process-based ecohydrology investigations. This presentation will illustrate how LiDAR datasets from the Critical Zone Observatory (CZO) network have been applied to advance ecohydrological understanding through direct empirical analysis, as well as model parameterization and verification. Direct analysis of the datasets has proved fruitful for pre- and post-disturbance snow distribution estimates and interpreting in-situ snow depth measurements across sites. In addition, we illustrate the potential value of LiDAR to parameterize and verify of physical models with two examples. First, we use LiDAR to parameterize a land surface model, Noah multi-parameterization (Noah-MP), to investigate the sensitivity of modeled water and energy fluxes to high-resolution forest information. Second, we present a Snow Physics and Laser Mapping (SnowPALM) model that is parameterized with LiDAR information at its native 1-m scale. Both modeling studies demonstrate the value of LiDAR for representing processes with greater fidelity. More importantly, the increased model fidelity led to different estimates of water and energy fluxes at larger, watershed scales. Creating a network of experimental watersheds with LiDAR datasets offers the potential to test theories and models in previously unexplored ways.
Adolescent Girls with illegally Induced Abortion in Dar es Salaam

DEFF Research Database (Denmark)

Rasch, V; Silberschmidt, Margrethe; Mchumvu, Y

2000-01-01

that gave them the right to seek family planning services and in practice these services are not being provided. There is a need for youth-friendly family planning services and to make abortion safe and legal, in order to reduce unwanted pregnancies and abortion-related complications and deaths among......This article reports on a study of induced abortion among adolescent girls in Dar es Salaam, Tanzania, who were admitted to a district hospital in Dar es Salaam because of an illegally induced abortion in 1997. In the quantitative part of the study, 197 teenage girls (aged 14-19) were asked...
The OptD-multi method in LiDAR processing

International Nuclear Information System (INIS)

Błaszczak-Bąk, Wioleta; Sobieraj-Żłobińska, Anna; Kowalik, Michał

2017-01-01

New and constantly developing technology for acquiring spatial data, such as LiDAR (light detection and ranging), is a source for large volume of data. However, such amount of data is not always needed for developing the most popular LiDAR products: digital terrain model (DTM) or digital surface model. Therefore, in many cases, the number of contained points are reduced in the pre-processing stage. The degree of reduction is determined by the algorithm used, which should enable the user to obtain a dataset appropriate and optimal for the planned purpose. The aim of this article is to propose a new Optimum Dataset method (OptD method) in the processing of LiDAR point clouds. The OptD method can reduce the number of points in a dataset for the specified optimization criteria concerning the characteristics of generated DTM. The OptD method can be used in two variants: OptD-single (one criterion for optimization) and OptD-multi (two or more optimization criteria). The OptD-single method has been thoroughly tested and presented by Błaszczak-Bąk (2016 Acta Geodyn. Geomater . 13/4 379–86). In this paper the authors discussed the OptD-multi method. (paper)
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...... of Greenland and the effect of the number of scenes used to generate the ASTER GDEM as well as relief are associated with the GDEM accuracy....
Quantifying Wave Breaking Shape and Type in the Surf-Zone Using LiDAR

Science.gov (United States)

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

2017-12-01

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

Science.gov (United States)

Hedrick, A.; Marshall, H.-P.; Winstral, A.; Elder, K.; Yueh, S.; Cline, D.

2014-06-01

Repeated Light Detection and Ranging (LiDAR) surveys are quickly becoming the de facto method for measuring spatial variability of montane snowpacks at high resolution. This study examines the potential of a 750 km2 LiDAR-derived dataset of snow depths, collected during the 2007 northern Colorado Cold Lands Processes Experiment (CLPX-2), as a validation source for an operational hydrologic snow model. The SNOw Data Assimilation System (SNODAS) model framework, operated by the US National Weather Service, combines a physically-based energy-and-mass-balance snow model with satellite, airborne and automated ground-based observations to provide daily estimates of snowpack properties at nominally 1 km resolution over the coterminous United States. Independent validation data is scarce due to the assimilating nature of SNODAS, compelling the need for an independent validation dataset with substantial geographic coverage. Within twelve distinctive 500 m × 500 m study areas located throughout the survey swath, ground crews performed approximately 600 manual snow depth measurements during each of the CLPX-2 LiDAR acquisitions. This supplied a dataset for constraining the uncertainty of upscaled LiDAR estimates of snow depth at the 1 km SNODAS resolution, resulting in a root-mean-square difference of 13 cm. Upscaled LiDAR snow depths were then compared to the SNODAS-estimates over the entire study area for the dates of the LiDAR flights. The remotely-sensed snow depths provided a more spatially continuous comparison dataset and agreed more closely to the model estimates than that of the in situ measurements alone. Finally, the results revealed three distinct areas where the differences between LiDAR observations and SNODAS estimates were most drastic, suggesting natural processes specific to these regions as causal influences on model uncertainty.

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

to accept screening in comparison with women who had five or more children (ORs 3.21). Finally, knowledge of cervical cancer and awareness of the existing screening program were also associated with increased acceptance rates (ORs of 5.90 and 4.20). CONCLUSION: There are identifiable subgroups where...... 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......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...
Key events and their effects on cycling behaviour in Dar-es-Salaam : abstract + powerpoint

OpenAIRE

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

2012-01-01

The paper explores key events and investigates their effects on cycling behaviour in the city of Dar-es-Salaam, Tanzania. The objective of the study is to identify specific key events during a person’s life course with a significant effect on change of travel behaviour towards cycling in relation to stage of change. Stage of change is a key construct of the transtheoretical model of behaviour change that defines behavioural readiness (intentions and actions) into six distinct categories (i.e....
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...
Dar clase en el aula. Insidie e risorse nell’insegnamento di lingue affini

Directory of Open Access Journals (Sweden)

Maria Isabella Mininni

2014-06-01

Full Text Available Dar clase en el aula. Risks and opportunities in the teaching of related languages. Spanish, being near to Italian, is often seen as a language easy to learn for Italian native speakers. This kind of prejudice perpetuated by wrong and trivial evaluations is probably the first obstacle that a teacher must overcome in her work; on the other hand, media, especially music and cinema, have made Spanish a so widespread and known language, that the interest of young generations in it has grown rapidly, while only a few years ago it was even excluded, in Italy, from public education. This work proposes some reflections on the methodological frameworks used at present in the teaching of Spanish Language in Italian Secondary School, through a reasoned research conducted with the trainees of the T.F.A., working on recent publications (methods, courses, manuals and on original documents that a teacher of Spanish as a foreign language has at her disposition, with a special attention for the discussion of students’ elaborations of single didactical unities.
Origin of enhanced vibrational excitation in N2 by electron impact in the 15--35 eV region

International Nuclear Information System (INIS)

Dehmer, J.L.; Siegel, J.; Welch, J.; Dill, D.

1980-01-01

The authors calculate the integrated vibrational excitation cross section for e-N 2 scattering in the interval 0 --50 eV using the continuum multiple-scattering model with the Hara exchange approximation. Resonant enhancement is observed at 2.4 eV owing to the well-known π/sub g/ shape resonance. In addition, however, enhanced vibrational excitation is found centered at approx.26 eV, arising from a broad shape resonance in the sigma/sub u/ channel. The authors propose this one-electron feature as the main source of the enhanced vibrational excitation observed by Pavlovic et al. in the 15--35 eV region
Automatic 3d Building Model Generations with Airborne LiDAR Data

Science.gov (United States)

Yastikli, N.; Cetin, Z.

2017-11-01

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

Directory of Open Access Journals (Sweden)

N. Yastikli

2017-11-01

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

NARCIS (Netherlands)

Wittenberg, A.H.J.; Lee, van der T.A.J.; Cayla, C.; Kilian, A.; Visser, R.G.F.; Schouten, H.J.

2005-01-01

Diversity Arrays Technology (DArT) is a microarray-based DNA marker technique for genome-wide discovery and genotyping of genetic variation. DArT allows simultaneous scoring of hundreds of restriction site based polymorphisms between genotypes and does not require DNA sequence information or
Rubén Darío y la pintura Principio ekfrástico y sinestesia // Rubén Darío and painting: Ekphrastic principle and synesthesia

Directory of Open Access Journals (Sweden)

Alvaro Salvador

2016-12-01

Full Text Available The article examines the relationships between literature and painting in the works of Rubén Darío. The issue is seen in the context of modernis synesthesia, which was strongly present in the literary ideology of the modernist discourse, and it is analyzed with the help of the theories of ekphrasis of Murray Krieger. In Darío’s canonical works painting plays an important role, both in the form of literary references, and the so called “transpositions of art”, in its intent to create a total art.
Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

Science.gov (United States)

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

2015-12-01

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

Science.gov (United States)

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

2015-04-01

Taiwan is subject to 3.4 landfall typhoons each year in average, generally occurring in the third quarter of every year (July-September). Understanding of boundary-layer turbulence characteristics of a typhoon is needed to ensure the safety of both onshore and offshore wind turbines used for power generation. In this study, a floating LiDAR (Light Detection and Ranging) was deployed in a harbor to collect data of wind turbulence, atmospheric pressure, and temperature in three typhoon events (Matmo typhoon, Soulik typhoon, Trami typhoon). Data collected from the floating LiDAR and from meteorological stations located at Taipei, Taichung and Kaohsiung are adopted to analyse the wind turbulence characteristics in the three typhoon events. The measurement results show that the maximum 10-min average wind speed measured with the floating LiDAR is up to 24 m/s at a height of 200 m. Compared with other normal days, the turbulence intensity is lower in the three typhoon events where the wind speed has a rapid increase. Changes of wind direction take place clearly as the typhoons cross Taiwan from East to West. Within the crossing intervals, the vertical momentum flux is observed to have a significant pattern with both upward and downward propagating waves which are relevant to the flow structure of the typhoons.
Quantifying spatial distribution of snow depth errors from LiDAR using Random Forests

Science.gov (United States)

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

2013-12-01

There is increasing need to characterize the distribution of snow in complex terrain using remote sensing approaches, especially in isolated mountainous regions that are often water-limited, the principal source of terrestrial freshwater, and sensitive to climatic shifts and variations. We apply intensive topographic surveys, multi-temporal LiDAR, and Random Forest modeling to quantify snow volume and characterize associated errors across seven land cover types in a semi-arid mountainous catchment at a 1 and 4 m spatial resolution. The LiDAR-based estimates of both snow-off surface topology and snow depths were validated against ground-based measurements across the catchment. Comparison of LiDAR-derived snow depths to manual snow depth surveys revealed that LiDAR based estimates were more accurate in areas of low lying vegetation such as shrubs (RMSE = 0.14 m) as compared to areas consisting of tree cover (RMSE = 0.20-0.35 m). The highest errors were found along the edge of conifer forests (RMSE = 0.35 m), however a second conifer transect outside the catchment had much lower errors (RMSE = 0.21 m). This difference is attributed to the wind exposure of the first site that led to highly variable snow depths at short spatial distances. The Random Forest modeled errors deviated from the field measured errors with a RMSE of 0.09-0.34 m across the different cover types. Results show that snow drifts, which are important for maintaining spring and summer stream flows and establishing and sustaining water-limited plant species, contained 30 × 5-6% of the snow volume while only occupying 10% of the catchment area similar to findings by prior physically-based modeling approaches. This study demonstrates the potential utility of combining multi-temporal LiDAR with Random Forest modeling to quantify the distribution of snow depth with a reasonable degree of accuracy. Future work could explore the utility of Terrestrial LiDAR Scanners to produce validation of snow-on surface
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.
Land Cover Segmentation of Airborne LiDAR Data Using Stochastic Atrous Network

Directory of Open Access Journals (Sweden)

Hasan Asy’ari Arief

2018-06-01

Full Text Available Inspired by the success of deep learning techniques in dense-label prediction and the increasing availability of high precision airborne light detection and ranging (LiDAR data, we present a research process that compares a collection of well-proven semantic segmentation architectures based on the deep learning approach. Our investigation concludes with the proposition of some novel deep learning architectures for generating detailed land resource maps by employing a semantic segmentation approach. The contribution of our work is threefold. (1 First, we implement the multiclass version of the intersection-over-union (IoU loss function that contributes to handling highly imbalanced datasets and preventing overfitting. (2 Thereafter, we propose a novel deep learning architecture integrating the deep atrous network architecture with the stochastic depth approach for speeding up the learning process, and impose a regularization effect. (3 Finally, we introduce an early fusion deep layer that combines image-based and LiDAR-derived features. In a benchmark study carried out using the Follo 2014 LiDAR data and the NIBIO AR5 land resources dataset, we compare our proposals to other deep learning architectures. A quantitative comparison shows that our best proposal provides more than 5% relative improvement in terms of mean intersection-over-union over the atrous network, providing a basis for a more frequent and improved use of LiDAR data for automatic land cover segmentation.
LESTO: an Open Source GIS-based toolbox for LiDAR analysis

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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
Development of digital subtraction system DAR-1200

International Nuclear Information System (INIS)

Kawai, Masumi; Shimizu, Yasumitsu; Ozaki, Takeshi; Sawada, Hiroshi; Uzuyama, Kazuhiro; Nishioka, Hiroyuki

1989-01-01

Digital subtraction angiography (DSA) has been of widespread use clinically, and it has attracted considerable attention in angiographic examination today. The merits of Shimadzu high resolution digital subtraction system DAR-1200 are reported in this paper. Furthermore, the principle and clinical usefullness of a new method of DSA called the Peak-Hold DSA are explained especially in details. (author)
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
The Extraction of Vegetation Points from LiDAR Using 3D Fractal Dimension Analyses

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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.
Antibiogram of E. coli serotypes isolated from children aged under ...

African Journals Online (AJOL)

Antibiogram of E. coli serotypes isolated from children aged under five with acute diarrhea in Bahir Dar town. Ayrikim Adugna1, Mulugeta Kibret1, Bayeh Abera2, Endalkachew Nibret1, Melaku Adal1. 1. Department of Biology, Science College, Bahir Dar University. 2. Department of Microbiology, Parasitology and ...
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.

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.
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.
Object Tracking with LiDAR: Monitoring Taxiing and Landing Aircraft

Directory of Open Access Journals (Sweden)

Zoltan Koppanyi

2018-02-01

Full Text Available Mobile light detection and ranging (LiDAR sensors used in car navigation and robotics, such as the Velodyne’s VLP-16 and HDL-32E, allow for sensing the surroundings of the platform with high temporal resolution to detect obstacles, tracking objects and support path planning. This study investigates the feasibility of using LiDAR sensors for tracking taxiing or landing aircraft close to the ground to improve airport safety. A prototype system was developed and installed at an airfield to capture point clouds to monitor aircraft operations. One of the challenges of accurate object tracking using the Velodyne sensors is the relatively small vertical field of view (30°, 41.3° and angular resolution (1.33°, 2°, resulting in a small number of points of the tracked object. The point density decreases with the object–sensor distance, and is already sparse at a moderate range of 30–40 m. The paper introduces our model-based tracking algorithms, including volume minimization and cube trajectories, to address the optimal estimation of object motion and tracking based on sparse point clouds. Using a network of sensors, multiple tests were conducted at an airport to assess the performance of the demonstration system and the algorithms developed. The investigation was focused on monitoring small aircraft moving on runways and taxiways, and the results indicate less than 0.7 m/s and 17 cm velocity and positioning accuracy achieved, respectively. Overall, based on our findings, this technology is promising not only for aircraft monitoring but for airport applications.
Intussusception in children seen at Muhimbili National Hospital, Dar ...

African Journals Online (AJOL)

Intussusception in children seen at Muhimbili National Hospital, Dar es salaam. ... its magnitude of concern and any seasonal variation in our environment. ... majority of the children present late, >48 hours from the onset of symptoms and ...
Airborne LiDAR reflective linear feature extraction for strip adjustment and horizontal accuracy determination : executive summary.

Science.gov (United States)

2009-02-01

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

Directory of Open Access Journals (Sweden)

Javier Guerreo Barrón

1999-01-01

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

Science.gov (United States)

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

2017-11-01

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

Science.gov (United States)

Chen, Guoliang; Liu, Xingmei; Brookes, Philip C; Xu, Jianming

2015-01-01

The identification of plants with high arsenic hyperaccumulating efficiency from water is required to ensure the successful application of phytoremediation technology. Five dominant submerged plant species (Vallisneria natans (Lour.) Hara., Potamageton crispus L., Myriophyllum spicatum L., Ceratophyllum demersum L. and Hydrilla verticillata (L.f.) Royle) in China were used to determine their potential to remove As from contaminated water. V. natans had the highest accumulation of As among them. The characteristics of As accumulation, transformation and the effect of phosphate on As accumulation in V. natans were then further studied. The growth of V. natans was not inhibited even when the As concentration reached 2.0 mg L(-1). After 21 d of As treatment, the bioconcentration factor (BCF) reached 1300. The As concentration in the environment and exposure time are major factors controlling the As concentration in V. natans. After being absorbed, As(V) is efficiently reduced to As(III) in plants. The synthesis of non-enzymic antioxidants may play an important role under As stress and increase As detoxication. In addition, As(V) uptake by V. natans was negatively correlated with phosphate (P) uptake when P was sufficiently supplied. As(V) is probably taken up via P transporters in V. natans.
Timely binding of IHF and Fis to DARS2 regulates ATP–DnaA production and replication initiation

Science.gov (United States)

Kasho, Kazutoshi; Fujimitsu, Kazuyuki; Matoba, Toshihiro; Oshima, Taku; Katayama, Tsutomu

2014-01-01

In Escherichia coli, the ATP-bound form of DnaA (ATP–DnaA) promotes replication initiation. During replication, the bound ATP is hydrolyzed to ADP to yield the ADP-bound form (ADP–DnaA), which is inactive for initiation. The chromosomal site DARS2 facilitates the regeneration of ATP–DnaA by catalyzing nucleotide exchange between free ATP and ADP bound to DnaA. However, the regulatory mechanisms governing this exchange reaction are unclear. Here, using in vitro reconstituted experiments, we show that two nucleoid-associated proteins, IHF and Fis, bind site-specifically to DARS2 to activate coordinately the exchange reaction. The regenerated ATP–DnaA was fully active in replication initiation and underwent DnaA–ATP hydrolysis. ADP–DnaA formed heteromultimeric complexes with IHF and Fis on DARS2, and underwent nucleotide dissociation more efficiently than ATP–DnaA. Consistently, mutant analyses demonstrated that specific binding of IHF and Fis to DARS2 stimulates the formation of ATP–DnaA production, thereby promoting timely initiation. Moreover, we show that IHF–DARS2 binding is temporally regulated during the cell cycle, whereas Fis only binds to DARS2 in exponentially growing cells. These results elucidate the regulation of ATP–DnaA and replication initiation in coordination with the cell cycle and growth phase. PMID:25378325
Timely binding of IHF and Fis to DARS2 regulates ATP-DnaA production and replication initiation.

