Round-bale feeder design affects hay waste and economics during horse feeding.

PubMed

Martinson, K; Wilson, J; Cleary, K; Lazarus, W; Thomas, W; Hathaway, M

2012-03-01

Many horse owners find round bales convenient, less labor intensive, and more affordable than other hay types, but report an inability to control horse BW gain and excessive hay waste. The objectives were to compare hay waste, hay intake, and payback of 9 round-bale feeders and a no-feeder control when used during horse feeding. Nine round-bale feeders were tested: Cinch Net, Cone, Covered Cradle, Hayhut, Hay Sleigh, Ring, Tombstone, Tombstone Saver, and Waste Less. Each feeder design was placed on the ground in a dirt paddock. Five groups of 5 horses were fed in rotation for a 4-d period with each feeder. Every fourth day, groups were rotated among paddocks and a new round bale was placed in each feeder. In the 5 paddocks used, 5 feeders were installed for d 1 through 20, and the remaining 4 feeders and no-feeder control were installed for d 21 through 40. Groups of horses were sequentially assigned to feeders using two 5 × 5 Latin squares, the first for d 1 through 20, the second for d 21 through 40. Horse groups of similar age, BW, breed, and sex were formed from 25 Quarter Horse and Thoroughbred geldings and open mares (means: 11 yr; 541 kg of BW). Hay on the ground surrounding the feeder was collected daily, dried, and weighed. The total amount of hay removed around each feeder for a 4-d period was considered waste. Dry matter intake was estimated as the difference between hay disappearance and waste. Number of months for the reduction in waste to repay feeder cost (payback) were calculated using hay valued at $110/t, and improved feeder efficiency over the control. Feeder design did not affect hay intake (P > 0.05); all feeders resulted in an estimated hay intake of 2.0 to 2.4% BW; the no-feeder control resulted in a reduced intake of 1.3% BW (P = 0.001). Mean percentage of hay waste differed among feeders (P < 0.001): Waste Less, 5%; Cinch Net, 6%; Hayhut, 9%; Covered Cradle, 11%; Tombstone Saver, 13%; Tombstone, Cone, and Ring, 19%; Hay Sleigh, 33%; and no

Sampling requirements for forage quality characterization of rectangular hay bales

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

Sheaffer, C.C.; Martin, N.P.; Jewett, J.G.

2000-02-01

Commercial lots of alfalfa (Medicago sativa L.) hay are often bought and sold on the basis of forage quality. Proper sampling is essential to obtain accurate forage quality results for pricing of alfalfa hay, but information about sampling is limited to small, 20- to 40-kg rectangular bales. Their objectives were to determine the within-bale variation in 400-kg rectangular bales and to determine the number and distribution of core samples required to represent the crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), and dry matter (DM) concentration in commercial lots of alfalfa hay. Four bales were selected frommore » each of three hay lots and core sampled nine times per side for a total of 54 cores per bale. There was no consistent pattern of forage quality variation within bales. Averaged across lots, any portion of a bale was highly correlated with bale grand means for CP, ADF, NDF, and DM. Three lots of hay were probed six times per bale, one core per bale side from 55, 14, and 14 bales per lot. For determination of CP, ADF, NDF, and DM concentration, total core numbers required to achieve an acceptable standard error (SE) were minimized by sampling once per bale. Bootstrap analysis of data from the most variable hay lot suggested that forage quality of any lot of 400-kg alfalfa hay bales should be adequately represented by 12 bales sampled once per bale.« less

Substituting oat hay or maize silage for portion of alfalfa hay affects growth performance, ruminal fermentation, and nutrient digestibility of weaned calves

PubMed Central

Zou, Yang; Zou, XinPing; Li, XiZhi; Guo, Gang; Ji, Peng; Wang, Yan; Li, ShengLi; Wang, YaJing; Cao, ZhiJun

2018-01-01

Objective The impact of forage feeding strategy on growth performance, ruminal fermentation and nutrient digestibility in post-weaning calves was investigated. Methods Forty-five female Holstein calves (body weight [BW] = 79.79±0.38 kg) were enrolled in the 35-d study at one week after weaning and randomly assigned to one of three dietary treatments. All diets were fed as total mixed ration containing 60% (dry matter [DM] basis) of basal starter feed and 40% (DM basis) of forage, but varied in composition of forage source including i) alfalfa (40% DM, AH); ii) alfalfa hay (26.7% DM)+oat hay (13.3% DM; OH); iii) alfalfa hay (26.7% DM)+corn silage (13.3% DM; WS). Results Dry matter intake was not different among treatment groups (p>0.05). However, BW (p<0.05) and average daily gain (p<0.05) of calves fed AH and OH were greater than WS-fed calves, whereas heart girth was greater in OH-fed calves than those fed AH and WS (p<0.05). Ruminal fermentation parameters including proportion of butyric acid, acetated-to-propionate ratio, concentration of total volatile fatty acid, protozoal protein, bacterial protein, and microbial protein in rumen were the highest in OH (p<0.05) and the lowest in WS. Compared with the AH and WS, feeding oat hay to postweaning calves increased crude protein digestibility (p<0.05), and decreased duration of diarrhea (p<0.05) and fecal index (p<0.05). Conclusion Our results suggested that partially replacing alfalfa hay with oat hay improved ruminal fermentation, nitrogen utilization, and reduced incidence of diarrhea in post-weaning dairy calves. PMID:28728373

Infrastructure Investment Protection with LiDAR

DOT National Transportation Integrated Search

2012-10-15

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

LiDAR for Air Quality Measurements

DOT National Transportation Integrated Search

2017-02-02

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

LiDAR - An emerging tool for geological applications

USGS Publications Warehouse

Stoker, Jason M.

2012-01-01

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

Processing LiDAR Data to Predict Natural Hazards

NASA Technical Reports Server (NTRS)

Fairweather, Ian; Crabtree, Robert; Hager, Stacey

2008-01-01

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

Influence of feeding hay on the alopecia of breeding guinea pigs.

PubMed

Gerold, S; Huisinga, E; Iglauer, F; Kurzawa, A; Morankic, A; Reimers, S

1997-08-01

Animals with partial alopecia were seen frequently in a breeding colony of guinea pigs. No pathologic aetiology could be determined. An influence of nutrition on the density of the hair coat was considered. Breeding groups were fed one of the commercial guinea pig diets of differing composition, with or without the addition of hay. Observation occurred over a period of months and the quality of the hair coat was evaluated periodically using a semi-quantitative scoring system. More extensive and more frequent fur defects were found is guinea pigs receiving a breeding diet with a high content of crude protein (23%) and a low level of crude fibre (12%), offered hay only restrictively compared with animals receiving a diet with a lower content of crude protein (15.5%) and a higher level of crude fibre (19.5%), offered the same amount of hay. The amount of hay offered is of paramount importance. Animals fed only the diet with the higher level of crude fibre (19.5%), according to the manufacturer's instructions as a complete food, without the addition of hay, showed a less dense hair coat within 4 weeks. In our colony a group of five breeding animals and their young required 200 g of hay daily in order to improve their hair coat quality to normal. Conversely, animals receiving less hay had progressively deteriorating hair coat density. Not only the amount of hay offered, but also the accessibility for all animals plays a role in preventing alopecia in guinea pigs. In larger cages (twice the usual ground surface area) fur defects were seen when the same amount of hay (200 g) was offered in only one central area, rather than spread out evenly throughout the cage. Hair loss was observed to be the result of trichophagia between adult animals kept in the same cage. The need for crude fibre of breeding animals does not appear to be completely met by pellets rich in fibre segments.

Shipborne LiDAR system for coastal change monitoring

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Sheep fed with banana leaf hay reduce ruminal protozoa population.

PubMed

Freitas, Cláudio Eduardo Silva; Duarte, Eduardo Robson; Alves, Dorismar David; Martinele, Isabel; D'Agosto, Marta; Cedrola, Franciane; de Moura Freitas, Angélica Alves; Dos Santos Soares, Franklin Delano; Beltran, Makenzi

2017-04-01

A ciliate protozoa suppression can reduce methane production increasing the energy efficiency utilization by ruminants. The physicochemical characteristics of rumen fluid and the profile of the rumen protozoa populations were evaluated for sheep fed banana leaf hay in replacement of the Cynodon dactylon cv. vaqueiro hay. A total of 30 male sheep were raised in intensive system during 15 days of adaptation and 63 days of experimental period. The animals were distributed in a completely randomized design that included six replicates of five treatments with replacement levels (0, 25, 50, 75, and 100%) of the grass vaquero for the banana leaf hay. Samples of fluid were collected directly from the rumen with sterile catheters. Color, odor, viscosity, and the methylene blue reduction potential (MBRP) were evaluated and pH estimated using a digital potentiometer. After decimal dilutions, counts of genus protozoa were performed in Sedgewick Rafter chambers. The averages of pH, MBRP, color, odor, and viscosity were not influenced by the inclusion of the banana leaf hay. However, the total number of protozoa and Entodinium spp. population significantly decreased at 75 and 100% inclusions of banana leaf hay as roughage.

Tuskegee Airman Lee Hayes

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

Hayes, Lee

2006-08-03

Hayes, a resident of Amagansett who worked at Brookhaven Lab as a custodian from 1958 to 1966, served in an all-black bomber squadron at Tuskegee Army Air Field in Alabama. He was among 994 precedent-breaking black soldiers at Tuskegee who passed rigorous tests between 1942 and 1946 to become pilots in the then-segregated armed forces.

Tuskegee Airman Lee Hayes

ScienceCinema

Hayes, Lee

2017-12-22

Hayes, a resident of Amagansett who worked at Brookhaven Lab as a custodian from 1958 to 1966, served in an all-black bomber squadron at Tuskegee Army Air Field in Alabama. He was among 994 precedent-breaking black soldiers at Tuskegee who passed rigorous tests between 1942 and 1946 to become pilots in the then-segregated armed forces.

The HayWired earthquake scenario—We can outsmart disaster

USGS Publications Warehouse

Hudnut, Kenneth W.; Wein, Anne M.; Cox, Dale A.; Porter, Keith A.; Johnson, Laurie A.; Perry, Suzanne C.; Bruce, Jennifer L.; LaPointe, Drew

2018-04-18

The HayWired earthquake scenario, led by the U.S. Geological Survey (USGS), anticipates the impacts of a hypothetical magnitude-7.0 earthquake on the Hayward Fault. The fault is along the east side of California’s San Francisco Bay and is among the most active and dangerous in the United States, because it runs through a densely urbanized and interconnected region. One way to learn about a large earthquake without experiencing it is to conduct a scientifically realistic scenario. The USGS and its partners in the HayWired Coalition and the HayWired Campaign are working to energize residents and businesses to engage in ongoing and new efforts to prepare the region for such a future earthquake.

64. ELECTRIC MOTOR HAYES STREET POWERHOUSE 1905: Photocopy ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

64. ELECTRIC MOTOR - HAYES STREET POWERHOUSE - 1905: Photocopy of April 1905 photograph showing an early electric motor installation used to drive the winding machinery at the Hayes Street powerhouse of the United Railroads of San Francsico. A portion of the steam engine originally used to power the machinery is visible behind the winding sheave in the left background of the photograph. - San Francisco Cable Railway, Washington & Mason Streets, San Francisco, San Francisco County, CA

Effect of mid-summer haying on growth and reproduction in prairie forbs

Treesearch

Becky Begay; Helen M. Alexander; Erin Questad

2011-01-01

Mid-summer haying is a common management practice for prairies; plant species could differ in the effect of haying on subsequent growth and reproduction. We examined the effect of haying on prairie species by performing a clipping experiment. For each of seven species, sixteen plants were chosen and half were randomly assigned to a clipping treatment and half to a...

A different voice: Mary Hays's the Memoirs of Emma Courtney.