Science.gov (United States)

Kasho, Kazutoshi; Fujimitsu, Kazuyuki; Matoba, Toshihiro; Oshima, Taku; Katayama, Tsutomu

2014-12-01

In Escherichia coli, the ATP-bound form of DnaA (ATP-DnaA) promotes replication initiation. During replication, the bound ATP is hydrolyzed to ADP to yield the ADP-bound form (ADP-DnaA), which is inactive for initiation. The chromosomal site DARS2 facilitates the regeneration of ATP-DnaA by catalyzing nucleotide exchange between free ATP and ADP bound to DnaA. However, the regulatory mechanisms governing this exchange reaction are unclear. Here, using in vitro reconstituted experiments, we show that two nucleoid-associated proteins, IHF and Fis, bind site-specifically to DARS2 to activate coordinately the exchange reaction. The regenerated ATP-DnaA was fully active in replication initiation and underwent DnaA-ATP hydrolysis. ADP-DnaA formed heteromultimeric complexes with IHF and Fis on DARS2, and underwent nucleotide dissociation more efficiently than ATP-DnaA. Consistently, mutant analyses demonstrated that specific binding of IHF and Fis to DARS2 stimulates the formation of ATP-DnaA production, thereby promoting timely initiation. Moreover, we show that IHF-DARS2 binding is temporally regulated during the cell cycle, whereas Fis only binds to DARS2 in exponentially growing cells. These results elucidate the regulation of ATP-DnaA and replication initiation in coordination with the cell cycle and growth phase. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Real-time surveillance system for marine environment based on HLIF LiDAR

Science.gov (United States)

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

2017-10-01

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

Science.gov (United States)

Acharjee, Partha Pratim

Airborne light detection and ranging (LiDAR) can generate co-registered elevation and intensity map over large terrain. The co-registered 3D map and intensity information can be used efficiently for different feature extraction application. In this dissertation, we developed two algorithms for feature extraction, and usages of features for practical applications. One of the developed algorithms can map still and flowing waterbody features, and another one can extract building feature and estimate solar potential on rooftops and facades. Remote sensing capabilities, distinguishing characteristics of laser returns from water surface and specific data collection procedures provide LiDAR data an edge in this application domain. Furthermore, water surface mapping solutions must work on extremely large datasets, from a thousand square miles, to hundreds of thousands of square miles. National and state-wide map generation/upgradation and hydro-flattening of LiDAR data for many other applications are two leading needs of water surface mapping. These call for as much automation as possible. Researchers have developed many semi-automated algorithms using multiple semi-automated tools and human interventions. This reported work describes a consolidated algorithm and toolbox developed for large scale, automated water surface mapping. Geometric features such as flatness of water surface, higher elevation change in water-land interface and, optical properties such as dropouts caused by specular reflection, bimodal intensity distributions were some of the linear LiDAR features exploited for water surface mapping. Large-scale data handling capabilities are incorporated by automated and intelligent windowing, by resolving boundary issues and integrating all results to a single output. This whole algorithm is developed as an ArcGIS toolbox using Python libraries. Testing and validation are performed on a large datasets to determine the effectiveness of the toolbox and results are
Identification of four Drosophila allatostatins as the cognate ligands for the Drosophila orphan receptor DAR-2

DEFF Research Database (Denmark)

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

2001-01-01

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

African Journals Online (AJOL)

admin

liquid waste management practices of the community; to assess the .... Logistic regression was performed to assess the impact of a number of factors on the .... the ever-growing Bahir Dar Town with modern buildings using flush toilets will ...
Coastal and tidal landform detection from high resolution topobathymetric LiDAR data

DEFF Research Database (Denmark)

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

-resolution mapping of these land-water transition zones. We have carried out topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage. Detailed digital elevation models (DEMs) with a grid...... to tides. Furthermore, we demonstrate the potential of morphometric analysis on high-resolution topobathymetric LiDAR data for automatic identification, characterisation and classification of different landforms present in coastal land-water transition zones. Acknowledgements This work was funded...
Development and validation of the Dimensional Anhedonia Rating Scale (DARS) in a community sample and individuals with major depression.

Science.gov (United States)

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

2015-09-30

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

Science.gov (United States)

Cook, Bruce D.; Asner, Gregory P.

2010-01-01

This slide presentation reviews the use of Visible ShortWave InfraRed (VSWIR) Imaging Spectrometer and LiDAR to study ecosystem structure, biomass and canopy diversity. It is shown that the biophysical data from LiDAR and biochemical information from hyperspectral remote sensing provides complementary data for: (1) describing spatial patterns of vegetation and biodiversity, (2) characterizing relationships between ecosystem form and function, and (3) detecting natural and human induced change that affects the biogeochemical cycles.
Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale

Science.gov (United States)

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

2013-01-01

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

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Rubén Martínez Marín

2013-01-01

Full Text Available During the last years, in many developed countries, administrations and private companies have devoted considerable amounts of money to obtain mapping data using airborne LiDAR. For many civil activities, we can take advantage of it, since those data are available with no cost. Some important questions arise: Are those data good enough to be used for determining the heights of the civil constructions with the accuracy we need in some civil work? What accuracy can we expect when using low-density LiDAR data (0.5 pts/m2? In order to answer those questions, we have developed a specific methodology based on establishing a set of control points on the top of several constructions and calculating the elevation of each one using postprocessing GPS. Those results have been taken as correct values and the comparison between those values and the elevations obtained, assigning values to the control points by the interpolation of the LiDAR dataset, has been carried out. This paper shows the results obtained using low-density airborne LiDAR data and the accuracy obtained. Results have shown that LiDAR can be accurate enough (10–25 cm to determine the height of civil constructions and apply those data in many civil engineering activities.

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

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

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

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

2017-01-01

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

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

2015-08-01

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

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

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Shaun R. Levick

2016-05-01

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

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

2016-04-01

Land-water transition zones, like e.g. coastal and fluvial environments, are valuable ecosystems which are often characterised by high biodiversity and geodiversity. However, often these land-water transition zones are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. Combining vessel borne shallow water multibeam echosounder (MBES) surveys ,to cover the subtidal coastal areas and the river channel areas, with airborne topobathymetric light detection and ranging (LiDAR) surveys, to cover the intertidal and supratidal coastal areas and the river floodplain areas, potentially enables full-coverage and high-resolution mapping in these challenging environments. We have carried out MBES and topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage, and in the Ribe Vesterå, a fluvial environment in the Ribe Å river catchment discharging into the Knudedyb tidal basin. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the MBES and the LiDAR point clouds, which both have point densities in the order of 20 points/m2. Morphometric analyses of the DEMs enabled the identification and mapping of the different landforms within the coastal and fluvial environments. Hereby, we demonstrate that vessel borne MBES and airborne topobathymetric LiDAR, here in combination, are promising tools for seamless mapping across land-water transition zones as well as for the quantification of a range of landforms at landscape scale in different land-water transition zone environments. Hence, we demonstrate the potential for mapping and quantifying geomorphological diversity, which is one of the main components of geodiversity and a prerequisite for assessing geoheritage. Acknowledgements This work was funded by the Danish Council for
Effects of LiDAR point density and landscape context on the retrieval of urban forest biomass

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Singh, K. K.; Chen, G.; McCarter, J. B.; Meentemeyer, R. K.

2014-12-01

Light Detection and Ranging (LiDAR), as an alternative to conventional optical remote sensing, is being increasingly used to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and better data accuracies, which however pose challenges to the procurement and processing of LiDAR data for large-area assessments. Reducing point density cuts data acquisition costs and overcome computational challenges for broad-scale forest management. However, how does that impact the accuracy of biomass estimation in an urban environment containing a great level of anthropogenic disturbances? The main goal of this study is to evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing regions of Charlotte, North Carolina, USA. We used multiple linear regression to establish the statistical relationship between field-measured biomass and predictor variables (PVs) derived from LiDAR point clouds with varying densities. We compared the estimation accuracies between the general Urban Forest models (no discrimination of forest type) and the Forest Type models (evergreen, deciduous, and mixed), which was followed by quantifying the degree to which landscape context influenced biomass estimation. The explained biomass variance of Urban Forest models, adjusted R2, was fairly consistent across the reduced point densities with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models using two representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, signifying the distance impact of development on biomass estimation. Our evaluation
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.
Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests

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

2017-10-01

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

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Beatriz Colombi

1996-11-01

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

Science.gov (United States)

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

2013-01-01

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

African Journals Online (AJOL)

Patient Satisfaction At The Muhimbili National Hospital In Dar Es Salaam, Tanzania. ... staffpatient relationship ethos, in which the patient is a viewed as a customer. Keywords: patient satisfaction, reform, Muhimbili National Hospital, referral ...
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...
Evaluation of Landslide Mapping Techniques and LiDAR-based Conditioning Factors

Science.gov (United States)

Mahalingam, R.; Olsen, M. J.

2014-12-01

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

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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.
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.
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

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...
PENGARUH TINDAKAN KONSERVASI TANAH TERHADAP ALIRAN PERMUKAAN, EROSI, KEHILANGAN HARA DAN PENGHASILAN PADA USAHA TANI KENTANG DAN KUBIS (Effect of Coil and Water Conservation Practices on Runoff, Erosion, Nutrient Loss and Farmer Income of Potato

Directory of Open Access Journals (Sweden)

Umi Baroroh Lili Utami

2001-08-01

Full Text Available ABSTRAK Laju erosi yang terjadi di dataran tinggi Dieng, Jawa Tengah sangat tinggi karena pertanian yang dominan adalah sayuran, dan umumnya petani tidak melaksanakan teknik konservasi tanah dan air secara benar. Karena itu, perlu dilakukan penelitian untuk mencari tindakan konservasi tanah yang memadai agar dapat menekan erosi dan aliran permukaan, kehilangan hara dan meningkatkan penghasilan pada usaha tani kentang (Solanum toberosum L dan kubis (Brassica oleracea l. Penelitian ini bertujuan untuk mengkaji pengaruh tindakan konservasi tanah terhadap aliran permukaan, erosi, kehilangan hara, dan penghasilan sehingga diharapkan teknik konservasi yang sesuai pada usaha tani kentang dan kubis dapat ditemukan. Metode yang digunakan dalam penelitian ini adalah dengan mengukur aliran permukaan dan erosi tiap kejadian hujan mulai bulan Februari hingga Mei 2000 selama satu musim tanam pada plot erosi berukuran 2 x 10 meter dengan kemiringan 34 %. Kehilangan hara tanah ditentukan dengan mengukur kandungan hara sedimen tanah. Penghasilan usaha tani dihitung setelah panen. Penelitian dirancang secara faktorial dalam Rancangan Kelompok Lengkap Teracak (RKLT dengan dua faktor. Faktor pertama adalah usaha tani, yaitu kentang (C1 dan kubis (C2. Faktor kedua adalah teknik konservasi tanah, yaitu guludan memotong kontur (P1 sebagai kontrol, guludan sejajar kontur dan teras-gulud yang di tanami serai (P2, guludan sejajar kontur dengm penutupan mulsa alang-alang (P3, dan guludan sejajar kontur dengan mulsa plastik perak hitam (P4. Hasil penelitian ini menunjukkan bahwa pada usaha tani kentang, tindakan konservasi P2, P3 dan P4 mampu menekan erosi. Tindakan konservasi P2 dan P4 mampu meningkatkan penghasilan, namun P3 menurunkan penghasilan. Pada usaha tani kubis, tindakan konservasi tanah yang mampu menekan erosi hanya P3. Tindakan konservasi P2, P3, dan P4 mampu meningkatkan penghasilan. Tindakan konservasi kentang yang bagus, baik secara lingkungan maupun
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
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...
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...
Managing pre-eclampsia and eclampsia in Dar es Salaam public ...

African Journals Online (AJOL)

Managing pre-eclampsia and eclampsia in Dar es Salaam public health facilities: A focus on equipment, supplies, ... Tanzania Medical Journal ... A checklist was used to assess availability of equipment, supplies and drugs, and a structured ...
Validation of the high-throughput marker technology DArT using the model plant Arabidopsis thaliana.

Science.gov (United States)

Wittenberg, Alexander H J; van der Lee, Theo; Cayla, Cyril; Kilian, Andrzej; Visser, Richard G F; Schouten, Henk J

2005-08-01

Diversity Arrays Technology (DArT) is a microarray-based DNA marker technique for genome-wide discovery and genotyping of genetic variation. DArT allows simultaneous scoring of hundreds of restriction site based polymorphisms between genotypes and does not require DNA sequence information or site-specific oligonucleotides. This paper demonstrates the potential of DArT for genetic mapping by validating the quality and molecular basis of the markers, using the model plant Arabidopsis thaliana. Restriction fragments from a genomic representation of the ecotype Landsberg erecta (Ler) were amplified by PCR, individualized by cloning and spotted onto glass slides. The arrays were then hybridized with labeled genomic representations of the ecotypes Columbia (Col) and Ler and of individuals from an F(2) population obtained from a Col x Ler cross. The scoring of markers with specialized software was highly reproducible and 107 markers could unambiguously be ordered on a genetic linkage map. The marker order on the genetic linkage map coincided with the order on the DNA sequence map. Sequencing of the Ler markers and alignment with the available Col genome sequence confirmed that the polymorphism in DArT markers is largely a result of restriction site polymorphisms.
The Use of Three-Dimensional Convolutional Neural Networks to Interpret LiDAR for Forest Inventory

Directory of Open Access Journals (Sweden)

Elias Ayrey

2018-04-01

Full Text Available As light detection and ranging (LiDAR technology becomes more available, it has become common to use these datasets to generate remotely sensed forest inventories across landscapes. Traditional methods for generating these inventories employ the use of height and proportion metrics to measure LiDAR returns and relate these back to field data using predictive models. Here, we employ a three-dimensional convolutional neural network (CNN, a deep learning technique that scans the LiDAR data and automatically generates useful features for predicting forest attributes. We test the accuracy in estimating forest attributes using the three-dimensional implementations of different CNN models commonly used in the field of image recognition. Using the best performing model architecture, we compared CNN performance to models developed using traditional height metrics. The results of this comparison show that CNNs produced 12% less prediction error when estimating biomass, 6% less in estimating tree count, and 2% less when estimating the percentage of needleleaf trees. We conclude that using CNNs can be a more accurate means of interpreting LiDAR data for forest inventories compared to standard approaches.
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.
San Clemente Island Baseline LiDAR Mapping Final Report

Science.gov (United States)

2016-12-01

full-waveform LiDAR (Riegl® Q680i), a hyperspectral sensor (Specim AISA EAGLE), an SLR camera, and supporting instruments for geolocation and...manual editing would be necessary for detailed gully identification. Figure 12. Extensive gully erosion on the southwest part of San Clemente. Figure 13
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.
Bilevel Optimization for Scene Segmentation of LiDAR Point Cloud

Directory of Open Access Journals (Sweden)

LI Minglei

2018-02-01

Full Text Available The segmentation of point clouds obtained by light detection and ranging (LiDAR systems is a critical step for many tasks,such as data organization,reconstruction and information extraction.In this paper,we propose a bilevel progressive optimization algorithm based on the local differentiability.First,we define the topological relation and distance metric of points in the framework of Riemannian geometry,and in the point-based level using k-means method generates over-segmentation results,e.g.super voxels.Then these voxels are formulated as nodes which consist a minimal spanning tree.High level features are extracted from voxel structures,and a graph-based optimization method is designed to yield the final adaptive segmentation results.The implementation experiments on real data demonstrate that our method is efficient and superior to state-of-the-art methods.
ÉTUDE DE CAS — Dar es-Salaam, Tanzanie : Assurer la sécurité ...

International Development Research Centre (IDRC) Digital Library (Canada)

20 déc. 2010 ... En l'absence de services suffisants, les citadins sont passés maîtres dans l'art de « se débrouiller » et d'improviser. Par la force des choses, Dar es-Salaam, ou Dar, est devenue une ville ..... Urban agriculture: Growing food in our cities. City dwellers have been growing their own food for millennia.
Métodos de extração e qualidade da fração lipídica de matérias-primas de origem vegetal e animal Extraction methods and quality of the lipid fraction of vegetable and animal samples

Directory of Open Access Journals (Sweden)

Aelson Aloir Santana Brum

2009-01-01

Full Text Available Methodologies of extraction of lipids from chicken breast and oats flakes were evaluated: Soxhlet, Folch et al., Bligh & Dyer and Hara & Radin. For chicken breast, the methods Soxhlet, Folch et al. and Bligh & Dyer presented the highest yields in total lipids. With oat flakes, the methods Soxhlet and Bligh & Dyer presented higher yields than the Hara & Radin and Folch et al. The Soxhlet method affected the quality of the lipid fraction in both samples. Extracted lipid components were separated by thin layer chromatography, the chloroform-methanol based was more efficient to extract the neutral and polar lipids.
Applying a weighted random forests method to extract karst sinkholes from LiDAR data

Science.gov (United States)

Zhu, Junfeng; Pierskalla, William P.