PubMed

Sharma, A

2001-01-01

Mary Hays wrote in the decade of the 1790s, a period of intense creative flowering in England. Writing in a period enshrined to the works of the canonical Wordsworth and Coleridge, Hays explored through her Jacobinical novel, The Memoirs of Emma Courtney, the contentious relationship between self and society. Like other Jacobin women writers - Elizabeth Inchbald, Charlotte Smith and Mary Wollstonecraft - Mary Hays too used her novel to explode the insidious connection between education and gender construction. Emma Courtney is a landmark novel that wrestles with the paradigm of decorum and propriety which disallows women from voicing their aspirations. In the process, Hays merges the plots of the domestic novel of courtship and love with the novel of ideas to create a searing portrait of women's intellectual confinement and psychic dissonance in a society that only projects them in terms of their gender construction. Memoirs of Emma Courtney is a remarkable novel in its depiction of the emotional imbalance created by thwarted desire: intellectual and sexual.

Current best management practices for harvesting and storing dry hay: a research review

USDA-ARS?s Scientific Manuscript database

The production of high-quality grass or legume hays in humid environments is complicated by slower drying rates, and increased probability of rainfall events compared to hay produced under arid climatic conditions. As a result, hay producers in humid environments often face the management dilemma of...

Environmental impact assessment of alfalfa (Medicago sativa L.) hay production.

PubMed

Bacenetti, Jacopo; Lovarelli, Daniela; Tedesco, Doriana; Pretolani, Roberto; Ferrante, Valentina

2018-09-01

On-farm production of hay and high-protein-content feed has several advantages such as diversification of on-farm cultivated crops, reduction of off-farm feed concentrates transported over long distances and a reduction in runoff during the winter season if grown crops are perennial. Among those crops cultivated for high-protein-content feed, alfalfa (Medicago sativa L.) is one of the most important in the Italian context. Nevertheless, up to now, only a few studies have assessed the environmental performance of alfalfa hay production. In this study, using the Life Cycle Assessment approach, the environmental impact of alfalfa hay production in Northern Italy was analyzed. More in detail, two production practices (without and with irrigation) were compared. The results show that alfalfa hay production in irrigated fields has a better environmental performance compared to non-irrigated production, mainly because of the yield increase achieved with irrigation. In particular, for the Climate Change impact category, the impact is equal to 84.54 and 80.21kgCO 2 /t of hay for the scenario without and with irrigation, respectively. However, for two impact categories (Ozone Depletion and Human Toxicity-No Cancer Effect), the impact of irrigation completely offsets the yield increase, and the cultivation practice without irrigation shows the best environmental performance. For both scenarios, the mechanization of harvest is the main environmental hotspot, mostly due to fuel consumption and related combustion emissions. Wide differences were highlighted by comparing the two scenarios with the Ecoinvent process of alfalfa hay production; these differences are mostly due to the cultivation practice and, in particular, to the more intensive fertilization in Swiss production. Copyright © 2018 Elsevier B.V. All rights reserved.

Hay fever & homeopathy: a case series evaluation.

PubMed

Pandey, Vinita

2016-05-01

Seasonal allergic rhinitis (hay fever) is common and can considerably reduce the quality of life of sufferers. Despite the wide everyday application and promising results with homeopathy, scientific evidence of its effectiveness for most ailments is scarce. The assessment of the clinical effectiveness of homeopathic remedies in the alleviation of hay fever symptoms in a typical clinical setting. We performed a clinical observational study of eight patients in the treatment of hay fever symptoms over a two-year period (2012 and 2013) using Measure Yourself Medical Outcome Profile (MYMOP) self-evaluation questionnaires at baseline and again after two weeks and four weeks of homeopathic treatment. The individualized prescription - either a single remedy or multiple remedies - was based on the totality of each patient's symptoms. The average MYMOP scores for the eyes, nose, activity and wellbeing had improved significantly after two and four weeks of homeopathic treatment. The overall average MYMOP profile score at baseline was 3.83 (standard deviation, SD, 0.78). After 14 and 28 days of treatment the average score had fallen to 1.14 (SD, 0.36; P<0.001) and 1.06 (SD, 0.25; P<0.001) respectively. Individualized homeopathic treatment was associated with significant alleviation of hay fever symptoms, enabling the reduction in use of conventional treatment. The results presented in this study can be considered as a step towards a pilot pragmatic study that would use more robust outcome measures and include a larger number of patients prescribed a single or a multiple homeopathic prescription on an individualized basis. Copyright © 2016 The Faculty of Homeopathy. Published by Elsevier Ltd. All rights reserved.

Toxicosis in dairy cattle exposed to poison hemlock (Conium maculatum) in hay: isolation of Conium alkaloids in plants, hay, and urine.

PubMed

Galey, F D; Holstege, D M; Fisher, E G

1992-01-01

Cattle in two herds developed signs of bloating, increased salivation and lacrimation, depression, respiratory distress, ataxia, and death after ingestion of hay that contained large amounts of poison hemlock (Conium maculatum). Twenty of 30 Angus cows and calves were affected in the first herd (2 died). In the second herd, 5 of 30 Holstein heifers were affected (1 died). The Conium alkaloids, coniine and gamma-coniceine, were quantified in the hay, the plants from the responsible hayfield, and the urine of affected animals.

Novel Methods for Measuring LiDAR

NASA Astrophysics Data System (ADS)

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

Raster Vs. Point Cloud LiDAR Data Classification

NASA Astrophysics Data System (ADS)

El-Ashmawy, N.; Shaker, A.

2014-09-01

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

Waveform LiDAR across forest biomass gradients

NASA Astrophysics Data System (ADS)

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

2011-12-01

Detailed information on the quantity and distribution of aboveground biomass (AGB) is needed to understand how it varies across space and changes over time. Waveform LiDAR data is routinely used to derive the heights of scattering elements in each illuminated footprint, and the vertical structure of vegetation is related to AGB. Changes in LiDAR waveforms across vegetation structure gradients can demonstrate instrument sensitivity to land cover transitions. A close examination of LiDAR waveforms in footprints across a forest gradient can provide new insight into the relationship of vegetation structure and forest AGB. In this study we use field measurements of individual trees within Laser Vegetation Imaging Sensor (LVIS) footprints along transects crossing forest to non-forest gradients to examine changes in LVIS waveform characteristics at sites with low (< 50Mg/ha) AGB. We relate field AGB measurements to original and adjusted LVIS waveforms to detect the forest AGB interval along a forest - non-forest transition in which the LVIS waveform lose the ability to discern differences in AGB. Our results help identify the lower end the forest biomass range that a ~20m footprint waveform LiDAR can detect, which can help infer accumulation of biomass after disturbances and during forest expansion, and which can guide the use of LiDAR within a multi-sensor fusion biomass mapping approach.