2016-02-01

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

2010-01-01

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

Directory of Open Access Journals (Sweden)

Heather A. Kramer

2016-09-01

Full Text Available Forests historically associated with frequent fire have changed dramatically due to fire suppression and past harvesting over the last century. The buildup of ladder fuels, which carry fire from the surface of the forest floor to tree crowns, is one of the critical changes, and it has contributed to uncharacteristically large and severe fires. The abundance of ladder fuels makes it difficult to return these forests to their natural fire regime or to meet management objectives. Despite the importance of ladder fuels, methods for quantifying them are limited and imprecise. LiDAR (Light Detection and Ranging, a form of active remote sensing, is able to estimate many aspects of forest structure across a landscape. This study investigates a new method for quantifying ladder fuel in the field (using photographs with a calibration banner and remotely (using LiDAR data. We apply these new techniques in the Klamath Mountains of Northern California to predict ladder fuel levels across the study area. Our results demonstrate a new utility of LiDAR data to identify fire hazard and areas in need of fuels reduction.
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

Wind Predictions Upstream Wind Turbines from a LiDAR Database

Directory of Open Access Journals (Sweden)

Soledad Le Clainche

2018-03-01

Full Text Available This article presents a new method to predict the wind velocity upstream a horizontal axis wind turbine from a set of light detection and ranging (LiDAR measurements. The method uses higher order dynamic mode decomposition (HODMD to construct a reduced order model (ROM that can be extrapolated in space. LiDAR measurements have been carried out upstream a wind turbine at six different planes perpendicular to the wind turbine axis. This new HODMD-based ROM predicts with high accuracy the wind velocity during a timespan of 24 h in a plane of measurements that is more than 225 m far away from the wind turbine. Moreover, the technique introduced is general and obtained with an almost negligible computational cost. This fact makes it possible to extend its application to both vertical axis wind turbines and real-time operation.
Assessing the Transferability of Statistical Predictive Models for Leaf Area Index Between Two Airborne Discrete Return LiDAR Sensor Designs Within Multiple Intensely Managed Loblolly Pine Forest Locations in the South-Eastern USA

Science.gov (United States)

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

2016-01-01

Leaf area is an important forest structural variable which serves as the primary means of mass and energy exchange within vegetated ecosystems. The objective of the current study was to determine if leaf area index (LAI) could be estimated accurately and consistently in five intensively managed pine plantation forests using two multiple-return airborne LiDAR datasets. Field measurements of LAI were made using the LiCOR LAI2000 and LAI2200 instruments within 116 plots were established of varying size and within a variety of stand conditions (i.e. stand age, nutrient regime and stem density) in North Carolina and Virginia in 2008 and 2013. A number of common LiDAR return height and intensity distribution metrics were calculated (e.g. average return height), in addition to ten indices, with two additional variants, utilized in the surrounding literature which have been used to estimate LAI and fractional cover, were calculated from return heights and intensity, for each plot extent. Each of the indices was assessed for correlation with each other, and was used as independent variables in linear regression analysis with field LAI as the dependent variable. All LiDAR derived metrics were also entered into a forward stepwise linear regression. The results from each of the indices varied from an R2 of 0.33 (S.E. 0.87) to 0.89 (S.E. 0.36). Those indices calculated using ratios of all returns produced the strongest correlations, such as the Above and Below Ratio Index (ABRI) and Laser Penetration Index 1 (LPI1). The regression model produced from a combination of three metrics did not improve correlations greatly (R2 0.90; S.E. 0.35). The results indicate that LAI can be predicted over a range of intensively managed pine plantation forest environments accurately when using different LiDAR sensor designs. Those indices which incorporated counts of specific return numbers (e.g. first returns) or return intensity correlated poorly with field measurements. There were
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...
Engineering geological mapping of Dar es Salaam city, Tanzania ...

African Journals Online (AJOL)

Two basic maps were prepared, namely, geomorphological and geological map depicts the spatial extent of the Neogene geological formations. Three distinct sandstone terraces could be distinguished in Dar es Salaam region at 0-15 m and 30 – 40 m above sea level. The terraces comprised sandstones fringed by coral ...
Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.

Science.gov (United States)

Guo, Qinghua; Wu, Fangfang; Pang, Shuxin; Zhao, Xiaoqian; Chen, Linhai; Liu, Jin; Xue, Baolin; Xu, Guangcai; Li, Le; Jing, Haichun; Chu, Chengcai

2018-03-01

With the growing population and the reducing arable land, breeding has been considered as an effective way to solve the food crisis. As an important part in breeding, high-throughput phenotyping can accelerate the breeding process effectively. Light detection and ranging (LiDAR) is an active remote sensing technology that is capable of acquiring three-dimensional (3D) data accurately, and has a great potential in crop phenotyping. Given that crop phenotyping based on LiDAR technology is not common in China, we developed a high-throughput crop phenotyping platform, named Crop 3D, which integrated LiDAR sensor, high-resolution camera, thermal camera and hyperspectral imager. Compared with traditional crop phenotyping techniques, Crop 3D can acquire multi-source phenotypic data in the whole crop growing period and extract plant height, plant width, leaf length, leaf width, leaf area, leaf inclination angle and other parameters for plant biology and genomics analysis. In this paper, we described the designs, functions and testing results of the Crop 3D platform, and briefly discussed the potential applications and future development of the platform in phenotyping. We concluded that platforms integrating LiDAR and traditional remote sensing techniques might be the future trend of crop high-throughput phenotyping.
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.
Fusion of LiDAR and aerial imagery for the estimation of downed tree volume using Support Vector Machines classification and region based object fitting

Science.gov (United States)

Selvarajan, Sowmya

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

Science.gov (United States)

Castaño, Fernando; Beruvides, Gerardo; Villalonga, Alberto; Haber, Rodolfo E

2018-05-10

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the 'Internet of Things' (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds.
LiDAR-guided Archaeological Survey of a Mediterranean Landscape: Lessons from the Ancient Greek Polis of Kolophon (Ionia, Western Anatolia).

Science.gov (United States)

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

2017-01-01

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

African Journals Online (AJOL)

Dar Es Salaam Medical Students' Journal. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 15, No 1 (2008) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. Aggression; a Paradoxical pathology of the mind.
MKENO-DAR: a direct angular representation Monte Carlo code for criticality safety analysis

International Nuclear Information System (INIS)

Naito, Yoshitaka; Komuro, Yuichi; Tsunoo, Yukiyasu; Nakayama, Mitsuo.

1984-03-01

Improving the Monte Carlo code MULTI-KENO, the MKENO-DAR (Direct Angular Representation) code has been developed for criticality safety analysis in detail. A function was added to MULTI-KENO for representing anisotropic scattering strictly. With this function, the scattering angle of neutron is determined not by the average scattering angle μ-bar of the Pl Legendre polynomial but by the random work operation using probability distribution function produced with the higher order Legendre polynomials. This code is avilable for the FACOM-M380 computer. This report is a computer code manual for MKENO-DAR. (author)
Sexual behaviours and associated factors among students at Bahir Dar University: a cross sectional study

OpenAIRE

Mulu, Wondemagegn; Yimer, Mulat; Abera, Bayeh

2014-01-01

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

Directory of Open Access Journals (Sweden)

Myburg Alexander A

2010-06-01

Full Text Available Abstract Background A number of molecular marker technologies have allowed important advances in the understanding of the genetics and evolution of Eucalyptus, a genus that includes over 700 species, some of which are used worldwide in plantation forestry. Nevertheless, the average marker density achieved with current technologies remains at the level of a few hundred markers per population. Furthermore, the transferability of markers produced with most existing technology across species and pedigrees is usually very limited. High throughput, combined with wide genome coverage and high transferability are necessary to increase the resolution, speed and utility of molecular marker technology in eucalypts. We report the development of a high-density DArT genome profiling resource and demonstrate its potential for genome-wide diversity analysis and linkage mapping in several species of Eucalyptus. Findings After testing several genome complexity reduction methods we identified the PstI/TaqI method as the most effective for Eucalyptus and developed 18 genomic libraries from PstI/TaqI representations of 64 different Eucalyptus species. A total of 23,808 cloned DNA fragments were screened and 13,300 (56% were found to be polymorphic among 284 individuals. After a redundancy analysis, 6,528 markers were selected for the operational array and these were supplemented with 1,152 additional clones taken from a library made from the E. grandis tree whose genome has been sequenced. Performance validation for diversity studies revealed 4,752 polymorphic markers among 174 individuals. Additionally, 5,013 markers showed segregation when screened using six inter-specific mapping pedigrees, with an average of 2,211 polymorphic markers per pedigree and a minimum of 859 polymorphic markers that were shared between any two pedigrees. Conclusions This operational DArT array will deliver 1,000-2,000 polymorphic markers for linkage mapping in most eucalypt pedigrees
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.
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.
Tecniche di rilievo tridimensionale e rischio idrogeologico: condivisione in rete di dati in alta risoluzione LiDAR

Directory of Open Access Journals (Sweden)

Giorgio Paolo Maria Vassena

2013-03-01

Full Text Available Le tecniche di rilevamento tridimensionale con misurazione ad alta densità, ad esempio tramite approcci LiDARaerotrasportati, da terra (TLS - Terrestrial Laser Scanner o su mezzi mobili (mobile mapping, permettono di rilevaree osservare il territorio con una accuratezza, una risoluzione e una ricchezza di dettaglio globalmente molto elevaterispetto agli approcci di rilevamento tradizionali. Per la gestione delle grandi moli di dati generati si presenta unaapplicazione di una tecnologia altamente innovativa, unica a livello internazionale, sviluppata dall’Università degli Studidi Brescia, in accordo con l’azienda spin-off Gexcel srl, che permette la condivisione e visualizzazione di dati ad altadensità, anche via rete.Abstract 3D surveying techniques dealing withhigh density measurement (i.e. throughairborne LiDAR by TLS - Terrestrial LaserScanner - or by mobile mappingallow to survey and observe the territorywith accuracy, a particular resolutionand richness of details extremely highcompared to traditional survey approaches.These technologies, due tothe size of raw data, not allow the sharingand the direct reading of 3D databy different users. Usually, the data areput into standard formats (digital terrainmodel, contour lines, etc. to beshared. The raw data (with all the associatedcontents are, on the otherhand, generally lost or saved in formatsand devices (hard disks or DVD thatdoesn’t make it available to the costumer.An application of a technologydeveloped by the University of Brescia(together with the spin-off Gexcel srl ispresented. This application allows thesharing and visualization of these databy web. The difficulty of implementingthe sharing technologies of LiDARdata lies in the transfer of 3D surveyeddata, even if only to display them. Thisresearch intends to propose a new wayof data managing/transmission, also byinternet, enabling to store 3D LiDARdata in a single file and to add differentlayers on this model. In particular
Tecniche di rilievo tridimensionale e rischio idrogeologico: condivisione in rete di dati in alta risoluzione LiDAR

Directory of Open Access Journals (Sweden)

Giorgio Paolo Maria Vassena

2013-03-01

Full Text Available Le tecniche di rilevamento tridimensionale con misurazione ad alta densità, ad esempio tramite approcci LiDARaerotrasportati, da terra (TLS - Terrestrial Laser Scanner o su mezzi mobili (mobile mapping, permettono di rilevaree osservare il territorio con una accuratezza, una risoluzione e una ricchezza di dettaglio globalmente molto elevaterispetto agli approcci di rilevamento tradizionali. Per la gestione delle grandi moli di dati generati si presenta unaapplicazione di una tecnologia altamente innovativa, unica a livello internazionale, sviluppata dall’Università degli Studidi Brescia, in accordo con l’azienda spin-off Gexcel srl, che permette la condivisione e visualizzazione di dati ad altadensità, anche via rete. Abstract 3D surveying techniques dealing withhigh density measurement (i.e. throughairborne LiDAR by TLS - Terrestrial LaserScanner - or by mobile mappingallow to survey and observe the territorywith accuracy, a particular resolutionand richness of details extremely highcompared to traditional survey approaches.These technologies, due tothe size of raw data, not allow the sharingand the direct reading of 3D databy different users. Usually, the data areput into standard formats (digital terrainmodel, contour lines, etc. to beshared. The raw data (with all the associatedcontents are, on the otherhand, generally lost or saved in formatsand devices (hard disks or DVD thatdoesn’t make it available to the costumer.An application of a technologydeveloped by the University of Brescia(together with the spin-off Gexcel srl ispresented. This application allows thesharing and visualization of these databy web. The difficulty of implementingthe sharing technologies of LiDARdata lies in the transfer of 3D surveyeddata, even if only to display them. Thisresearch intends to propose a new wayof data managing/transmission, also byinternet, enabling to store 3D LiDARdata in a single file and to add differentlayers on this model. In
Feeding Dar es Salaam: a symbiotic food system perspective

NARCIS (Netherlands)

Wegerif, Marc C.A.

2017-01-01

This thesis is a sociological analysis of the agri-food system that feeds most of the over four and a half million residents of the fast-growing city of Dar es Salaam in Tanzania. It is based on qualitative research that has generated a picture of the food system that supplies the important foods
Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR.

Science.gov (United States)

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

2017-10-17

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

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

African Journals Online (AJOL)

DrNneka

International Journal of Arts and Humanities(IJAH). Bahir Dar- Ethiopia. Vol. 5(2), S/No 17, April, ... Commission's accreditation exercise on personnel in the business education programmes of the universities in the South-east .... education personnel in universities. Method. The study adopted descriptive survey design.
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.
High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR.

Science.gov (United States)

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

2018-01-01

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

Science.gov (United States)

Gordon, Christopher E; Price, Owen F; Tasker, Elizabeth M

2017-07-01

There is a public perception that large high-severity wildfires decrease biodiversity and increase fire hazard by homogenizing vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10 × 10 m, 30 × 30 m, 50 × 50 m, 100 × 100 m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5-3.0 m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22-40% lower in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seed banks varied at finer scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01 ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high-severity fires do not homogenize vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate
Intraday monitoring of granitic exfoliation sheets with LiDAR and thermal imaging (Yosemite Valley, California, USA)

Science.gov (United States)

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

2016-04-01

Rockfall activity in Yosemite Valley is often linked to the presence of exfoliation sheets associated with other structures such as faults, joints or geological contacts. Daily and seasonal temperature variations or freeze-thaw cycles may strongly promote crack propagation along discontinuities, ultimately leading to rockfalls (Stock et al., 2013). However, little is known concerning the impact of thermal variations on rock face deformation, despite its occurrence at all times of year. To understand the influence of daily temperature fluctuations on the behavior of exfoliation joints (i.e., fractures separating exfoliation sheets), we carried out two different experiments in October 2015: (a) We first monitored a sub-vertical granodiorite flake (19 m by 4 m by 0.1 m ; Collins and Stock, 2014) for 24 consecutive hours using LiDAR and infrared thermal sensors; (b) We monitored a rock cliff (60 m by 45 m) composed of tens of exfoliation sheets located on the southeast face of El Capitan (an ~1000-m-tall cliff located in western Yosemite Valley) for several hours (from 05:30 pm to 01:30 am) to investigate the diurnal cooling effect on rocks of different lithologies. To calibrate the raw apparent temperature measured by the thermal imager (FLIR T660 infrared camera), we fixed pieces of reflective paper (aluminum foil) and black duct tape on both monitored cliffs to measure the reflected temperature and the emissivity of the different rocks. In addition, ambient temperature and relative humidity readings were performed for each acquisition. We then compared the calibrated temperatures to the values registered by resistance temperature detectors (Pt100 sensors), also attached to the rock. Finally, we compared the millimeter scale deformations observed with LiDAR to the values measured by manual crackmeters (standard analog comparators with springs) installed beforehand in the fractures. For the first experiment (24-hour monitoring), a series of measurements were carried
Mapping and quantifying geodiversity in land-water transition zones using MBES and topobathymetric LiDAR

DEFF Research Database (Denmark)

Ernstsen, Verner Brandbyge; Andersen, Mikkel Skovgaard; Gergely, Aron

due to the challenging environmental conditions. Combining vessel borne shallow water multibeam echosounder (MBES) surveys ,to cover the subtidal coastal areas and the river channel areas, with airborne topobathymetric light detection and ranging (LiDAR) surveys, to cover the intertidal and supratidal...... coastal areas and the river floodplain areas, potentially enables full-coverage and high-resolution mapping in these challenging environments. We have carried out MBES and topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part...... of the Wadden Sea National Park and UNESCO World Heritage, and in the Ribe Vesterå, a fluvial environment in the Ribe Å river catchment discharging into the Knudedyb tidal basin. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the MBES and the LiDAR point...
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...
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....
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...
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...
Coastal Marine Pollution in Dar es Salaam (Tanzania) relative to ...

African Journals Online (AJOL)

Pollution surveys were undertaken during 2007 and 2008 in the coastal marine environment of Dar es Salaam and the remote Ras Dege Creek. The objective was to determine the levels of microbial contamination, heavy metals and persistent organic pollutants and compare these with the recommended environmental ...
Automatic extraction of pavement markings on streets from point cloud data of mobile LiDAR

International Nuclear Information System (INIS)

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

2017-01-01

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. (paper)
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.
Effective compounds screening from Rabdosia serra (Maxim) Hara against HBV and tumor in vitro.

Science.gov (United States)

Chen, Cheng; Chen, Yang; Zhu, Hongyuan; Xiao, Yiyun; Zhang, Xiuzhen; Zhao, Jingfeng; Chen, Yuxiang

2014-01-01

The aim of this study was to screen and investigate the anti-HBV and anti-tumor activities of separated compounds from Rabdosia serra (Maxim.) Hara to lay the basis for further isolate active entity. Three kinds of extractions from Rabdosia serra using different solvents (petroleum ether, acetidin, butyl alcohol) were prepared and used to analyze their anti-HBV activity in HepG2.2.15 cells for further separation. The cytotoxicity of each extraction was tested by MTT assay, the levels of HBsAg, HBeAg and HBV DNA in supernatants from HepG2.2.15 cells were detected by ELISA and real-time quantitative polymerase chain reaction (PCR). Then, the most effective extraction was further separated, the anti-HBV activities of separated compounds were also tested by MTT and ELISA, and three compounds with highest cytotoxicity were selected to further identify their anti-tumor activities on MCF-7, BGC-823 and HepG2 cells. Acetidin extraction C2 had the most effective anti-HBV activity that was used to be further separated, it led to statistically significant reduction in HBsAg and HBeAg secretion and HBV DNA. The separation of C2 resulted in 14 compounds, A3 and A5 markedly inhibited HBsAg secretion, while A9 inhibited HBeAg secretion in a dose-dependent manner with higher TI comparing with C2. A6, A7, A11 had different anti-tumor activity against different tumor cells. These data showed that the extraction and their separated effective compounds had strong inhibitory effect on HBV replication so as to have anti-HBV activity, and further separation and purification could enhance anti-HBV activity. Meanwhile, some compounds have high cytotoxicities on different tumor cells. Our study could provide a theoretical basis for the next clinical use and the development of potential and efficient drugs for HBV and tumor therapy from Rabdosia serra.
Post-construction monitoring of a Core-Loc™ breakwater using tripod-based LiDAR

Science.gov (United States)

Podoski, Jessica H.; Bawden, Gerald W.; Bond, Sandra; Smith, Thomas D.; Foster, James

2010-01-01

The goal of the technology application described herein is to determine whether breakwater monitoring data collected using Tripod (or Terrestrial) Light Detection and Ranging (T-LiDAR) can give insight into processes such as how Core-Loc™ concrete armour units nest following construction, and in turn how settlement affects armour layer stability, concrete cap performance, and armour unit breakage. A further objective is that this information can then be incorporated into the design of future projects using concrete armour units. The results of this application of T-LiDAR, including the challenges encountered and the conclusions drawn regarding initial concrete armour unit movement will be presented in this paper.
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).
I Pulmonary aspergilloma: A 15 years experience in Dar es Salaam ...

African Journals Online (AJOL)

College of Health Sciences,P 0 Box 65001, Dar es Salaam, Tanzania. Email address: ... esisting lung cavity by a fungus of the genus aspergillus forming ... is a national referral and teaching hospital with a ... Thus, preoperative evaluation and.
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...
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....
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....

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

Data.gov (United States)

National Aeronautics and Space Administration — This dataset provides multiple-return LiDAR-derived vegetation canopy structure at 30-meter spatial resolution for the Great Smoky Mountains National Park (GSMNP)....
How integrating 3D LiDAR data in the dike surveillance protocol: The French case

Science.gov (United States)

Bretar, F.; Mériaux, P.; Fauchard, C.

2012-04-01

The recent and dramatic floods of the last years in Europe (e.g. Rhône river major flood, December 2003, Windstorm Xynthia, February 2010, in France) and in the United-States (Hurricane Katrina, August 2005) showed the vulnerability of flood or coastal defence systems. The first key point for avoiding these dramatic damages and the high cost of a failure and its consequences lies in the appropriate conception and construction of the dikes, but above all in the relevance of the surveillance protocol. Many factors introduce weaknesses in the fluvial or maritime dikes. Most of them are old embankment structures. For instance, some of the French Loire River dikes were built several centuries ago. They may have been rebuilt, modified, heightened several times, with some materials that do not necessarily match the original conception of the structure. In other respects, tree roots or animal burrows could modify the structure of the dike and reduce the watertightness or mechanical properties. The French government has built a national database, "BarDigues", since 1999 to inventory and characterize dikes. Today, there are approx. 9000 km of dikes protecting 1.5 to 2 millions of people. In the meantime, a GIS application, called « Dike SIRS » [Maurel P., 2004] , provides an operational and accurate tool to several great stakeholders in charge of managing more than 100 km of dikes. Today, the dike surveillance and diagnosis protocol consists in identifying the weaknesses of the structure and providing the degree of safety by making a preliminary study (historical research, geological and morphodynamic study, topography), geophysical study (e.g. electromagnetic methods and electrical resistivity tomography) and at last geotechnical study (e.g. drillings and stability modelling) at the very local scale when necessary [Mériaux P. & Royet P, 2007] . Considering the stretch of hundreds of kilometres, rapid, cost-effective and reliable techniques for surveying the dike must be
Shift work and sleep disorder among textile mill workers in Bahir Dar, northwest Ethiopia.

Science.gov (United States)

Abebe, Y; Fantahun, M

1999-07-01

To assess the length and quality of sleep among shift workers at Bahir Dar textile mill. A cross sectional study using structured questionnaire that contained sociodemographic variables, duration of work, work schedule, number of sleeping hours, sleep disorders, and associated reasons for such disorders. A textile mill in Bahir Dar, northwest Ethiopia. Three-hundred ninety four random sample of production workers of the mill. Sleep disorders, and the impact of external and home environment on sleep. The mean duration of work in the factory was 25.4 +/- 7.1 years. Ninety-seven per cent of the study population work in a rotating eight hourly shift system. The mean number of hours a worker sleeps after a worked shift was 5.1 +/- 2.3. Two hundred thirty (58.4%) claimed to experience a sleep disorder. Sleep disturbance was significantly associated with rotating shift work, external environmental noise, and working in the spinning department. The majority of the workers in Bahir Dar textile mill experienced sleep disturbances as detailed in the study methodology.
Automated Extraction of 3D Trees from Mobile LiDAR Point Clouds

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Y. Yu

2014-06-01

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

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Azita Ahmad Zawawi

2015-04-01

Full Text Available Aim of study: To present an approach for estimating tree heights, stand density and crown patches using LiDAR data in a subtropical broad-leaved forest. Area of study: The study was conducted within the Yambaru subtropical evergreen broad-leaved forest, Okinawa main island, Japan. Materials and methods: A digital canopy height model (CHM was extracted from the LiDAR data for tree height estimation and a watershed segmentation method was applied for the individual crown delineation. Dominant tree canopy layers were estimated using multi-scale filtering and local maxima detection. The LiDAR estimation results were then compared to the ground inventory data and a high resolution orthophoto image for accuracy assessment. Main results: A Wilcoxon matched pair test suggests that LiDAR data is highly capable of estimating tree height in a subtropical forest (z = 4.0, p = 0.345, but has limitation to detect small understory trees and a single tree delineation. The results show that there is a statistically significant different type of crown detection from LiDAR data over forest inventory (z = 0, p = 0.043. We also found that LiDAR computation results underestimated the stand density and overestimated the crown size. Research highlights: Most studies involving crown detection and tree height estimation have focused on the analysis of plantations, boreal forests and temperate forests, and less was conducted on tropical and/or subtropical forests. Our study tested the capability of LiDAR as an effective application for analyzing a highly dense forest
Knowledge, Attitude and Practice of Commercial Drivers in Dar es ...

African Journals Online (AJOL)

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

NARCIS (Netherlands)

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

2001-01-01

The aim of this study was to investigate the prevalence of teeth with untreated dental trauma among children aged 4-15 years in Dar es Salaam, Tanzania. A sample of 4524 children from three districts of different socio-economic status in the Dar es Salaam area was examined for signs of dental trauma
Derivation of Strike and Dip in Sedimentary Terrain Using 3D Image Interpretation Based on Airborne LiDAR Data

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Chih-Hsiang Yeh

2014-01-01

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

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J. A. Ejares

2016-06-01

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

African Journals Online (AJOL)

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

African Journals Online (AJOL)

The focus of this paper is on challenges facing solid waste management in. Manzese and Sinza wards, in Dar es Salaam city. In this paper different ways of generating, disposing waste and the associated problems are surveyed. About 102 people were interviewed. Different methods were employed in data collection which ...
Damage Assessment for Disaster Relief Efforts in Urban Areas Using Optical Imagery and LiDAR Data

Science.gov (United States)

Bahr, Thomas

2014-05-01

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

DEFF Research Database (Denmark)

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

2016-01-01

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

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Hamid Gharibi

2018-04-01

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

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Hui Zhou

2018-05-01

Full Text Available An airborne Ku-band frequency-modulated continuous waveform (FM-CW profiling radar, Tomoradar, records the backscatter signal from the canopy surface and the underlying ground in the southern boreal forest zone of Finland. The recorded waveforms are transformed into canopy height profiles (CHP with a similar methodology utilized in large-footprint light detection and ranging (LiDAR. The point cloud data simultaneously collected by a Velodyne® VLP-16 LiDAR on-board the same platform represent the frequency of discrete returns, which are also applied to the extraction of the CHP by calculating the gap probability and incremental distribution. To thoroughly explore the relationships of the CHP derived from Tomoradar waveforms and LiDAR data we utilized the effective waveforms of one-stripe field measurements and comparison them with four indicators, including the correlation coefficient, the root-mean-square error (RMSE of the difference, and the coefficient of determination and the RMSE of residuals of linear regression. By setting the Tomoradar footprint as 20 degrees to contain over 95% of the transmitting energy of the main lobe, the results show that 88.17% of the CHPs derived from Tomoradar waveforms correlated well with those from the LiDAR data; 98% of the RMSEs of the difference ranged between 0.002 and 0.01; 79.89% of the coefficients of determination were larger than 0.5; and 98.89% of the RMSEs of the residuals ranged from 0.001 to 0.01. Based on the investigations, we discovered that the locations of the greatest CHP derived from the Tomoradar were obviously deeper than those from the LiDAR, which indicated that the Tomoradar microwave signal had a stronger penetration capability than the LiDAR signal. Meanwhile, there are smaller differences (the average RMSEs of differences is only 0.0042 when the total canopy closure is less than 0.5 and better linear regression results in an area with a relatively open canopy than with a denser
Forest Canopy LAI and Vertical FAVD Profile Inversion from Airborne Full-Waveform LiDAR Data Based on a Radiative Transfer Model

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Han Ma

2015-02-01

Full Text Available Forest canopy leaf area index (LAI is a critical variable for the modeling of climates and ecosystems over both regional and global scales. This paper proposes a physically based method to retrieve LAI and foliage area volume density (FAVD profile directly from full-waveform Light Detection And Ranging (LiDAR data using a radiative transfer (RT model. First, a physical interaction model between LiDAR and a forest scene was built on the basis of radiative transfer theories. Next, FAVD profile of each laser shot of full-waveform LiDAR was inverted using the physical model. In addition, the missing LiDAR data, caused by high-density forest and LiDAR system limitations, were filled in based on the inverted FAVD and the ancillary CHM data. Finally, LAI of the study area was retrieved from the inverted FAVD at a 10-m resolution. CHM derived LAI based on the Beer-Lambert law was compared with the LAI derived from full-waveform data. Also, we compared the results with the field measured LAI. The values of correlation coefficient r and RMSE of the estimated LAI were 0.73 and 0.67, respectively. The results indicate that full-waveform LiDAR data is a reliable data source and represent a useful tool for retrieving forest LAI.
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.
Case of rhesus antigen weak D type 4.2. (DAR category detection

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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.
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...

Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

OpenAIRE

Dengsheng Lu; Qi Chen; Guangxing Wang; Emilio Moran; Mateus Batistella; Maozhen Zhang; Gaia Vaglio Laurin; David Saah

2012-01-01

Landsat Thematic mapper (TM) image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonst...
Aloe; Beyond use as cosmetics | Pili | Dar Es Salaam Medical ...

African Journals Online (AJOL)

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

African Journals Online (AJOL)

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

Science.gov (United States)

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

2014-01-01

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

Science.gov (United States)

Lauve, R. M.; Alizad, K.; Hagen, S. C.

2017-12-01

Airborne LiDAR (Light Detection and Ranging) data are used by engineers and scientists to create bare earth digital elevation models (DEM), which are essential to modeling complex coastal, ecological, and hydrological systems. However, acquiring accurate bare earth elevations in coastal wetlands is difficult due to the density of marsh grasses that prevent the sensors reflection off the true ground surface. Previous work by Medeiros et al. [2015] developed a technique to assess LiDAR error and adjust elevations according to marsh vegetation density and index. The aim of this study is the collection of ground truth points and the investigation on the range of potential errors found in existing LiDAR datasets within coastal Louisiana's wetlands. Survey grids were mapped out in an area dominated by Spartina alterniflora and a survey-grade Trimble Real Time Kinematic (RTK) GPS device was employed to measure bare earth ground elevations in the marsh system adjacent to Terrebonne Bay, LA. Elevations were obtained for 20 meter-spaced surveyed grid points and were used to generate a DEM. The comparison between LiDAR derived and surveyed data DEMs yield an average difference of 23 cm with a maximum difference of 68 cm. Considering the local tidal range of 45 cm, these differences can introduce substantial error when the DEM is used for ecological modeling [Alizad et al., 2016]. Results from this study will be further analyzed and implemented in order to adjust LiDAR-derived DEMs closer to their true elevation across Louisiana's coastal wetlands. ReferencesAlizad, K., S. C. Hagen, J. T. Morris, S. C. Medeiros, M. V. Bilskie, and J. F. Weishampel (2016), Coastal wetland response to sea-level rise in a fluvial estuarine system, Earth's Future, 4(11), 483-497, 10.1002/2016EF000385. Medeiros, S., S. Hagen, J. Weishampel, and J. Angelo (2015), Adjusting Lidar-Derived Digital Terrain Models in Coastal Marshes Based on Estimated Aboveground Biomass Density, Remote Sensing, 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. The Tanzanian Household Budget Survey (HBS) data covering many households' characteristics was used. Multinomial Logit (MNL) model was applied to ...
Heavy metal contamination in agricultural soils and water in Dar es ...

African Journals Online (AJOL)

USER

Department of Environmental Science and Management, Ardhi University, P. O. Box 35176, Dar es Salaam, Tanzania. Accepted 20 ... opportunities, demand for food, proximity to markets and ... serious environmental and public health effects. One of ... concentrations they can lead to poisoning (Cambra et al.,. 1999).
Algorithm for Extracting Digital Terrain Models under Forest Canopy from Airborne LiDAR Data

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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.
Literatura e Independencia

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Marta González de Díaz

2013-01-01

Full Text Available ?l abor?ar el ?e?a ??i?era??ra e i??e?e??e??ia? ?o?o ob?e?o ?e re?e?i?? e? este escrito, es pertinente dar una mirada y hacer un an lisis, as sea somero, de la situaci n de los ilustrados en la Nueva Granada, y del papel que desempe aron en la conformaci n cultural de la sociedad neogranadina. Esto nos permitir examinar la idea de una independencia cultural en lo que respecta a las creaciones literarias, y presentar las ?guras de dos grandes escritores que encarnan dos maneras diferentes de asumir el reto de esa independencia: Andr s Bello y Domingo Faustino Sarmiento.
Ancient Maya Regional Settlement and Inter-Site Analysis: The 2013 West-Central Belize LiDAR Survey

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Arlen F. Chase

2014-09-01

Full Text Available During April and May 2013, a total of 1057 km2 of LiDAR was flown by NCALM for a consortium of archaeologists working in West-central Belize, making this the largest surveyed area within the Mayan lowlands. Encompassing the Belize Valley and the Vaca Plateau, West-central Belize is one of the most actively researched parts of the Maya lowlands; however, until this effort, no comprehensive survey connecting all settlement had been conducted. Archaeological projects have investigated at least 18 different sites within this region. Thus, a large body of archaeological research provides both the temporal and spatial parameters for the varied ancient Maya centers that once occupied this area; importantly, these data can be used to help interpret the collected LiDAR data. The goal of the 2013 LiDAR campaign was to gain information on the distribution of ancient Maya settlement and sites on the landscape and, particularly, to determine how the landscape was used between known centers. The data that were acquired through the 2013 LiDAR campaign have significance for interpreting both the composition and limits of ancient Maya political units. This paper presents the initial results of these new data and suggests a developmental model for ancient Maya polities.
Fine-spatial scale predictions of understory species using climate- and LiDAR-derived terrain and canopy metrics

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

2014-01-01

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

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

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National Aeronautics and Space Administration — This data set provides LiDAR point clouds and digital terrain models (DTM) from surveys over the Tapajos National Forest in Belterra municipality, Para, Brazil...
Aggregating pixel-level basal area predictions derived from LiDAR data to industrial forest stands in North-Central Idaho

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

2008-01-01

Stand exams are the principal means by which timber companies monitor and manage their forested lands. Airborne LiDAR surveys sample forest stands at much finer spatial resolution and broader spatial extent than is practical on the ground. In this paper, we developed models that leverage spatially intensive and extensive LiDAR data and a stratified random sample of...
Does Personalized Water and Hand Quality Information Affect Attitudes, Behavior, and Health in Dar es Salaam, Tanzania?

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

2008-12-01

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

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

2014-09-09

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

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

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Qingquan Li

2014-09-01

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

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Ziegler, Alice

2017-04-01

LiDAR (Light Detection And Ranging) is a remote sensing technology that offers high-resolution three-dimensional information about the covered area. These three-dimensional datasets were used in this work to derive structural parameters of the vegetation to predict the abundance of eight different arthropod assemblages with several models. For the model training of each arthropod assemblage, different versions (extent, filters) of the LiDAR datasets were provided and evaluated. Furthermore the importance of each of the LiDAR-derived structural parameters for each model was calculated. The best input dataset and structural parameters were used for the prediction of the abundance of arthropod assemblages. The analyses of the prediction results across seven different landuse types and the eight arthropod assemblages exposed, that for the arthropod assemblages, LiDAR-based predictions were in general best feasible for "Orthoptera" (average R2 (coefficient of determination) over all landuses: 0.14), even though the predictions for the other arthropod assemblages reached values of the same magnitude. It was also found that the landuse type "disturbed forest" showed the best results (average R2 over all assemblages: 0.20), whereas "home garden" was the least predictable (average R2 over all assemblages: 0.04). Differenciated by arthropod-landuse pairs, the results showed distinct differences and the R2 values diverged clearly. It was shown, that when model settings were optimized for only one arthropod taxa, values for R2 could reach values up to 0.55 ("Orthoptera" in "disturbed forest"). The analysis of the importance of each structural parameter for the prediction revealed that about one third of the 18 used parameters were always among the most important ones for the prediction of all assemblages. This strong ranking of parameters implied that focus for further research needs to be put on the selection of predictor variables.
2009 National Renewable Energy Laboratory/Boston Redevelopment Authority Topographic LiDAR: Boston, Massachusetts

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

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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
Processing and evaluation of riverine waveforms acquired by an experimental bathymetric LiDAR

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Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.