Laboratory Exercise to Evaluate Hay Preservatives.

ERIC Educational Resources Information Center

McGraw, R. L.; And Others

1990-01-01

Presented is a laboratory exercise designed to demonstrate the effects of moisture on hay preservation products in a manner that does not require large amounts of equipment or instructor time. Materials, procedures, and probable results are discussed. (CW)

Steam explosion pretreatment for enhancing biogas production of late harvested hay.

PubMed

Bauer, Alexander; Lizasoain, Javier; Theuretzbacher, Franz; Agger, Jane W; Rincón, María; Menardo, Simona; Saylor, Molly K; Enguídanos, Ramón; Nielsen, Paal J; Potthast, Antje; Zweckmair, Thomas; Gronauer, Andreas; Horn, Svein J

2014-08-01

Grasslands are often abandoned due to lack of profitability. Extensively cultivating grassland for utilization in a biogas-based biorefinery concept could mend this problem. Efficient bioconversion of this lignocellulosic biomass requires a pretreatment step. In this study the effect of different steam explosion conditions on hay digestibility have been investigated. Increasing severity in the pretreatment induced degradation of the hemicellulose, which at the same time led to the production of inhibitors and formation of pseudo-lignin. Enzymatic hydrolysis showed that the maximum glucose yields were obtained under pretreatment at 220 °C for 15 min, while higher xylose yields were obtained at 175 °C for 10 min. Pretreatment of hay by steam explosion enhanced 15.9% the methane yield in comparison to the untreated hay. Results indicate that hay can be effectively converted to methane after steam explosion pretreatment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Flavor compounds and quality parameters of chevon as influenced by sericea lespedeza hay.

PubMed

Lee, Jung Hoon; Vanguru, Manohar; Moore, Danier A; Kannan, Govind; Terrill, Thomas H; Kouakou, Brou

2012-04-18

This research assessed the utilization of sericea lespedeza (SL, Lespedeza cuneata ) hay, a highly condensed tannin (CT) forage (87-181 g CT/kg), as a dietary regimen of meat goats, and thereby the effects on physicochemical properties of goat meat (chevon) and flavor compounds in cooked chevon chops were evaluated. Although it is commonly believed that higher amounts of CT can have deleterious effects on animal performance due to low digestibility and low voluntary intakes in ruminants, feeding meat goats with SL hay increased the body weight compared to goats fed bermudagrass hay without altering the chemical composition and meat quality of chevon. Feeding SL hay to meat goats also did not significantly influence the flavor volatiles in cooked chevon chops. The findings indicate that SL hay can be used as a low-input forage to replace expensive forages.

Relationship between Hay Fever and Mineral Concentration in the Hair, Lifestyle or Aging.

PubMed

Yamashiro, Kaito; Ogata, Fumihiko; Kawasaki, Naohito

2017-01-01

It is important to ingest just proportions of minerals to prevent disease, but these minerals are also secreted into the hair. Meanwhile, the number of hay fever patients in Japan is increasing, causing an increase in national medical expenses. In this study, we investigated the relationship between hay fever and mineral concentrations in hair to obtain findings on the risk of developing pollen allergies. A questionnaire survey was conducted for 275 men and 977 women on their lifestyle habits and ten kinds of mineral concentrations present in their hair were measured with subsequent analysis using nominal logistic regression analysis. The results indicated that half the patients in each age group had hay fever, with no significant difference between hay fever and aging, exercise habits, sleep and dietary rhythms. On the other hand, there was a significant difference between hay fever and mineral concentrations in the hair, and in men with hay fever, iron (odds ratio: 0.55, p<0.05) was low, while in women calcium (odds ratio: 0.67, p<0.05), chromium (odds ratio: 0.46, p<0.001), cadmium (odds ratio: 0.68, p<0.01) were low and selenium (odds ratio: 1.78, p<0.01) was high. These results, suggest that measurements mineral concentrations in hair are indicators of hay fever risk.

Environmental parameters associated with stable fly development at hay feeding sites

USDA-ARS?s Scientific Manuscript database

Substrates composed of hay residues, dung, and urine accumulate around winter hay feeding sites in cattle pastures providing developmental habitat for stable flies. The objective of this study was to relate physiochemical and microbial properties of this substrate to the presence or absence of devel...

Distribution and dynamics of the invasive native hay-scented fern

Treesearch

Songlin Fei; Peter Gould; Melanie Kaeser; Kim Steiner

2010-01-01

The spread and dominance of the invasive native hay-scented fern in the understory is one of the most significant changes to affect the forest ecosystems in the northeastern United States in the last century. We studied changes in the distribution and dynamics of hay-scented fern at a large scale over a 10-yr period in Pennsylvania. The study included 56 stands...

Tannin content and rate of ruminal protein degradation of legume hays

USDA-ARS?s Scientific Manuscript database

This work evaluated ruminal protein degradation rates of legume hays that varied in tannin content. Two cuttings of 5 varieties of birdsfoot trefoil, (Lotus corniculatus), selected for different tannin contents but similar NDF and CP contents, and Spredor 4 alfalfa (control) were conserved as hay. S...

LiDAR Vegetation Investigation and Signature Analysis System (LVISA)

NASA Astrophysics Data System (ADS)

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

Assessing LiDAR elevation data for KDOT applications.

DOT National Transportation Integrated Search

2013-02-01

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

LiDAR and Image Point Cloud Comparison

DTIC Science & Technology

2014-09-01

UAV unmanned aerial vehicle USGS United States Geological Survey UTM Universal Transverse Mercator WGS 84 World Geodetic System 1984 WSI...19  1.  Physics of LiDAR Systems ................................................................20  III.  DATA AND SOFTWARE...ground control point GPS Global Positioning System IMU inertial measurements unit LiDAR light detection and ranging MI mutual information MVS

34 CFR 663.20 - How is a Fulbright-Hays Faculty Research Abroad Fellow selected?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false How is a Fulbright-Hays Faculty Research Abroad Fellow... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 663.20 How is a Fulbright-Hays Faculty Research Abroad Fellow...

34 CFR 663.20 - How is a Fulbright-Hays Faculty Research Abroad Fellow selected?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 3 2011-07-01 2011-07-01 false How is a Fulbright-Hays Faculty Research Abroad Fellow... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 663.20 How is a Fulbright-Hays Faculty Research Abroad Fellow...

34 CFR 663.1 - What is the Fulbright-Hays Faculty Research Abroad Fellowship Program?

Code of Federal Regulations, 2014 CFR

2014-07-01

... 34 Education 3 2014-07-01 2014-07-01 false What is the Fulbright-Hays Faculty Research Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM General § 663.1 What is the Fulbright-Hays Faculty Research Abroad Fellowship Program? (a...

34 CFR 663.1 - What is the Fulbright-Hays Faculty Research Abroad Fellowship Program?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false What is the Fulbright-Hays Faculty Research Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM General § 663.1 What is the Fulbright-Hays Faculty Research Abroad Fellowship Program? (a...

34 CFR 663.1 - What is the Fulbright-Hays Faculty Research Abroad Fellowship Program?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 3 2011-07-01 2011-07-01 false What is the Fulbright-Hays Faculty Research Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM General § 663.1 What is the Fulbright-Hays Faculty Research Abroad Fellowship Program? (a...

34 CFR 663.20 - How is a Fulbright-Hays Faculty Research Abroad Fellow selected?

Code of Federal Regulations, 2012 CFR

2012-07-01

... 34 Education 3 2012-07-01 2012-07-01 false How is a Fulbright-Hays Faculty Research Abroad Fellow... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 663.20 How is a Fulbright-Hays Faculty Research Abroad Fellow...

34 CFR 663.1 - What is the Fulbright-Hays Faculty Research Abroad Fellowship Program?

Code of Federal Regulations, 2013 CFR

2013-07-01

... 34 Education 3 2013-07-01 2013-07-01 false What is the Fulbright-Hays Faculty Research Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM General § 663.1 What is the Fulbright-Hays Faculty Research Abroad Fellowship Program? (a...

34 CFR 663.20 - How is a Fulbright-Hays Faculty Research Abroad Fellow selected?

Code of Federal Regulations, 2014 CFR

2014-07-01

... 34 Education 3 2014-07-01 2014-07-01 false How is a Fulbright-Hays Faculty Research Abroad Fellow... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 663.20 How is a Fulbright-Hays Faculty Research Abroad Fellow...

34 CFR 663.20 - How is a Fulbright-Hays Faculty Research Abroad Fellow selected?

Code of Federal Regulations, 2013 CFR

2013-07-01

... 34 Education 3 2013-07-01 2013-07-01 false How is a Fulbright-Hays Faculty Research Abroad Fellow... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 663.20 How is a Fulbright-Hays Faculty Research Abroad Fellow...

34 CFR 663.1 - What is the Fulbright-Hays Faculty Research Abroad Fellowship Program?

Code of Federal Regulations, 2012 CFR

2012-07-01

... 34 Education 3 2012-07-01 2012-07-01 false What is the Fulbright-Hays Faculty Research Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS FACULTY RESEARCH ABROAD FELLOWSHIP PROGRAM General § 663.1 What is the Fulbright-Hays Faculty Research Abroad Fellowship Program? (a...

Georeferenced LiDAR 3D vine plantation map generation.

PubMed

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

2011-01-01

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

Using Remote Sensing to Determine Timing of High Altitude Grass Hay Growth Stages

NASA Astrophysics Data System (ADS)

Mefford, B.

2015-12-01

Remote sensing has become the standard for collecting data to determine potential irrigation consumptive use in Wyoming for the Green River Basin. The Green River Basin within Wyoming is around 10.8 million acres, located in south western Wyoming and is a sub-basin of the Colorado River Basin. Grass hay is the main crop grown in the basin. The majority of the hay is grown at elevations 7,000 feet above mean sea level. Daily potential irrigation consumptive use is calculated for the basin during the growing season (May 1st to September 30th). To determine potential irrigation consumptive use crop coefficients, reference evapotranspiration (ET) and effective precipitation are required. Currently crop coefficients are the hardest to determine as most research on crop coefficients are based at lower elevations. Values for crop coefficients for grass hay still apply to high altitude grass hay, but the hay grows at a much slower rate than low elevation grass hay. To be able to more accurately determine the timing of the growth stages of hay in this basin, time-lapse cameras were installed at two different irrigated hay fields in the basin for the 2015 growing season and took pictures automatically once a day at 1 P.M.. Both of the fields also contained a permanent research grade weather station. Imagery obtained from these cameras was used as indicators of timing of the major growth stages of the hay and the length of days between the stages. A crop coefficient value was applied every day in the growing season based on the results from the imagery. Daily potential ET was calculated using the crop coefficients and the data from the on-site weather stations. The final result was potential irrigation induced crop consumptive use for each site. Using remote sensing provided necessary information that normally would be applied arbitrarily in determining irrigation induced consumptive use in the Green River Basin.

Motivation for hay: effects of a pelleted diet on behavior and physiology of horses.