2010-12-01

Accurate mapping of fluvial environments with airborne bathymetric LiDAR is challenged not only by environmental characteristics but also the development and application of software routines to post-process the recorded laser waveforms. During a bathymetric LiDAR survey, the transmission of the green-wavelength laser pulses through the water column is influenced by a number of factors including turbidity, the presence of organic material, and the reflectivity of the streambed. For backscattered laser pulses returned from the river bottom and digitized by the LiDAR detector, post-processing software is needed to interpret and identify distinct inflections in the reflected waveform. Relevant features of this energy signal include the air-water interface, volume reflection from the water column itself, and, ideally, a strong return from the bottom. We discuss our efforts to acquire, analyze, and interpret riverine surveys using the USGS Experimental Advanced Airborne Research LiDAR (EAARL) in a variety of fluvial environments. Initial processing of data collected in the Trinity River, California, using the EAARL Airborne Lidar Processing Software (ALPS) highlighted the difficulty of retrieving a distinct bottom signal in deep pools. Examination of laser waveforms from these pools indicated that weak bottom reflections were often neglected by a trailing edge algorithm used by ALPS to process shallow riverine waveforms. For the Trinity waveforms, this algorithm had a tendency to identify earlier inflections as the bottom, resulting in a shallow bias. Similarly, an EAARL survey along the upper Colorado River, Colorado, also revealed the inadequacy of the trailing edge algorithm for detecting weak bottom reflections. We developed an alternative waveform processing routine by exporting digitized laser waveforms from ALPS, computing the local extrema, and fitting Gaussian curves to the convolved backscatter. Our field data indicate that these techniques improved the
Metal concentrations in selected tissues and main prey species of the annulated sea snake (Hydrophis cyanocinctus) in the Hara Protected Area, northeastern coast of the Persian Gulf, Iran

International Nuclear Information System (INIS)

Rezaie-Atagholipour, Mohsen; Riyahi-Bakhtiari, Alireza; Sajjadi, Mirmasoud; Yap, Chee Kong; Ghaffari, Sanaz; Ebrahimi-Sirizi, Zohreh; Ghezellou, Parviz

2012-01-01

This study is the first detailed ecotoxicological study of the annulated sea snake, Hydrophis cyanocinctus. Concentrations of lead, cadmium, nickel and vanadium were evaluated in muscle, liver, kidney, skin and blood of the annulated sea snake (H. cyanocinctus) and in the whole bodies of its main prey species (Periophthalmus waltoni and Boleophthalmus dussumieri) in the Hara Protected Area, the Persian Gulf. The mean concentrations of lead and vanadium were highest in the kidney, which identified the kidney as a target organ for metals in sea snakes as it is in other reptilian groups. Mean concentrations of cadmium and nickel were highest in the liver and skin, respectively. Mean cadmium concentrations were significantly higher in the liver compared to prey species, which indicated that prey items may be a source of cadmium for the annulated sea snake in the study area. Data presented here may be considered as a baseline for further ecotoxicological studies in sea snakes.
Computational modeling of river flow using bathymetry collected with an experimental, water-penetrating, green LiDAR

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Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.

2009-12-01

Airborne bathymetric Light Detection and Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly being deployed in fluvial environments. While the adaptation of this technology to rivers and streams would appear to be straightforward, currently technical challenges remain with regard to achieving high levels of vertical accuracy and precision when mapping bathymetry in shallow fluvial settings. Collectively these mapping errors have a direct bearing on hydraulic model predictions made using these data. We compared channel surveys conducted along the Platte River, Nebraska, and the Trinity River, California, using conventional ground-based methods with those made with the hybrid topographic/bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). In the turbid and braided Platte River, a bathymetric-waveform processing algorithm was shown to enhance the definition of thalweg channels over a more simplified, first-surface waveform processing algorithm. Consequently flow simulations using data processed with the shallow bathymetric algorithm resulted in improved prediction of wetted area relative to the first-surface algorithm, when compared to the wetted area in concurrent aerial imagery. However, when compared to using conventionally collected data for flow modeling, the inundation extent was over predicted with the EAARL topography due to higher bed elevations measured by the LiDAR. In the relatively clear, meandering Trinity River, bathymetric processing algorithms were capable of defining a 3 meter deep pool. However, a similar bias in depth measurement was observed, with the LiDAR measuring the elevation of the river bottom above its actual position, resulting in a predicted water surface higher than that measured by field data. This contribution addresses the challenge of making bathymetric measurements with the EAARL in different environmental conditions encountered in fluvial settings, explores technical issues related to
Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast-growing Eucalyptus forest plantation using airborne LiDAR data.

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

2017-12-01

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

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Wai-Yeung Yan

2011-09-01

Full Text Available LiDAR (Light Detection And Ranging systems are capable of providing 3D positional and spectral information (in the utilized spectrum range of the mapped surface. Due to systematic errors in the system parameters and measurements, LiDAR systems require geometric calibration and radiometric correction of the intensity data in order to maximize the benefit from the collected positional and spectral information. This paper presents a practical approach for the geometric calibration of LiDAR systems and radiometric correction of collected intensity data while investigating their impact on the quality of the derived products. The proposed approach includes the use of a quasi-rigorous geometric calibration and the radar equation for the radiometric correction of intensity data. The proposed quasi-rigorous calibration procedure requires time-tagged point cloud and trajectory position data, which are available to most of the data users. The paper presents a methodology for evaluating the impact of the geometric calibration on the relative and absolute accuracy of the LiDAR point cloud. Furthermore, the impact of the geometric calibration and radiometric correction on land cover classification accuracy is investigated. The feasibility of the proposed methods and their impact on the derived products are demonstrated through experimental results using real data.
Testing the Suitability of a Terrestrial 2D LiDAR Scanner for Canopy Characterization of Greenhouse Tomato Crops

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Jordi Llop

2016-09-01

Full Text Available 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.
Using LiDAR to Estimate Surface Erosion Volumes within the Post-storm 2012 Bagley Fire

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

2014-12-01

The total post-storm 2012 Bagley fire sediment budget of the Squaw Creek watershed in the Shasta-Trinity National Forest was estimated using many methods. A portion of the budget was quantitatively estimated using LiDAR. Simple workflows were designed to estimate the eroded volume's of debris slides, fill failures, gullies, altered channels and streams. LiDAR was also used to estimate depositional volumes. Thorough manual mapping of large erosional features using the ArcGIS 10.1 Geographic Information System was required as these mapped features determined the eroded volume boundaries in 3D space. The 3D pre-erosional surface for each mapped feature was interpolated based on the boundary elevations. A surface difference calculation was run using the estimated pre-erosional surfaces and LiDAR surfaces to determine volume of sediment potentially delivered into the stream system. In addition, cross sections of altered channels and streams were taken using stratified random selection based on channel gradient and stream order respectively. The original pre-storm surfaces of channel features were estimated using the cross sections and erosion depth criteria. Open source software Inkscape was used to estimate cross sectional areas for randomly selected channel features and then averaged for each channel gradient and stream order classes. The average areas were then multiplied by the length of each class to estimate total eroded altered channel and stream volume. Finally, reservoir and in-channel depositional volumes were estimated by mapping channel forms and generating specific reservoir elevation zones associated with depositional events. The in-channel areas and zones within the reservoir were multiplied by estimated and field observed sediment thicknesses to attain a best guess sediment volume. In channel estimates included re-occupying stream channel cross sections established before the fire. Once volumes were calculated, other erosion processes of the Bagley
High resolution t-LiDAR scanning of an active bedrock fault scarp for palaeostress analysis

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Reicherter, Klaus; Wiatr, Thomas; Papanikolaou, Ioannis; Fernández-Steeger, Tomas

2013-04-01

Palaeostress analysis of an active bedrock normal fault scarp based on kinematic indicators is carried applying terrestrial laser scanning (t-LiDAR or TLS). For this purpose three key elements are necessary for a defined region on the fault plane: (i) the orientation of the fault plane, (ii) the orientation of the slickenside lineation or other kinematic indicators and (iii) the sense of motion of the hanging wall. We present a workflow to obtain palaeostress data from point cloud data using terrestrial laser scanning. The entire case-study was performed on a continuous limestone bedrock normal fault scarp on the island of Crete, Greece, at four different locations along the WNW-ESE striking Spili fault. At each location we collected data with a mobile terrestrial light detection and ranging system and validated the calculated three-dimensional palaeostress results by comparison with the conventional palaeostress method with compass at three of the locations. Numerous kinematics indicators for normal faulting were discovered on the fault plane surface using t-LiDAR data and traditional methods, like Riedel shears, extensional break-outs, polished corrugations and many more. However, the kinematic indicators are more or less unidirectional and almost pure dip-slip. No oblique reactivations have been observed. But, towards the tips of the fault, inclination of the striation tends to point towards the centre of the fault. When comparing all reconstructed palaeostress data obtained from t-LiDAR to that obtained through manual compass measurements, the degree of fault plane orientation divergence is around ±005/03 for dip direction and dip. The degree of slickenside lineation variation is around ±003/03 for dip direction and dip. Therefore, the percentage threshold error of the individual vector angle at the different investigation site is lower than 3 % for the dip direction and dip for planes, and lower than 6 % for strike. The maximum mean variation of the complete
2010 U.S. Geological Survey (USGS) Topographic LiDAR: San Francisco Bay, California

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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)...
Approach to voxel-based carbon stock quanticiation using LiDAR data in tropical rainforest, Brunei

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Kim, Eunji; Piao, Dongfan; Lee, Jongyeol; Lee, Woo-Kyun; Yoon, Mihae; Moon, Jooyeon

2016-04-01

Forest is an important means to adapt climate change as the only carbon sink recognized by the international community (KFS 2009). According to the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), Agriculture, Forestry, and Other Land Use (AFOLU) sectors including forestry contributed 24% of total anthropogenic emissions in 2010 (IPCC 2014; Tubiello et al. 2015). While all sectors excluding AFOLU have increased Greenhouse Gas (GHG) emissions, land use sectors including forestry remains similar level as before due to decreasing deforestation and increasing reforestation. In earlier researches, optical imagery has been applied for analysis (Jakubowski et al. 2013). Optical imagery collects spectral information in 2D. It is difficult to effectively quantify forest stocks, especially in dense forest (Cui et al. 2012). To detect individual trees information from remotely sensed data, Light detection and ranging (LiDAR) has been used (Hyyppäet al. 2001; Persson et al. 2002; Chen et al. 2006). Moreover, LiDAR has the ability to actively acquire vertical tree information such as tree height using geo-registered 3D points (Kwak et al. 2007). In general, however, geo-register 3D point was used with a raster format which contains only 2D information by missing all the 3D data. Therefore, this research aimed to use the volumetric pixel (referred as "voxel") approach using LiDAR data in tropical rainforest, Brunei. By comparing the parameters derived from voxel based LiDAR data and field measured data, we examined the relationships between them for the quantification of forest carbon. This study expects to be more helpful to take advantage of the strategic application of climate change adaption.
High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates.

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Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z -value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values ( H 2 > 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable ( H 2 > 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed.
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.
2007 Southwest Florida Water Management District (SWFWMD) LiDAR: Hillsborough/Little Manatee Districts

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

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National Oceanic and Atmospheric Administration, Department of Commerce — This metadata document describes the LiDAR point data in LAS format produced by Kucera covering the project area of Lake County, FL. The data produced is...
2009 U.S. Geological Survey (USGS) Topographic LiDAR: Androscoggin County, Maine

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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...
Rating of roofs’ surfaces regarding their solar potential and suitability for PV systems, based on LiDAR data

International Nuclear Information System (INIS)

Lukač, Niko; Žlaus, Danijel; Seme, Sebastijan; Žalik, Borut; Štumberger, Gorazd

2013-01-01

Highlights: ► A new method for estimating and rating buildings roofs’ solar potential is presented. ► Considering LiDAR geospatial data together with pyranometer measurements. ► Use of multi-resolution shadowing model with new heuristic vegetation shadowing. ► High correlation between estimated solar potential and onsite measurements. -- Abstract: The roof surfaces within urban areas are constantly attracting interest regarding the installation of photovoltaic systems. These systems can improve self-sufficiency of electricity supply, and can help to decrease the emissions of greenhouse gases throughout urban areas. Unfortunately, some roof surfaces are unsuitable for installing photovoltaic systems. This presented work deals with the rating of roof surfaces within urban areas regarding their solar potential and suitability for the installation of photovoltaic systems. The solar potential of a roof’s surface is determined by a new method that combines extracted urban topography from LiDAR data with the pyranometer measurements of global and diffuse solar irradiances. Heuristic annual vegetation shadowing and a multi-resolution shadowing model, complete the proposed method. The significance of different influential factors (e.g. shadowing) was analysed extensively. A comparison between the results obtained by the proposed method and measurements performed on an actual PV power plant showed a correlation agreement of 97.4%.

New Visualization Techniques to Analyze Ultra-High Resolution Four-dimensional Surface Deformation Imagery Collected With Ground-based Tripod LiDAR

Science.gov (United States)

Kreylos, O.; Bawden, G. W.; Kellogg, L. H.

2005-12-01

We are developing a visualization application to display and interact with very large (tens of millions of points) four-dimensional point position datasets in an immersive environment such that point groups from repeated Tripod LiDAR (Light Detection And Ranging) surveys can be selected, measured, and analyzed for land surface change using 3D~interactions. Ground-based tripod or terrestrial LiDAR (T-LiDAR) can remotely collect ultra-high resolution (centimeter to subcentimeter) and accurate (± 4 mm) digital imagery of the scanned target, and at scanning rates of 2,000 (x, y, z, i) (3D~position~+ intensity) points per second over 7~million points can be collected for a given target in an hour. We developed a multiresolution point set data representation based on octrees to display large T-LiDAR point cloud datasets at the frame rates required for immersive display (between 60 Hz and 120 Hz). Data inside an observer's region of interest is shown in full detail, whereas data outside the field of view or far away from the observer is shown at reduced resolution to provide context. Using 3D input devices at the University of California Davis KeckCAVES, users can navigate large point sets, accurately select related point groups in two or more point sets by sweeping regions of space, and guide the software in deriving positional information from point groups to compute their displacements between surveys. We used this new software application in the KeckCAVES to analyze 4D T-LiDAR imagery from the June~1, 2005 Blue Bird Canyon landslide in Laguna Beach, southern California. Over 50~million (x, y, z, i) data points were collected between 10 and 21~days after the landslide to evaluate T-LiDAR as a natural hazards response tool. The visualization of the T-LiDAR scans within the immediate landslide showed minor readjustments in the weeks following the primarily landslide with no observable continued motion on the primary landslide. Recovery and demolition efforts across the
Modelling Forest α-Diversity and Floristic Composition — On the Added Value of LiDAR plus Hyperspectral Remote Sensing

Directory of Open Access Journals (Sweden)

Martin Wegmann

2012-09-01

Full Text Available The decline of biodiversity is one of the major current global issues. Still, there is a widespread lack of information about the spatial distribution of individual species and biodiversity as a whole. Remote sensing techniques are increasingly used for biodiversity monitoring and especially the combination of LiDAR and hyperspectral data is expected to deliver valuable information. In this study spatial patterns of vascular plant community composition and alpha-diversity of a temperate montane forest in Germany were analysed for different forest strata. The predictive power of LiDAR (LiD and hyperspectral (MNF datasets alone and combined (MNF+LiD was compared using random forest regression in a ten-fold cross-validation scheme that included feature selection and model tuning. The final models were used for spatial predictions. Species richness could be predicted with varying accuracy (R2 = 0.26 to 0.55 depending on the forest layer. In contrast, community composition of the different layers, obtained by multivariate ordination, could in part be modelled with high accuracies for the first ordination axis (R2 = 0.39 to 0.78, but poor accuracies for the second axis (R2 ≤ 0.3. LiDAR variables were the best predictors for total species richness across all forest layers (R2 LiD = 0.3, R2 MNF = 0.08, R2 MNF+LiD = 0.2, while for community composition across all forest layers both hyperspectral and LiDAR predictors achieved similar performances (R2 LiD = 0.75, R2 MNF = 0.76, R2 MNF+LiD = 0.78. The improvement in R2 was small (≤0.07—if any—when using both LiDAR and hyperspectral data as compared to using only the best single predictor set. This study shows the high potential of LiDAR and hyperspectral data for plant biodiversity modelling, but also calls for a critical evaluation of the added value of combining both with respect to acquisition costs.
Multi-static Serial LiDAR for Surveillance and Identification of Marine Life at MHK Installations

Energy Technology Data Exchange (ETDEWEB)

Alsenas, Gabriel [Florida Atlantic Univ., Boca Raton, FL (United States); Dalgleish, Fraser [Florida Atlantic Univ., Boca Raton, FL (United States); Ouyang, Bing [Florida Atlantic Univ., Boca Raton, FL (United States)

2017-06-30

Final Report for project DE-EE0006787: Multi-static Serial LiDAR for Surveillance and Identification of Marine Life at MHK Installations. This project developed and tested an optical monitoring system prototype that will be suitable for marine and hydrokinetic (MHK) full project lifecycle observation (baseline, commissioning, and decommissioning), with automated real-time classification of marine animals. This system can be deployed to collect pre-installation baseline species observations at a proposed deployment site with minimal post-processing overhead. To satisfy deployed MHK project species of concern (e.g. Endangered Species Act-listed) monitoring requirements, the system provides automated tracking and notification of the presence of managed animals within established perimeters of MHK equipment and provides high resolution imagery of their behavior through a wide range of conditions. During a project’s decommissioning stage, the system can remain installed to provide resource managers with post-installation data. Our technology, known as an Unobtrusive Multi-static Serial LiDAR Imager (UMSLI), is a technology transfer of underwater distributed LiDAR imaging technology that preserves the advantages of traditional optical and acoustic solutions while overcoming associated disadvantages for MHK environmental monitoring applications. This new approach is a purposefully-designed, reconfigurable adaptation of an existing technology that can be easily mounted on or around different classes of MHK equipment. The system uses low average power red (638nm) laser illumination to be invisible and eye-safe to marine animals and is compact and cost effective. The equipment is designed for long term, maintenance-free operations, to inherently generate a sparse primary dataset that only includes detected anomalies (animal presence information), and to allow robust real-time automated animal classification/identification with a low data bandwidth requirement. Advantages
Assessing Surface Fuel Hazard in Coastal Conifer Forests through the Use of LiDAR Remote Sensing

Science.gov (United States)

Koulas, Christos

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

Science.gov (United States)

Knevels, Raphael; Leopold, Philip; Petschko, Helene

2017-04-01

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

Science.gov (United States)

Yang, Bingwei; Xie, Xinhao; Li, Duan

2018-01-01

Time of flight (TOF) based light detection and ranging (LiDAR) is a technology for calculating distance between start/stop signals of time of flight. In lab-built LiDAR, two ranging systems for measuring flying time between start/stop signals include time-to-digital converter (TDC) that counts time between trigger signals and analog-to-digital converter (ADC) that processes the sampled start/stop pulses waveform for time estimation. We study the influence of waveform characteristics on range accuracy and precision of two kinds of ranging system. Comparing waveform based ranging (WR) with analog discrete return system based ranging (AR), a peak detection method (WR-PK) shows the best ranging performance because of less execution time, high ranging accuracy, and stable precision. Based on a novel statistic mathematical method maximal information coefficient (MIC), WR-PK precision has a high linear relationship with the received pulse width standard deviation. Thus keeping the received pulse width of measuring a constant distance as stable as possible can improve ranging precision. PMID:29642639
Influence of Waveform Characteristics on LiDAR Ranging Accuracy and Precision

Directory of Open Access Journals (Sweden)

Xiaolu Li

2018-04-01

Full Text Available Time of flight (TOF based light detection and ranging (LiDAR is a technology for calculating distance between start/stop signals of time of flight. In lab-built LiDAR, two ranging systems for measuring flying time between start/stop signals include time-to-digital converter (TDC that counts time between trigger signals and analog-to-digital converter (ADC that processes the sampled start/stop pulses waveform for time estimation. We study the influence of waveform characteristics on range accuracy and precision of two kinds of ranging system. Comparing waveform based ranging (WR with analog discrete return system based ranging (AR, a peak detection method (WR-PK shows the best ranging performance because of less execution time, high ranging accuracy, and stable precision. Based on a novel statistic mathematical method maximal information coefficient (MIC, WR-PK precision has a high linear relationship with the received pulse width standard deviation. Thus keeping the received pulse width of measuring a constant distance as stable as possible can improve ranging precision.
Analyzing Hydro-Geomorphic Responses in Post-Fire Stream Channels with Terrestrial LiDAR

Science.gov (United States)

Nourbakhshbeidokhti, S.; Kinoshita, A. M.; Chin, A.

2015-12-01

Wildfires have potential to significantly alter soil properties and vegetation within watersheds. These alterations often contribute to accelerated erosion, runoff, and sediment transport in stream channels and hillslopes. This research applies repeated Terrestrial Laser Scanning (TLS) Light Detection and Ranging (LiDAR) to stream reaches within the Pike National Forest in Colorado following the 2012 Waldo Canyon Fire. These scans allow investigation of the relationship between sediment delivery and environmental characteristics such as precipitation, soil burn severity, and vegetation. Post-fire LiDAR images provide high resolution information of stream channel changes in eight reaches for three years (2012-2014). All images are processed with RiSCAN PRO to remove vegetation and triangulated and smoothed to create a Digital Elevation Model (DEM) with 0.1 m resolution. Study reaches with two or more successive DEM images are compared using a differencing method to estimate the volume of sediment erosion and deposition. Preliminary analysis of four channel reaches within Williams Canyon and Camp Creek yielded erosion estimates between 0.035 and 0.618 m3 per unit area. Deposition was estimated as 0.365 to 1.67 m3 per unit area. Reaches that experienced higher soil burn severity or larger rainfall events produced the greatest geomorphic changes. Results from LiDAR analyses can be incorporated into post-fire hydrologic models to improve estimates of runoff and sediment yield. These models will, in turn, provide guidance for water resources management and downstream hazards mitigation.
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...
planning for the automation of the university of dar es salaam library

African Journals Online (AJOL)

The paper examines the planning process for the automation of the University of Dar es Salaam Library. The planning phases described include the preparation phase, planning for implementation and database construction. The major issues during the preparation phase are the discussion on the context of automation, ...
2011 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Quinnipiac River Watershed, Connecticut

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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...
Sebaran Horizontal Zat Hara di Perairan Lamalera, Nusa Tenggara Timur (Horizontal Distribution of Nutrients in the Waters Lamalera, East Nusa Tenggara

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Marojahan Simanjuntak

2012-06-01

Full Text Available Perairan Lamalera, Nusa Tenggara Timur merupakan perairan yang sangat penting karena kondisi oseanografinya yang dipengaruhi daratan, Laut Sawu, dan Samudera Hindia sehingga kaya akan sumberdaya laut. Penelitian oseanografi di perairan Lamalera, Nusa Tenggara Timur telah dilakukan pada bulan Juli 2011. Tujuan penelitian tersebut untuk mengkaji kualitas air ditinjau dari kandungan zat hara yang merupakan indikator kesuburan perairan serta faktor-faktor yang mempengaruhinya di perairan Lamalera, Nusa Tenggara Timur. Parameter yang diteliti meliputi fosfat, nitrat, dan silikat serta parameter kualitas air yaitu oksigen terlarut, dan keasaman (pH. Metode penelitian yang digunakan adalah pengambilan air laut dari lapisan permukaan (5 m, termoklin (15-150 m dan dibawah termoklin (100-300 m pada 19 stasiun penelitian. Kadar fosfat, nitrat, dan silikat dianalisis menurut metode Strickland dan Parsons. Kadar oksigen terlarut diukur dengan menggunakan metode Winkler. Derajat keasaman (pH diukur dengan pH meter Cyber Scan 300. Hasil yang diperoleh menunjukkan bahwa kadar zat hara pada umumnya lebih tinggi di sebelah selatan perairan ini. Kadar fosfat berkisar 0,53–5,93 μg A/l; nitrat 0,34–28,31 μg A/l, dan silikat 0,69–44,60 μg A/l. Kadar oksigen terlarut berkisar 2,30–4,90 ml/l, dan nilai pH 7,85–8,21. Parameter yang diteliti di perairan Lamalera, Nusa Tenggara Timur masih baik untuk kehidupan berbagai biota mengacu pada Baku Mutu yang telah ditetapkan oleh Kementerian Negara Lingkungan Hidup (KMNLH. Kata kunci: Kualitas air, fosfat, nitrat, silikat, Perairan Lamalera. Lamalera Waters, East Nusa Tenggara is one of the waters are very important because the condition of the affected land, Sawu Sea, and Indian Ocean, so rich in marine resources. Oceanographic research in the Lamalera Waters, East Nusa Tenggara have been carried out in July 2011. The research objective was to assess water quality in terms of the nutrients content, which is an
Comparative study of building footprint estimation methods from LiDAR point clouds

Science.gov (United States)

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

2017-10-01

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

Directory of Open Access Journals (Sweden)

Xiaolong Liu

2015-01-01

Full Text Available Identification of crop species is an important issue in agricultural management. In recent years, many studies have explored this topic using multi-spectral and hyperspectral remote sensing data. In this study, we perform dedicated research to propose a framework for mapping crop species by combining hyperspectral and Light Detection and Ranging (LiDAR data in an object-based image analysis (OBIA paradigm. The aims of this work were the following: (i to understand the performances of different spectral dimension-reduced features from hyperspectral data and their combination with LiDAR derived height information in image segmentation; (ii to understand what classification accuracies of crop species can be achieved by combining hyperspectral and LiDAR data in an OBIA paradigm, especially in regions that have fragmented agricultural landscape and complicated crop planting structure; and (iii to understand the contributions of the crop height that is derived from LiDAR data, as well as the geometric and textural features of image objects, to the crop species’ separabilities. The study region was an irrigated agricultural area in the central Heihe river basin, which is characterized by many crop species, complicated crop planting structures, and fragmented landscape. The airborne hyperspectral data acquired by the Compact Airborne Spectrographic Imager (CASI with a 1 m spatial resolution and the Canopy Height Model (CHM data derived from the LiDAR data acquired by the airborne Leica ALS70 LiDAR system were used for this study. The image segmentation accuracies of different feature combination schemes (very high-resolution imagery (VHR, VHR/CHM, and minimum noise fractional transformed data (MNF/CHM were evaluated and analyzed. The results showed that VHR/CHM outperformed the other two combination schemes with a segmentation accuracy of 84.8%. The object-based crop species classification results of different feature integrations indicated that
Genetics and Human Agency: Comment on Dar-Nimrod and Heine (2011)

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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…
A comparison of two open source LiDAR surface classification algorithms

Science.gov (United States)

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

2011-01-01

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

Science.gov (United States)

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

2011-01-01

Foresters are increasingly interested in remote sensing data because they provide an overview of landscape conditions, which is impractical with field sample data alone. Light Detection and Ranging (LiDAR) provides exceptional spatial detail of forest structure, but difficulties in processing LiDAR data have limited their application beyond the research community....
Reconstructing the Roman Site “Aquis Querquennis” (Bande, Spain from GPR, T-LiDAR and IRT Data Fusion

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Iván Puente

2018-03-01

Full Text Available This work presents the three-dimensional (3D reconstruction of one of the most important archaeological sites in Galicia: “Aquis Querquennis” (Bande, Spain using in-situ non-invasive ground-penetrating radar (GPR and Terrestrial Light Detection and Ranging (T-LiDAR techniques, complemented with infrared thermography. T-LiDAR is used for the recording of the 3D surface of this particular case and provides high resolution 3D digital models. GPR data processing is performed through the novel software tool “toGPRi”, developed by the authors, which allows the creation of a 3D model of the sub-surface and the subsequent XY images or time-slices at different depths. All these products are georeferenced, in such a way that the GPR orthoimages can be combined with the orthoimages from the T-LiDAR for a complete interpretation of the site. In this way, the GPR technique allows for the detection of the structures of the barracks that are buried, and their distribution is completed with the structure measured by the T-LiDAR on the surface. In addition, the detection of buried elements made possible the identification and labelling of the structures of the surface and their uses. These structures are additionally inspected with infrared thermography (IRT to determine their conservation condition and distinguish between original and subsequent constructions.
Comportamento sexual, parâmetros seminais e fertilidade do sêmen congelado de jumentos (Equus asinus) da raça Pêga

OpenAIRE

Canisso, Igor Frederico

2008-01-01

Esta dissertação compreende quatro experimentos. Experimento1: Este estudo descreve algumas características do comportamento sexual de jumentos quando uma égua em estro foi usada para a coleta de sêmen. Foram usados neste estudo seis jumentos (J: 1, 2, 3, 4, 5, 6) da raça Pêga, com idade variando de 3,5 a 16 anos e pesando de 230 a 330 kg. Os animais foram previamente condicionados em um haras comercial de produção de muares localizado em Guaraciaba, Minas Gerais, Brasil. Para a colheita de s...
Development of a UAV-LiDAR System with Application to Forest Inventory

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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.

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

Data.gov (United States)

National Aeronautics and Space Administration — This data set provides high-resolution LiDAR point cloud data collected during surveys over mangrove forests in the Zambezi River Delta in Mozambique in May 2014....
Characterization of the horizontal structure of the tropical forest canopy using object-based LiDAR and multispectral image analysis

Science.gov (United States)

Dupuy, Stéphane; Lainé, Gérard; Tassin, Jacques; Sarrailh, Jean-Michel

2013-12-01

This article's goal is to explore the benefits of using Digital Surface Model (DSM) and Digital Terrain Model (DTM) derived from LiDAR acquisitions for characterizing the horizontal structure of different facies in forested areas (primary forests vs. secondary forests) within the framework of an object-oriented classification. The area under study is the island of Mayotte in the western Indian Ocean. The LiDAR data were the data originally acquired by an airborne small-footprint discrete-return LiDAR for the "Litto3D" coastline mapping project. They were used to create a Digital Elevation Model (DEM) at a spatial resolution of 1 m and a Digital Canopy Model (DCM) using median filtering. The use of two successive segmentations at different scales allowed us to adjust the segmentation parameters to the local structure of the landscape and of the cover. Working in object-oriented mode with LiDAR allowed us to discriminate six vegetation classes based on canopy height and horizontal heterogeneity. This heterogeneity was assessed using a texture index calculated from the height-transition co-occurrence matrix. Overall accuracy exceeds 90%. The resulting product is the first vegetation map of Mayotte which emphasizes the structure over the composition.
AN EFFICIENT METHOD FOR AUTOMATIC ROAD EXTRACTION BASED ON MULTIPLE FEATURES FROM LiDAR DATA

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Y. Li

2016-06-01

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

Science.gov (United States)

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

2018-01-01

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

Directory of Open Access Journals (Sweden)

Roberto José Ortiz

2015-08-01

Full Text Available The late 19th struggle for artistic freedom in the capitalist world-system put the artist in a contradictory position. This contradiction is particularly relevant for writers of the periphery. Freedom or autonomy to pursue purely intellectual projects required a certain aristocratic defense of the value of art. At the same time, however, artists and intellectuals did confront structural subordination: they belonged, as Pierre Bourdieu explained, to the dominated fractions of the dominant class, subordinated both to the state and the bourgeoisie. The life of Nicaraguan Ruben Darío (1867–1916, probably the most well-known poet in Latin American history, provides a paradigmatic instance of this dilemma. Moreover, it sheds light into a dilemma particular to the peripheral intellectual. Peripheral writers, in the 19th century and still today, are subject to world-systemic hierarchies, even cultural ones. This double subordination is clear in the case of Ruben Darío. He was in a subordinated position not only vis-à-vis the national state and the bourgeoisie. Darío was also in a subordinated position, even if symbolic, in relation to those same intellectuals that Bourdieu celebrated as creators of the autonomy of culture in France. One can account for this complex of hierarchies only through a 'world-systems biography' approach. World-systems biographies clearly examine the dialectic of personal, national and global levels of social life. Moreover, it can uncover the core-periphery dialectic in the realm of artistic production. Thus, this world-systems biography approach is shown to be a useful framework through a brief analysis of Darío's life and work.
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
A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds

Directory of Open Access Journals (Sweden)

Bin Wu

2017-01-01

Full Text Available 3D building model reconstruction is of great importance for environmental and urban applications. Airborne light detection and ranging (LiDAR is a very useful data source for acquiring detailed geometric and topological information of building objects. In this study, we employed a graph-based method based on hierarchical structure analysis of building contours derived from LiDAR data to reconstruct urban building models. The proposed approach first uses a graph theory-based localized contour tree method to represent the topological structure of buildings, then separates the buildings into different parts by analyzing their topological relationships, and finally reconstructs the building model by integrating all the individual models established through the bipartite graph matching process. Our approach provides a more complete topological and geometrical description of building contours than existing approaches. We evaluated the proposed method by applying it to the Lujiazui region in Shanghai, China, a complex and large urban scene with various types of buildings. The results revealed that complex buildings could be reconstructed successfully with a mean modeling error of 0.32 m. Our proposed method offers a promising solution for 3D building model reconstruction from airborne LiDAR point clouds.
Remote measurement of surface roughness, surface reflectance, and body reflectance with LiDAR.

Science.gov (United States)

Li, Xiaolu; Liang, Yu

2015-10-20

Light detection and ranging (LiDAR) intensity data are attracting increasing attention because of the great potential for use of such data in a variety of remote sensing applications. To fully investigate the data potential for target classification and identification, we carried out a series of experiments with typical urban building materials and employed our reconstructed built-in-lab LiDAR system. Received intensity data were analyzed on the basis of the derived bidirectional reflectance distribution function (BRDF) model and the established integration method. With an improved fitting algorithm, parameters involved in the BRDF model can be obtained to depict the surface characteristics. One of these parameters related to surface roughness was converted to a most used roughness parameter, the arithmetical mean deviation of the roughness profile (Ra), which can be used to validate the feasibility of the BRDF model in surface characterizations and performance evaluations.
Prevalência e características da violência no namoro entre adolescentes escolares de Portugal

Directory of Open Access Journals (Sweden)

Maria Aparecida Beserra

2016-03-01

Full Text Available Resumo Objetivos: Identificar a prevalência de violência no namoro entre adolescentes e discutir a associação entre os comportamentos de violência e as variáveis: idade, sexo e tempo de namoro. Métodos: Estudo transversal epidemiológico. A amostra foi constituída por 1.268 estudantes de ambos os sexos, idades entre 16 e 24 anos, de escolas secundárias de quatro distritos da Região Central de Portugal. Na coleta de dados, foi utilizado um questionário contendo dados sociodemográficos e de comportamentos de vitimização e perpetração de violência no namoro. Resultados: 5,9% do total dos adolescentes referiram envolvimento em situação de violência no namoro. Ambos os sexos relataram uso de violência física. Na violência psicológica, o sexo masculino é o maior perpetrador e vítima. Conclusão: Os resultados apresentaram, em alguns comportamentos, similaridade do padrão de violência entre os sexos, tais como: puxar os cabelos com força; dar uma bofetada; apertar o pescoço; atirar objetos em outra pessoa; dar pontapés e cabeçadas e dar empurrões violentos, indicando, portanto, que mais pesquisas são necessárias para entender que fatores influenciam as diferenças e similaridades desse evento.
Feeding Dar es Salaam: a symbiotic food system perspective

OpenAIRE

Wegerif, Marc C.A.

2017-01-01

This thesis is a sociological analysis of the agri-food system that feeds most of the over four and a half million residents of the fast-growing city of Dar es Salaam in Tanzania. It is based on qualitative research that has generated a picture of the food system that supplies the important foods for the majority of residents of the city. The research took an actor orientated approach and started from urban eaters and then followed the food back through retailers, processors and transporters ...
Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation.

Science.gov (United States)

Silva, Carlos Alberto; Klauberg, Carine; Hudak, Andrew T; Vierling, Lee A; Liesenberg, Veraldo; Bernett, Luiz G; Scheraiber, Clewerson F; Schoeninger, Emerson R

2018-01-01

Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM) and tree density (TD) of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR) data and the non- k-nearest neighbor (k-NN) imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more effective for retrieving height than tree density. The model coefficients of determination (adj.R2) and a root mean squared difference (RMSD) for HD, HM and TD were 0.90, 0.94, 0.38m and 6.99, 5.70, 12.92%, respectively. Our results show that LiDAR and k-NN imputation can be used to predict stand heights with high accuracy in Pinus taeda. However, furthers studies need to be realized to improve the accuracy prediction of TD and to evaluate and compare the cost of acquisition and processing of LiDAR data against the conventional inventory procedures.
Modeling plant composition as community continua in a forest landscape with LiDAR and hyperspectral remote sensing.

Science.gov (United States)

Hakkenberg, C R; Peet, R K; Urban, D L; Song, C

2018-01-01

In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling. © 2017 by the Ecological Society of America.
Effects of the D1 dopamine receptor agonist dihydrexidine (DAR-0100A) on working memory in schizotypal personality disorder.