PubMed

Elia, Jamie B; Erb, Hollis N; Houpt, Katherine Albro

2010-12-02

The natural diet of free-ranging horses is grass, which is typically high in fiber and calorically dilute, however diets for high performance domestic horses are often low in fiber and calorically dense. The aim of the study was to determine the motivation of horses for hay when fed a low roughage diet. Their motivation could be used to determine if low roughage diets compromise the welfare of horses. Eight mares were fed two different diets in counterbalanced order: ad libitum orchard grass hay; a complete pelleted feed (pellets). Each trial lasted three weeks, with a one-week transition period between diets. To determine the motivation of horses for fiber they were taught to press a panel to obtain a food reward. The fixed ratio (FR) was increased using a progressive ratio ((1,2,4,7,11…) technique. When fed pellets, the horses worked for a median FR of 1 (Range=1-497) to attain pellets, and when fed hay, they worked for a median FR of 25.5 (4-497) to attain pellets. When fed hay, the horses worked for a median FR of 0 (0-0) to attain hay, and when fed pellets, they worked for a FR of 13 (2-79) to attain hay. These results indicate a greater motivation for hay, a high fiber diet, when fed a low fiber diet. The horses spent 10 (5-19.4)% of their time during a 24-hour period eating pellets compared to 61.5 (29-76) % of their time eating hay. Horses spent 58% of their time standing when fed the pellets and only 37% of their time standing when fed hay. Searching behavior (i.e. sifting through wood shaving bedding for food particles) took up 11.5 (1.4-32) % of the horse's day when fed pellets, but only 1.2 (0-3.5) % of the daily time budget when fed hay. Horses chew more times when eating a hay diet (43,476chews/day) than when eating a pellet diet (10,036chews/day). Fecal pH was lower in horses fed the pelleted diet. Copyright © 2010 Elsevier Inc. All rights reserved.

Field drying rate differences amoung cool-season grasses harvested for hay

USDA-ARS?s Scientific Manuscript database

Making high-quality, cool-season grass hay is a challenge, due to the field drying time needed to reach the appropriate moisture content and the high probability of rain in the spring when hay is typically produced. This study was conducted to determine if cool-season grasses with different yield po...

Short-Term responses of breeding birds of grassland and early successional habitat to timing of haying in Northwestern Arkansas

USGS Publications Warehouse

Luscier, J.D.; Thompson, W.L.

2009-01-01

In 2003, we evaluated nest survival and density of the Dickcissel (Spiza americana), Eastern Meadowlark (Sturnella magna), Field Sparrow (Spizella pusilla), and Red-winged Blackbird (Agelaius phoeniceus) in four unhayed, two early-hayed (26-31 May) and three late-hayed (17-25 June) fields in northwestern Arkansas. Rope dragging and observations revealed 89 nests. Daily nest-survival rates (SE) prior to haying ranged from 0.94 (0.03) to 0.97 (0.02). Early haying affected both nest-survival rates and bird densities negatively, whereas late haying had minimal effects. Fifteen nests in hayed portions of early-hayed fields were destroyed, whereas only 2 of 52 nests were affected by late haying. Density was at least 0.98 birds ha-1 higher in unhayed than in early-hayed fields and 1.03 birds ha-1 higher in late-hayed than in early-hayed fields. In northwestern Arkansas, postponing haying until mid- to late June would allow time for nestlings to fledge, would have little effect on bird densities, and would affect hay nutrition and regrowth minimally. ?? The Cooper Ornithological Society, 2009.

LiDAR point classification based on sparse representation

NASA Astrophysics Data System (ADS)

Li, Nan; Pfeifer, Norbert; Liu, Chun

2017-04-01

In order to combine the initial spatial structure and features of LiDAR data for accurate classification. The LiDAR data is represented as a 4-order tensor. Sparse representation for classification(SRC) method is used for LiDAR tensor classification. It turns out SRC need only a few of training samples from each class, meanwhile can achieve good classification result. Multiple features are extracted from raw LiDAR points to generate a high-dimensional vector at each point. Then the LiDAR tensor is built by the spatial distribution and feature vectors of the point neighborhood. The entries of LiDAR tensor are accessed via four indexes. Each index is called mode: three spatial modes in direction X ,Y ,Z and one feature mode. Sparse representation for classification(SRC) method is proposed in this paper. The sparsity algorithm is to find the best represent the test sample by sparse linear combination of training samples from a dictionary. To explore the sparsity of LiDAR tensor, the tucker decomposition is used. It decomposes a tensor into a core tensor multiplied by a matrix along each mode. Those matrices could be considered as the principal components in each mode. The entries of core tensor show the level of interaction between the different components. Therefore, the LiDAR tensor can be approximately represented by a sparse tensor multiplied by a matrix selected from a dictionary along each mode. The matrices decomposed from training samples are arranged as initial elements in the dictionary. By dictionary learning, a reconstructive and discriminative structure dictionary along each mode is built. The overall structure dictionary composes of class-specified sub-dictionaries. Then the sparse core tensor is calculated by tensor OMP(Orthogonal Matching Pursuit) method based on dictionaries along each mode. It is expected that original tensor should be well recovered by sub-dictionary associated with relevant class, while entries in the sparse tensor associated with

Hay/Modern Healthcare compensation survey.

PubMed

Berg, E

1991-06-10

Healthcare chief executives' base salaries overtook those of their industrial counterparts, but they still lagged when comparing total pay, according to this year's Hay/Modern Healthcare Compensation Survey. Even in total compensation, however, healthcare execs were narrowing the gap. The survey also found disparities in pay levels reflected regional factors such as the competitive environment and high cost of living.

Rutherford B. Hayes: His Contributions to American Education (The Presidential Years).

ERIC Educational Resources Information Center

Dye, Charles M.