Science.gov (United States)

Rosell, Daniel R; Zaluda, Lauren C; McClure, Margaret M; Perez-Rodriguez, M Mercedes; Strike, K Sloan; Barch, Deanna M; Harvey, Philip D; Girgis, Ragy R; Hazlett, Erin A; Mailman, Richard B; Abi-Dargham, Anissa; Lieberman, Jeffrey A; Siever, Larry J

2015-01-01

Pharmacological enhancement of prefrontal D1 dopamine receptor function remains a promising therapeutic approach to ameliorate schizophrenia-spectrum working memory deficits, but has yet to be rigorously evaluated clinically. This proof-of-principle study sought to determine whether the active enantiomer of the selective and full D1 receptor agonist dihydrexidine (DAR-0100A) could attenuate working memory impairments in unmedicated patients with schizotypal personality disorder (SPD). We performed a randomized, double-blind, placebo-controlled trial of DAR-0100A (15 mg/150 ml of normal saline administered intravenously over 30 min) in medication-free patients with SPD (n=16) who met the criteria for cognitive impairment (ie, scoring below the 25th percentile on tests of working memory). We employed two measures of verbal working memory that are salient to schizophrenia-spectrum cognitive deficits, and that clinical data implicate as being associated with prefrontal D1 availability: (1) the Paced Auditory Serial Addition Test (PASAT); and (2) the N-back test (ratio of 2-back:0-back scores). Study procedures occurred over four consecutive days, with working memory testing on Days 1 and 4, and DAR-0100A/placebo administration on Days 2-4. Treatment with DAR-0100A was associated with significantly improved PASAT performance relative to placebo, with a very large effect size (Cohen's d=1.14). Performance on the N-back ratio was also significantly improved; however, this effect rested on both a non-significant enhancement and diminution of 2-back and 0-back performance, respectively; therefore interpretation of this finding is more complicated. DAR-0100A was generally well tolerated, with no serious medical or psychiatric adverse events; common side effects were mild to moderate and transient, consisting mainly of sedation, lightheadedness, tachycardia, and hypotension; however, we were able to minimize these effects, without altering the dose, with supportive
Optimizing the Use of LiDAR for Hydraulic and Sediment Transport Model Development: Case Studies from Marin and Sonoma Counties, CA

Science.gov (United States)

Kobor, J. S.; O'Connor, M. D.; Sherwood, M. N.

2013-12-01

Effective floodplain management and restoration requires a detailed understanding of floodplain processes not readily achieved using standard one-dimensional hydraulic modeling approaches. The application of more advanced numerical models is, however, often limited by the relatively high costs of acquiring the high-resolution topographic data needed for model development using traditional surveying methods. The increasing availability of LiDAR data has the potential to significantly reduce these costs and thus facilitate application of multi-dimensional hydraulic models where budget constraints would have otherwise prohibited their use. The accuracy and suitability of LiDAR data for supporting model development can vary widely depending on the resolution of channel and floodplain features, the data collection density, and the degree of vegetation canopy interference among other factors. More work is needed to develop guidelines for evaluating LiDAR accuracy and determining when and how best the data can be used to support numerical modeling activities. Here we present two recent case studies where LiDAR datasets were used to support floodplain and sediment transport modeling efforts. One LiDAR dataset was collected with a relatively low point density and used to study a small stream channel in coastal Marin County and a second dataset was collected with a higher point density and applied to a larger stream channel in western Sonoma County. Traditional topographic surveying was performed at both sites which provided a quantitative means of evaluating the LiDAR accuracy. We found that with the lower point density dataset, the accuracy of the LiDAR varied significantly between the active stream channel and floodplain whereas the accuracy across the channel/floodplain interface was more uniform with the higher density dataset. Accuracy also varied widely as a function of the density of the riparian vegetation canopy. We found that coupled 1- and 2-dimensional hydraulic
Predicting forest height using the GOST, Landsat 7 ETM+, and airborne LiDAR for sloping terrains in the Greater Khingan Mountains of China

Science.gov (United States)

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

2018-03-01

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

Science.gov (United States)

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

2014-01-01

Vegetation structure quantified by light detection and ranging (LiDAR) can improve understanding of wildlife occupancy and species-richness patterns. However, there is often a time lag between the collection of LiDAR data and wildlife data. We investigated whether a time lag between the LiDAR acquisition and field-data acquisition affected mapped wildlife distributions...
Fachagentur Nachwachsende Rohstoffe e.V. (FNR). Annual report 1999/2000; Fachagentur Nachwachsende Rohstoffe e.V. (FNR). Jahresbericht 1999/2000

Energy Technology Data Exchange (ETDEWEB)

Schuette, A.

2001-07-01

The annual report of the Fachagentur Nachwachsende Rohstoffe e.V. outlines the state of the art and the boundary conditions of energy plant utilisation. The organisational struture of the association and its research projects are presented. [German] Der Jahresbericht der Fachagentur Nachwachsende Rohstoffe e.V. stellt Stand der Technik und Rahmenbedingungen fuer die Verwendung von Energiepflanzen dar. Die Organisation des Vereins sowie die gefoerderten Forschungsprojekte werden vorgestellt.
Modeling commuter preferences for the proposed bus rapid transit in Dar-es-Salaam

NARCIS (Netherlands)

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

2012-01-01

The paper analyzes individual commuter preferences towards the proposed bus rapid transit (BRT) system in Dar-es-Salaam, Tanzania. The objective of the survey was to identify how commuters perceive and value the proposed BRT service quality attributes. A stated preference survey of potential users
Quantifying Soil Carbon Change from Wildfires in Peatland Ecosystems of the Eastern United States Using Repeat LiDAR

Science.gov (United States)

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

2013-12-01

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

Evaluation of Some Physiochemical Parameters and Heavy Metal Contamination in Hara Biosphere Reserve, Iran, Using a New Pollution Index Approach

Directory of Open Access Journals (Sweden)

Iman Zarei

2016-07-01

Full Text Available Background: The pollution of the aquatic environment with heavy metals has become a worldwide problem during recent years, due to their potential toxic effects and ability to bio-accumulate in aquatic ecosystems. Heavy metals are sensitive indicators for monitoring changes in the aquatic environment. Methods: In this study, total concentrations of Cr, Pb, Cu, Zn, and Fe were measured in water and sediments from nine sites, based on ecological conditions and human activities and the effects of sediment pH and sediment organic matter on bioavailability of selected metals were determined. Modified degree of contamination (mCd was computed in order to determine anthropogenically derived sediment contamination. Results: Mean concentration of metals in water found to be in the following order: Pb > Fe > Zn > Cu > Cr, while in sediment samples it was Fe > Cr > Zn > Pb > Cu. The average content of examined metals in water was higher than the chronic values in marine surface water guideline values. Mean content of Cr, Pb and Fe in sediments were higher than average of the less contaminated sample but Cu and Zn were lower than this guideline value. In the study area, mCd values were less than 1.5 with values ranging from 0.71 to 1.02. Conclusion: The results of this study indicated with a decrease in organic matter and pH in sediments, the concentration of copper and iron increased. Base on modified contamination degree, the sediments of Hara Biosphere Reserve are considered to be in the zero to very low contamination status.
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.
Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure.

Science.gov (United States)

Lin, Yi; Jiang, Miao; Pellikka, Petri; Heiskanen, Janne

2018-01-01

Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology-light detection and ranging (LiDAR). Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs) into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics.
Air pollution by motor traffic in Dar-es-Salaam. Measurements and state of the art description

Energy Technology Data Exchange (ETDEWEB)

Henricson, Daniel

1999-06-01

Dar-es-Salaam was the capital of Tanzania until 1973, when it was moved to Dodoma. The city is still the largest and holds about 1.6 million inhabitants. The aim of the project is to measure air pollution from traffic close to people and set a foundation for future studies. Besides that finding ways to reduce air pollution and improve traffic situation in Dar-es-Salaam with an emphasis on the central city parts. Previous studies on air pollution in Dar-es-Salaam have all been rather rushed and mostly with old and not very precise equipment. For that reason you could say this project is like a pilot study. Measurements were made on NO, NO{sub 2}, SO{sub 2}, O{sub 3}, and VOC (hydrocarbons) during two different measuring weeks. Average temperature, wind velocity and traffic flow was measured on both weeks. Traffic flow was 12 000 vehicles/day. The percentage of accelerating/retarding vehicles and average speed was also studied. Average speed was 20 km/h. The result above show levels somewhat exceeding the guidelines. The levels can not be said to be alarmingly high, but bearing the rapid increase in the number of vehicles in mind, air pollution will soon be a major problem. It would have been preferred to also measure lead, particles and carbon monoxide, especially particles since previous reports indicates very high levels. To create a better air quality in Dar-es-Salaam there has to be an improvement of public transport and at the same time increased parking fees and fuel prices. Finally, fuel quality has to improve and unleaded petrol has to be introduced as soon as possible 10 refs, 4 figs, 15 tabs
FREUD E A MAÇONARIA

OpenAIRE

Carvalho, William Almeida

2014-01-01

O autor visa dar uma ideia sobre Freud na Maçonaria judaica: a B´nai B´rith. Diferenças e semelhanças entre a Maçonaria judaica e a Maçonaria tradicional. Sua iniciação, seus trabalhos apresentados em Loja. Uma breve visão sobre a b´nai b´rith no mundo e no Brasil e seu papel para a comunidade judaica. Cita os diversos trabalhos de Freud apresentados previamente em Loja e um texto sobre o que pensa da Maçonaria judaica. Encerra com uma visão de Einstein sobre a psicanálise.
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.
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...
Development of DArT markers and assessment of diversity in Fusarium oxysporum f. sp. ciceris, wilt pathogen of chickpea (Cicer arietinum L.).

Science.gov (United States)

Sharma, Mamta; Nagavardhini, Avuthu; Thudi, Mahendar; Ghosh, Raju; Pande, Suresh; Varshney, Rajeev K

2014-06-10

Fusarium oxysporum f. sp. ciceris (Foc), the causal agent of Fusarium wilt of chickpea is highly variable and frequent recurrence of virulent forms have affected chickpea production and exhausted valuable genetic resources. The severity and yield losses of Fusarium wilt differ from place to place owing to existence of physiological races among isolates. Diversity study of fungal population associated with a disease plays a major role in understanding and devising better disease control strategies. The advantages of using molecular markers to understand the distribution of genetic diversity in Foc populations is well understood. The recent development of Diversity Arrays Technology (DArT) offers new possibilities to study the diversity in pathogen population. In this study, we developed DArT markers for Foc population, analysed the genetic diversity existing within and among Foc isolates, compared the genotypic and phenotypic diversity and infer the race scenario of Foc in India. We report the successful development of DArT markers for Foc and their utility in genotyping of Foc collections representing five chickpea growing agro-ecological zones of India. The DArT arrays revealed a total 1,813 polymorphic markers with an average genotyping call rate of 91.16% and a scoring reproducibility of 100%. Cluster analysis, principal coordinate analysis and population structure indicated that the different isolates of Foc were partially classified based on geographical source. Diversity in Foc population was compared with the phenotypic variability and it was found that DArT markers were able to group the isolates consistent with its virulence group. A number of race-specific unique and rare alleles were also detected. The present study generated significant information in terms of pathogenic and genetic diversity of Foc which could be used further for development and deployment of region-specific resistant cultivars of chickpea. The DArT markers were proved to be a powerful
Modelling canopy fuel and forest stand variables and characterizing the influence of thinning in the stand structure using airborne LiDAR

Directory of Open Access Journals (Sweden)

A. Hevia

2016-02-01

Full Text Available Forest fires are a major threat in NW Spain. The importance and frequency of these events in the area suggests the need for fuel management programs to reduce the spread and severity of forest fires. Thinning treatments can contribute for fire risk reduction, because they cut off the horizontal continuity of forest fuels. Besides, it is necessary to conduct a fire risk management based on the knowledge of fuel allocation, since fire behaviour and fire spread study is dependent on the spatial factor. Therefore, mapping fuel for different silvicultural scenarios is essential. Modelling forest variables and forest structure parameters from LiDAR technology is the starting point for developing spatially explicit maps. This is essential in the generation of fuel maps since field measurements of canopy fuel variables is not feasible. In the present study, we evaluated the potential of LiDAR technology to estimate canopy fuel variables and other stand variables, as well as to identify structural differences between silvicultural managed and unmanaged P. pinaster Ait. stands. Independent variables (LiDAR metrics of greater explanatory significance were identified and regression analyses indicated strong relationships between those and field-derived variables (R2 varied between 0.86 and 0.97. Significant differences were found in some LiDAR metrics when compared thinned and unthinned stands. Results showed that LiDAR technology allows to model canopy fuel and stand variables with high precision in this species, and provides useful information for identifying areas with and without silvicultural management.
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)
Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation

Directory of Open Access Journals (Sweden)

CARLOS ALBERTO SILVA

Full Text Available ABSTRACT Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM and tree density (TD of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR data and the non- k-nearest neighbor (k-NN imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more effective for retrieving height than tree density. The model coefficients of determination (adj.R2 and a root mean squared difference (RMSD for HD, HM and TD were 0.90, 0.94, 0.38m and 6.99, 5.70, 12.92%, respectively. Our results show that LiDAR and k-NN imputation can be used to predict stand heights with high accuracy in Pinus taeda. However, furthers studies need to be realized to improve the accuracy prediction of TD and to evaluate and compare the cost of acquisition and processing of LiDAR data against the conventional inventory procedures.
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...
Peegeldus ajas : aja, ruumi ja vormi kohtumispaik / Kaja Tooming

Index Scriptorium Estoniae

Tooming, Kaja

2002-01-01

Näited: Kimiyo Mishima skulptuur "Newspaper 84 - E" (1984) Hara Muuseumi aias Tokyos, Miyajima Tatsuo installatiivne teos "Keep Change, Connect with Everything, Continue Forever" (1998), Kyoto Kiyomizudera templi budistliku kalmistu hauakivid
Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

Directory of Open Access Journals (Sweden)

Dengsheng Lu

2012-01-01

Full Text Available Landsat Thematic mapper (TM image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonstrates the forest biomass estimation methods and uncertainty analysis. Results indicate that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems. LiDAR can overcome TM’s shortcoming providing better biomass estimation performance but has not been extensively applied in practice due to data availability constraints. The uncertainty analysis indicates that various sources affect the performance of forest biomass/carbon estimation. With that said, the clear dominate sources of uncertainty are the variation of input sample plot data and data saturation problem related to optical sensors. A possible solution to increasing the confidence in forest biomass estimates is to integrate the strengths of multisensor data.
An Online Solution of LiDAR Scan Matching Aided Inertial Navigation System for Indoor Mobile Mapping

Directory of Open Access Journals (Sweden)

Xiaoji Niu

2017-01-01

Full Text Available Multisensors (LiDAR/IMU/CAMERA integrated Simultaneous Location and Mapping (SLAM technology for navigation and mobile mapping in a GNSS-denied environment, such as indoor areas, dense forests, or urban canyons, becomes a promising solution. An online (real-time version of such system can extremely extend its applications, especially for indoor mobile mapping. However, the real-time response issue of multisensors is a big challenge for an online SLAM system, due to the different sampling frequencies and processing time of different algorithms. In this paper, an online Extended Kalman Filter (EKF integrated algorithm of LiDAR scan matching and IMU mechanization for Unmanned Ground Vehicle (UGV indoor navigation system is introduced. Since LiDAR scan matching is considerably more time consuming than the IMU mechanism, the real-time synchronous issue is solved via a one-step-error-state-transition method in EKF. Stationary and dynamic field tests had been performed using a UGV platform along typical corridor of office building. Compared to the traditional sequential postprocessed EKF algorithm, the proposed method can significantly mitigate the time delay of navigation outputs under the premise of guaranteeing the positioning accuracy, which can be used as an online navigation solution for indoor mobile mapping.
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.
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.
Application of Airborne LiDAR to the Determination of the Height of Large Structures. Case Study: Dams

Directory of Open Access Journals (Sweden)

Rubén Martínez Marín

2014-01-01

Full Text Available La mejor forma de calcular la altura de una presa es realizar una nivelación geométrica de precisión. No obstante, este método es demandante y costoso. La precisión de los datos obtenidos ha mejorado sustancialmente, esta tecnología puede proveer precisiones de 2 a 3 centímetros, más que suficiente para determinar la altura de presa y utilizar ésta como dato de partida para cualquier actividad posterior que así lo requiera. La densidad de adquisición de los datos LiDAR (Light Detection and Ranging es importante para establecer la bondad de los resultados. Finalmente, como los sistemas LiDAR aerotransportados están basados en alturas elipsoidales, es necesario transformarlas a ortométricas. Este trabajo muestra los resultados obtenidos usando un LiDAR de baja densidad (0.5 pts/m2 y su validación con observaciones GPS (Global Positioning System en postproceso. Los resultados demuestran que se puede obtener una precisión del orden de 10-25 cm, suficiente para la mayoría de las actividades relacionadas con la ingeniería civil.
Espiritualidade, religiosidade e psicoterapia Spirituality, religiousness and psychotherapy

OpenAIRE

Julio Fernando Prieto Peres; Manoel José Pereira Simão; Antonia Gladys Nasello

2007-01-01

Crenças e práticas religiosas/espirituais constituem uma parte importante da cultura e dos princípios utilizados para dar forma a julgamentos e ao processamento de informações. O conhecimento e a valorização de tais sistemas de crenças colaboram com a aderência do indivíduo à psicoterapia e promovem melhores resultados. Contudo, nem todas as abordagens encontraram um ajuste desse tema em suas intervenções e os diversos conceitos sobre religiosidade/espiritualidade dificultam essa importante i...
Effect of urban design on microclimate and thermal comfort outdoors in warm-humid Dar es Salaam, Tanzania

Science.gov (United States)

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

2018-03-01

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

Influence of Functionality on Direct Arylation of Model Systems as a Route Toward Fluorinated Copolymers via Direct Arylation Polymerization (DArP)

DEFF Research Database (Denmark)

Livi, Francesco; Gobalasingham, Nemal S.; Bundgaard, Eva

2015-01-01

A screening of direct arylation conditions on amodel small molecule system is carried out to develop suitableconditions for the direct arylation polymerization (DArP) of fluorinatedcopolymers, which are incompatible with conditionspreviously utilized successfully for nonfluorinated systems. Themo......,4-phenylene)dithiophene. Polymers arefree of β-defects and significant homocoupling. This work furtherunderscores the attractive simplicity, relevance, and easeof DArP while reconfirming its broad compatibility withincreasingly popular fluorinated copolymers....
A Browning process : The case of Dar es Salaam city

OpenAIRE

Mng'ong'o, Othmar Simtali

2005-01-01

The study is about how green spaces and structures of Dar es Salaam city, quantitatively and qualitatively, are browning out. It also tries to explore the different reasons behind the browning tendency, and what it means to the function of the city and to the daily form of life of the inhabitants. Finally there is a discussion about how to counteract the tendency by involving the inhabitants in planning procedures following the communicative approach to planning. The main investigations have ...
Humor e ensino: J. Carlos e a caricatura no Ensino de História

Directory of Open Access Journals (Sweden)

Daniela Cardoso da Silva

2009-07-01

Full Text Available O propósito deste artigo é dar um breve histórico da caricatura, analisando-a como instrumento para o Ensino de História, apontando como acontece este diálogo entre a arte caricata de J.Carlos no período chamado Estado Novo, sua representação de mundo e o ensino de História.
Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure

Directory of Open Access Journals (Sweden)

Yi Lin

2018-02-01

Full Text Available Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology—light detection and ranging (LiDAR. Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics.
Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 3 : advanced consideration in LiDAR technology for bridge evaluation.

Science.gov (United States)

2012-03-01

This report describes Phase Two enhancement of terrestrial LiDAR scanning for bridge damage : evaluation that was initially developed in Phase One. Considering the spatial and reflectivity : information contained in LiDAR scans, two detection algorit...
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...
29 CFR 4.116 - Contracts for construction activity.

Science.gov (United States)

2010-07-01

... McNamara-O'Hara Service Contract Act Specific Exclusions § 4.116 Contracts for construction activity. (a... McNamara-O'Hara Service Contract Act indicates that the purpose of the provision is to avoid overlapping coverage of the two acts by excluding from the application of the McNamara-O'Hara Act those contracts to...
Intestinal Parasitic Infections in Bahir Dar and Risk Factors for Transmission

OpenAIRE

Erko, Berhanu; Medhin, Girmay; Birrie, Hailu

1995-01-01

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

Science.gov (United States)

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

2018-05-01

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

Science.gov (United States)

2012-01-01

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

African Journals Online (AJOL)

A retrospective study was carried out to assess the effect of El Nino on trypanosome infection in cattle. Trypanosome infection was monitored in free grazing dairy cattle before and after El Nino in Dar es Salaam. The study involved 49 smallholder dairy herds with a total of 570 dairy cattle. Trypanosomes were identified by ...
Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase one, volume 3 : use of scanning LiDAR in structural evaluation of bridges.

Science.gov (United States)

2009-12-01

This volume introduces several applications of remote bridge inspection technologies studied in : this Integrated Remote Sensing and Visualization (IRSV) study using ground-based LiDAR : systems. In particular, the application of terrestrial LiDAR fo...
Feiras e mercados no Porto: velhos e novos formatos de atividade económica e animação urbana

Directory of Open Access Journals (Sweden)

Célia Ferreira

2015-12-01

Full Text Available Apesar da escassez de literatura científica sobre feiras e mercados urbanos, esta atividade económica é reconhecida por instituições internacionais e organismos locais como uma força motriz do desenvolvimento económico local e das vivências e animação urbanas. Com esta pesquisa pretende-se dar um contributo para a investigação nesta área, através da análise dos mercados e feiras existentes oficialmente na cidade do Porto. A abordagem metodológica assenta na observação, na realização de um conjunto de entrevistas e em fontes complementares. O objetivo é analisar os formatos, as características, as parcerias, o envolvimento com a comunidade local e as estratégias de marketing e comunicação das feiras e mercados urbanos.
Identifying Ancient Settlement Patterns through LiDAR in the Mosquitia Region of Honduras.

Directory of Open Access Journals (Sweden)

Christopher T Fisher

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

OpenAIRE

Bulamile, Ludigija Boniface

2009-01-01

HTML clipboardThis study is about Homeowner’s architectural responses to crime in Dar es Salaam Tanzania: its impacts and implications to urban architecture, urban design and urban management. The study explores and examines the processes through which homeowners respond to crimes of burglary, home robbery and fear of it using architectural or physical elements. The processes are explored and examined using case study methodology in three cases in Dar es Salaam. The cases are residentia...
Adjustment of Measurements with Multiplicative Errors: Error Analysis, Estimates of the Variance of Unit Weight, and Effect on Volume Estimation from LiDAR-Type Digital Elevation Models

Directory of Open Access Journals (Sweden)

Yun Shi

2014-01-01

Full Text Available Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM.

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

Science.gov (United States)

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

2018-03-01

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

Science.gov (United States)

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

2014-12-01

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

Directory of Open Access Journals (Sweden)

Elisabetta Menetti

2015-06-01

Full Text Available A fantasia no Decameron de Giovanni Boccaccio entre fabula e historia, deve medir-se imediatamente com as consequências da estreita relação, estabelecida desde a antiguidade, entre invenção e verdade, dando origem a um texto em que o mundo real dialoga com o maravilhoso e o extraordinário na criação de outros mundos, pelos quais viaja o grupo dos dez narradores. Pode-se verificar ainda como a literatura para Boccaccio, que apresenta sua teoria sobre a escrita em seu Genealogia deorum gentilium é locutio sub figmento capaz de dar vida - por admirável tensão criativa – a um mundo novo de palavras
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
Key events and their effects on cycling behaviour in Dar-es-Salaam : abstract + powerpoint

NARCIS (Netherlands)

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

2012-01-01

The paper explores key events and investigates their effects on cycling behaviour in the city of Dar-es-Salaam, Tanzania. The objective of the study is to identify specific key events during a person’s life course with a significant effect on change of travel behaviour towards cycling in relation to
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...
Changes in allelic frequency over time in European bread wheat (Triticum aestivum L.) varieties revealed using DArT and SSR markers

DEFF Research Database (Denmark)

Orabi, Jihad; Jahoor, Ahmed; Backes, Gunter Martin

2014-01-01

A collection of 189 bread wheat landraces and cultivars, primarily of European origin, released between 1886 and 2009, was analyzed using two DNA marker systems. A set of 76 SSR markers and ~7,000 DArT markers distributed across the wheat genome were employed in these analyses. All of the SSR...... markers were found to be polymorphic, whereas only 2,532 of the ~7,000 DArT markers were polymorphic. A Mantel test between the genetic distances calculated based on the SSR and DArT data showed a strong positive correlation between the two marker types, with a Pearson's value (r) of 0.66. We assessed...... the genetic diversity and allelic frequencies among the accessions based on spring- versus winter-wheat type as well as between landraces and cultivars. We also analyzed the changes in genetic diversity and allelic frequencies in these samples over time. We observed separation based on both vernalization type...
Genetic mapping using the Diversity Arrays Technology (DArT) : application and validation using the whole-genome sequences of Arabidopsis thaliana and the fungal wheat pathogen Mycosphaerella graminicola

NARCIS (Netherlands)

Wittenberg, A.H.J.

2007-01-01

Diversity Arrays Technology (DArT) is a microarray-based DNA marker technique for genome-wide discovery and genotyping of genetic variation. DArT allows simultaneous scoring of hundreds- to thousands of restriction site based polymorphisms between genotypes and does not require DNA sequence
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
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...
Archaeological application of airborne LiDAR to examine social changes in the Ceibal region of the Maya lowlands

Science.gov (United States)

Triadan, Daniela; Pinzón, Flory; Burham, Melissa; Ranchos, José Luis; Aoyama, Kazuo; Haraguchi, Tsuyoshi

2018-01-01

Although the application of LiDAR has made significant contributions to archaeology, LiDAR only provides a synchronic view of the current topography. An important challenge for researchers is to extract diachronic information over typically extensive LiDAR-surveyed areas in an efficient manner. By applying an architectural chronology obtained from intensive excavations at the site center and by complementing it with surface collection and test excavations in peripheral zones, we analyze LiDAR data over an area of 470 km2 to trace social changes through time in the Ceibal region, Guatemala, of the Maya lowlands. We refine estimates of structure counts and populations by applying commission and omission error rates calculated from the results of ground-truthing. Although the results of our study need to be tested and refined with additional research in the future, they provide an initial understanding of social processes over a wide area. Ceibal appears to have served as the only ceremonial complex in the region during the transition to sedentism at the beginning of the Middle Preclassic period (c. 1000 BC). As a more sedentary way of life was accepted during the late part of the Middle Preclassic period and the initial Late Preclassic period (600–300 BC), more ceremonial assemblages were constructed outside the Ceibal center, possibly symbolizing the local groups’ claim to surrounding agricultural lands. From the middle Late Preclassic to the initial Early Classic period (300 BC-AD 300), a significant number of pyramidal complexes were probably built. Their high concentration in the Ceibal center probably reflects increasing political centralization. After a demographic decline during the rest of the Early Classic period, the population in the Ceibal region reached the highest level during the Late and Terminal Classic periods, when dynastic rule was well established (AD 600–950). PMID:29466384
Archaeological application of airborne LiDAR to examine social changes in the Ceibal region of the Maya lowlands.

Directory of Open Access Journals (Sweden)

Takeshi Inomata

Full Text Available Although the application of LiDAR has made significant contributions to archaeology, LiDAR only provides a synchronic view of the current topography. An important challenge for researchers is to extract diachronic information over typically extensive LiDAR-surveyed areas in an efficient manner. By applying an architectural chronology obtained from intensive excavations at the site center and by complementing it with surface collection and test excavations in peripheral zones, we analyze LiDAR data over an area of 470 km2 to trace social changes through time in the Ceibal region, Guatemala, of the Maya lowlands. We refine estimates of structure counts and populations by applying commission and omission error rates calculated from the results of ground-truthing. Although the results of our study need to be tested and refined with additional research in the future, they provide an initial understanding of social processes over a wide area. Ceibal appears to have served as the only ceremonial complex in the region during the transition to sedentism at the beginning of the Middle Preclassic period (c. 1000 BC. As a more sedentary way of life was accepted during the late part of the Middle Preclassic period and the initial Late Preclassic period (600-300 BC, more ceremonial assemblages were constructed outside the Ceibal center, possibly symbolizing the local groups' claim to surrounding agricultural lands. From the middle Late Preclassic to the initial Early Classic period (300 BC-AD 300, a significant number of pyramidal complexes were probably built. Their high concentration in the Ceibal center probably reflects increasing political centralization. After a demographic decline during the rest of the Early Classic period, the population in the Ceibal region reached the highest level during the Late and Terminal Classic periods, when dynastic rule was well established (AD 600-950.
Archaeological application of airborne LiDAR to examine social changes in the Ceibal region of the Maya lowlands.

Science.gov (United States)

Inomata, Takeshi; Triadan, Daniela; Pinzón, Flory; Burham, Melissa; Ranchos, José Luis; Aoyama, Kazuo; Haraguchi, Tsuyoshi

2018-01-01

Although the application of LiDAR has made significant contributions to archaeology, LiDAR only provides a synchronic view of the current topography. An important challenge for researchers is to extract diachronic information over typically extensive LiDAR-surveyed areas in an efficient manner. By applying an architectural chronology obtained from intensive excavations at the site center and by complementing it with surface collection and test excavations in peripheral zones, we analyze LiDAR data over an area of 470 km2 to trace social changes through time in the Ceibal region, Guatemala, of the Maya lowlands. We refine estimates of structure counts and populations by applying commission and omission error rates calculated from the results of ground-truthing. Although the results of our study need to be tested and refined with additional research in the future, they provide an initial understanding of social processes over a wide area. Ceibal appears to have served as the only ceremonial complex in the region during the transition to sedentism at the beginning of the Middle Preclassic period (c. 1000 BC). As a more sedentary way of life was accepted during the late part of the Middle Preclassic period and the initial Late Preclassic period (600-300 BC), more ceremonial assemblages were constructed outside the Ceibal center, possibly symbolizing the local groups' claim to surrounding agricultural lands. From the middle Late Preclassic to the initial Early Classic period (300 BC-AD 300), a significant number of pyramidal complexes were probably built. Their high concentration in the Ceibal center probably reflects increasing political centralization. After a demographic decline during the rest of the Early Classic period, the population in the Ceibal region reached the highest level during the Late and Terminal Classic periods, when dynastic rule was well established (AD 600-950).
Application of LiDAR technology in analyses of the topography of Margum/Morava and Kulič

Directory of Open Access Journals (Sweden)

Ivanišević Vujadin

2012-01-01

often believed that this fortification was originally built in Roman times, but the analyses of DTM have shown the fort erected on an embankment, round in shape, i.e. on the more elevated terrain in comparsion to the largest part of the confluence area, where most of Roman Margum and Mediaeval Morava has been wiped out by water. So the Kulič fortification could have been originally erected only afterwords, i.e. in Turkish times. There are some data from the written sources to corroborate such a date, and we also know of two later accounts describing the 17th century settlement in front of it. There has been no field confirmation so far, but thanks to the results of LiDAR scanning one may observe the traces of a small settlement south of the fortification, protected by a trench. [Projekat Ministarstva nauke Republike Srbije, br. 177021: ArchaeoLandscapes Europe i Procesi urbanizacije i razvoja srednjovekovnog društva
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.…
Linking rainforest ecophysiology and microclimate through fusion of airborne LiDAR and hyperspectral imagery

Science.gov (United States)

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

2014-01-01

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

Science.gov (United States)

Yan, Li; Li, Zan; Liu, Hua; Tan, Junxiang; Zhao, Sainan; Chen, Changjun

2017-12-01

Mobile LiDAR Scanning (MLS) can collect 3-dimensional (3D) road and road-related geospatial information accurately and efficiently. Pole-like objects located in road environment are important street furniture and they are necessary information in road inventory and road mapping. The automatic detection and classification of pole-like road objects from mobile LiDAR data can greatly reduce the cost and improve the efficiency. This paper provides a complete workflow for the detection and classification of pole-like road objects from mobile LiDAR data in motorway environment. The major workflow includes three steps: data preprocessing, pole-like road objects detection and pole-like road objects classification. In data preprocessing step, ground points are removed by an automatic ground filtering algorithm, and then off-ground points are clustered into segments and the overlapped segments containing pole-like road objects are further separated through an iterative min-cut based segmentation approach. In detection step, filters utilizing both prior and shape information are used to detect the target objects. In classification step, features of objects are calculated and classified using Random Forest classifier. Our method was tested on two datasets scanned in motorway environment, and the results showed that the Matthews correlation coefficient of the two datasets in detection step was 93.7% and 95.9% respectively and the overall accuracy of the two datasets in classification step was 96.5% and 97.9% respectively.
Monitoring the Distribution and Dynamics of an Invasive Grass in Tropical Savanna Using Airborne LiDAR

Directory of Open Access Journals (Sweden)

Shaun R. Levick

2015-04-01

Full Text Available The spread of an alien invasive grass (gamba grass—Andropogon gayanus in the tropical savannas of Northern Australia is a major threat to habitat quality and biodiversity in the region, primarily through its influence on fire intensity. Effective control and eradication of this invader requires better insight into its spatial distribution and rate of spread to inform management actions. We used full-waveform airborne LiDAR to map areas of known A. gayanus invasion in the Batchelor region of the Northern Territory, Australia. Our stratified sampling campaign included wooded savanna areas with differing degrees of A. gayanus invasion and adjacent areas of native grass and woody tree mixtures. We used height and spatial contiguity based metrics to classify returns from A. gayanus and developed spatial representations of A. gayanus occurrence (1 m resolution and canopy cover (10 m resolution. The cover classification proved robust against two independent field-based investigations at 500 m2 (R2 = 0.87, RMSE = 12.53 and 100 m2 (R2 = 0.79, RMSE = 14.13 scale. Our mapping results provide a solid benchmark for evaluating the rate and pattern of A. gayanus spread from future LiDAR campaigns. In addition, this high-resolution mapping can be used to inform satellite image analysis for the evaluation of A. gayanus invasion over broader regional scales. Our research highlights the huge potential that airborne LiDAR holds for facilitating the monitoring and management of savanna habitat condition.
Prevalence of equine Piroplasmosis and its association with tick infestation in the State of São Paulo, Brazil Prevalência da Piroplasmose equina e sua associação com infestação por carrapatos no Estado de São Paulo

Directory of Open Access Journals (Sweden)

Claudia E. Kerber

2009-12-01

Full Text Available Serum samples were collected from 582 horses from 40 stud farms in the State of São Paulo and tick (Acari: Ixodidae infestations were evaluated on them. Serum samples were subjected to the complement fixation test (CFT and a competitive inhibition ELISA (cELISA for Babesia caballi and Theileria equi. Logistic regression analyses were performed to construct multivariate models that could explain the dependent variable (horses positive for B. caballi or T. equi as a function of the independent variables (presence or abundance of each one of the tick species found on the farms. A higher overall prevalence of B. caballi (54.1% than of T. equi (21.6% was found by the two tests. The ticks Dermacentor nitens Neumann, 1897, Amblyomma cajennense (Fabricius, 1787 and Rhipicephalus (Boophilus microplus (Canestrini, 1887 were present on horses on 38 (95%, 20 (50%, and 4 (10% farms, respectively. Infestations by D. nitens were statistically associated with B. caballi-positive horses on the farms by either the CFT or cELISA. Infestations by A. cajennense were statistically associated with T. equi-positive horses on the farms by either CFT or cELISA.Amostras de soro sanguineo foram coletadas de 582 equinos de 40 haras no estado de São Paulo, onde as infestações por carrapatos foram avaliadas nos animais. Os soros foram testados por reação de fixação do complemento (RFC e ELISA competitivo por inibição (cELISA com antígenos de Babesia caballi e Theileria equi. Análises de regressão logística foram realizadas para construir modelos multivariados que pudessem explicar as variáveis dependentes (equinos positivos para B. caballi ou T. equi em função de variáveis independentes (presença e abundância de cada uma das espécies de carrapatos encontradas nos equinos dos haras. Em geral, os dois testes sorológicos indicaram uma prevalência maior para B. caballi (54,1% do que para T. equi (21,6%. Os carrapatos Dermacentor nitens Neumann, 1897

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