Emphasizing the dedication with which Rutherford B. Hayes (1822-92) labored to achieve advancement in American public education, the biography discusses the historical and political events which highlighted his career. Describing Hayes as a man who stood above party politicking in his years in the White House (1877-81), the biography maintains…

Study on environmental test technology of LiDAR used for vehicle

NASA Astrophysics Data System (ADS)

Wang, Yi; Yang, Jianfeng; Ou, Yong

2018-03-01

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

Forest structures retrieval from LiDAR onboard ULA

NASA Astrophysics Data System (ADS)

Shang, Xiaoxia; Chazette, Patrick; Totems, Julien; Marnas, Fabien; Sanak, Joseph

2013-04-01

Following the United Nations Framework Convention on Climate Change, the assessment of forest carbon stock is one of the main elements for a better understanding of the carbon cycle and its evolution following the climate change. The forests sequester 80% of the continental biospheric carbon and this efficiency is a function of the tree species and the tree health. The airborne backscatter LiDAR onboard the ultra light aircraft (ULA) can provide the key information on the forest vertical structures and evolution in the time. The most important structural parameter is the tree top height, which is directly linked to the above-ground biomass using non-linear relationships. In order to test the LiDAR capability for retrieving the tree top height, the LiDAR ULICE (Ultraviolet LIdar for Canopy Experiment) has been used over different forest types, from coniferous (maritime pins) to deciduous (oaks, hornbeams ...) trees. ULICE works at the wavelength of 355 nm with a sampling along the line-of-sight between 15 and 75 cm. According to the LiDAR signal to noise ratio (SNR), two different algorithms have been used in our study. The first algorithm is a threshold method directly based on the comparison between the LiDAR signal and the noise distributions, while the second one used a low pass filter by fitting a Gaussian curve family. In this paper, we will present these two algorithms and their evolution as a function of the SNR. The main error sources will be also discussed and assessed for each algorithm. The results show that these algorithms have great potential for ground-segment of future space borne LiDAR missions dedicated to the forest survey at the global scale. Acknowledgements: the canopy LiDAR system ULICE has been developed by CEA (Commissariat à l'Energie Atomique). It has been deployed with the support of CNES (Centre National d'Etude Spariales) and ANR (Agence Nationale de la Recherche). We acknowledge the ULA pilots Franck Toussaint for logistical help

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Modelling rating curves using remotely sensed LiDAR data

USGS Publications Warehouse

Nathanson, Marcus; Kean, Jason W.; Grabs, Thomas J.; Seibert, Jan; Laudon, Hjalmar; Lyon, Steve W.

2012-01-01

Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage-discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics-based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m-wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90-m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a 'hybrid model' rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see 'below' the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics-based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote

DArT Markers Effectively Target Gene Space in the Rye Genome.

PubMed

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

2016-01-01

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

Detecting understory plant invasion in urban forests using LiDAR

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Dual mechanisms regulate ecosystem stability under decade-long warming and hay harvest

PubMed Central

Shi, Zheng; Xu, Xia; Souza, Lara; Wilcox, Kevin; Jiang, Lifen; Liang, Junyi; Xia, Jianyang; García-Palacios, Pablo; Luo, Yiqi

2016-01-01

Past global change studies have identified changes in species diversity as a major mechanism regulating temporal stability of production, measured as the ratio of the mean to the standard deviation of community biomass. However, the dominant plant functional group can also strongly determine the temporal stability. Here, in a grassland ecosystem subject to 15 years of experimental warming and hay harvest, we reveal that warming increases while hay harvest decreases temporal stability. This corresponds with the biomass of the dominant C4 functional group being higher under warming and lower under hay harvest. As a secondary mechanism, biodiversity also explains part of the variation in temporal stability of production. Structural equation modelling further shows that warming and hay harvest regulate temporal stability through influencing both temporal mean and variation of production. Our findings demonstrate the joint roles that dominant plant functional group and biodiversity play in regulating the temporal stability of an ecosystem under global change. PMID:27302085

Integrating LiDAR Data into Earth Science Education

NASA Astrophysics Data System (ADS)

Robinson, S. E.; Arrowsmith, R.; de Groot, R. M.; Crosby, C. J.; Whitesides, A. S.; Colunga, J.

2010-12-01

The use of high-resolution topography derived from Light Detection and Ranging (LiDAR) in the study of active tectonics is widespread and has become an indispensable tool to better understand earthquake hazards. For this reason and the spectacular representation of the phenomena the data provide, it is appropriate to integrate these data into the Earth science education curriculum. A collaboration between Arizona State University, the OpenTopography Facility, and the Southern California Earthquake Center are developing, three earth science education products to inform students and other audiences about LiDAR and its application to active tectonics research. First, a 10-minute introductory video titled LiDAR: Illuminating Earthquakes was produced and is freely available online through the OpenTopography portal and SCEC. The second product is an update and enhancement of the Wallace Creek Interpretive Trail website (www.scec.org/wallacecreek). LiDAR topography data products have been added along with the development of a virtual tour of the offset channels at Wallace Creek using the B4 LiDAR data within the Google Earth environment. The virtual tour to Wallace Creek is designed as a lab activity for introductory undergraduate geology courses to increase understanding of earthquake hazards through exploration of the dramatic offset created by the San Andreas Fault (SAF) at Wallace Creek and Global Positioning System-derived displacements spanning the SAF at Wallace Creek . This activity is currently being tested in courses at Arizona State University. The goal of the assessment is to measure student understanding of plate tectonics and earthquakes after completing the activity. Including high-resolution topography LiDAR data into the earth science education curriculum promotes understanding of plate tectonics, faults, and other topics related to earthquake hazards.

DArT Markers Effectively Target Gene Space in the Rye Genome

PubMed Central

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

2016-01-01

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

LiDAR: Providing structure

USGS Publications Warehouse

Vierling, Lee A.; Martinuzzi, Sebastián; Asner, Gregory P.; Stoker, Jason M.; Johnson, Brian R.

2011-01-01

Since the days of MacArthur, three-dimensional (3-D) structural information on the environment has fundamentally transformed scientific understanding of ecological phenomena (MacArthur and MacArthur 1961). Early data on ecosystem structure were painstakingly laborious to collect. However, as reviewed and reported in recent volumes of Frontiers(eg Vierling et al. 2008; Asner et al.2011), advances in light detection and ranging (LiDAR) remote-sensing technology provide quantitative and repeatable measurements of 3-D ecosystem structure that enable novel ecological insights at scales ranging from the plot, to the landscape, to the globe. Indeed, annual publication of studies using LiDAR to interpret ecological phenomena increased 17-fold during the past decade, with over 180 new studies appearing in 2010 (ISI Web of Science search conducted on 23 Mar 2011: [{lidar AND ecol*} OR {lidar AND fores*} OR {lidar AND plant*}]).

Temporal transferability of LiDAR-based imputation of forest structure attributes

Treesearch

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

2015-01-01

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

Relationship between LiDAR-derived forest canopy height and Landsat images

Treesearch

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

2010-01-01

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

Genome-wide association analysis identifies 11 risk variants associated with the asthma with hay fever phenotype

PubMed Central

Ferreira, Manuel A. R.; Matheson, Melanie C.; Tang, Clara S.; Granell, Raquel; Ang, Wei; Hui, Jennie; Kiefer, Amy K.; Duffy, David L.; Baltic, Svetlana; Danoy, Patrick; Bui, Minh; Price, Loren; Sly, Peter D.; Eriksson, Nicholas; Madden, Pamela A.; Abramson, Michael J.; Holt, Patrick G.; Heath, Andrew C.; Hunter, Michael; Musk, Bill; Robertson, Colin F.; Le Souëf, Peter; Montgomery, Grant W.; Henderson, A. John; Tung, Joyce Y.; Dharmage, Shyamali C.; Brown, Matthew A.; James, Alan; Thompson, Philip J.; Pennell, Craig; Martin, Nicholas G.; Evans, David M.; Hinds, David A.; Hopper, John L.

2014-01-01

Background To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. Objective We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. Methods We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). Results At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10−9) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10−8). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10−7) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10−6). Conclusion By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency. PMID:24388013

Genome-wide association analysis identifies 11 risk variants associated with the asthma with hay fever phenotype.

PubMed

Ferreira, Manuel A R; Matheson, Melanie C; Tang, Clara S; Granell, Raquel; Ang, Wei; Hui, Jennie; Kiefer, Amy K; Duffy, David L; Baltic, Svetlana; Danoy, Patrick; Bui, Minh; Price, Loren; Sly, Peter D; Eriksson, Nicholas; Madden, Pamela A; Abramson, Michael J; Holt, Patrick G; Heath, Andrew C; Hunter, Michael; Musk, Bill; Robertson, Colin F; Le Souëf, Peter; Montgomery, Grant W; Henderson, A John; Tung, Joyce Y; Dharmage, Shyamali C; Brown, Matthew A; James, Alan; Thompson, Philip J; Pennell, Craig; Martin, Nicholas G; Evans, David M; Hinds, David A; Hopper, John L

2014-06-01

To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10(-9)) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10(-8)). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10(-7)) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10(-6)). By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Demystifying LiDAR technologies for temperate rainforest in the Pacific Northwest

Treesearch

Rhonda Mazza; Demetrios Gatziolis

2013-01-01

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

The application of LiDAR to investigate foredune morphology and vegetation

NASA Astrophysics Data System (ADS)

Doyle, Thomas B.; Woodroffe, Colin D.

2018-02-01

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

Association Between Hay Fever and High Myopia in United States Adolescents and Adults.

PubMed

Shafer, Brian M; Qiu, Mary; Rapuano, Christopher J; Shields, Carol L

2017-05-01

To investigate the relationship between hay fever and refractive error in a representative sample of adolescents and adults in the United States. This cross-sectional study included 5,744 participants aged ≥12 years from the 2005 to 2006 National Health and Nutrition Examination Survey who participated in the allergy questionnaire, completed objective refraction and keratometry in both eyes, and had immunoglobulin E (IgE) serology. The primary predictor variable, refractive error, was classified as emmetropia (-0.99 to +0.99 diopters [D]), low myopia (-1.00 to -2.99 D), moderate myopia (-3.00 to -5.99 D), high myopia (≥-6.00 D), or hyperopia (≥1.00 D). Covariates included age, gender, race, asthma, eczema, total serum IgE ≥120 kU/L, corneal steepness, and corneal astigmatism. The primary outcome was hay fever. The study population's mean age was 41.7 years; 48.8% of subjects were men and 51.2% were women. The prevalence of hay fever was 12.1% overall. High myopes had 2.7 times higher odds of hay fever compared to emmetropes (OR 2.67, CI, 1.57-4.51, P=0.001), which was independent of demographics, atopic conditions, IgE serology, and keratometry measurements. The association between hay fever and high myopia identified in this large cross-sectional study remains speculative and was not mediated through corneal steepness or corneal astigmatism. Further prospective studies may help elucidate the directionality of the association between hay fever and high myopia.

Environmental parameters associated with stable fly (Diptera: Muscidae) development at hay feeding sites

USDA-ARS?s Scientific Manuscript database

Substrates composed of hay residues, dung, and urine accumulate around winter hay feeding sites in cattle pastures, providing developmental habitats for stable flies. The objective of this study was to relate physiochemical and microbial properties of these substrates to the presence or absence of s...

34 CFR 664.1 - What is the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2010 CFR

2010-07-01

... Group Projects Abroad Program is designed to contribute to the development and improvement of the study... 34 Education 3 2010-07-01 2010-07-01 false What is the Fulbright-Hays Group Projects Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS GROUP PROJECTS ABROAD...

34 CFR 664.1 - What is the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2011 CFR

2011-07-01

... Group Projects Abroad Program is designed to contribute to the development and improvement of the study... 34 Education 3 2011-07-01 2011-07-01 false What is the Fulbright-Hays Group Projects Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS GROUP PROJECTS ABROAD...

34 CFR 664.1 - What is the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2014 CFR

2014-07-01

... Group Projects Abroad Program is designed to contribute to the development and improvement of the study... 34 Education 3 2014-07-01 2014-07-01 false What is the Fulbright-Hays Group Projects Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS GROUP PROJECTS ABROAD...

34 CFR 664.1 - What is the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2012 CFR

2012-07-01

... Group Projects Abroad Program is designed to contribute to the development and improvement of the study... 34 Education 3 2012-07-01 2012-07-01 false What is the Fulbright-Hays Group Projects Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS GROUP PROJECTS ABROAD...

34 CFR 664.1 - What is the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2013 CFR

2013-07-01

... Group Projects Abroad Program is designed to contribute to the development and improvement of the study... 34 Education 3 2013-07-01 2013-07-01 false What is the Fulbright-Hays Group Projects Abroad... (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION FULBRIGHT-HAYS GROUP PROJECTS ABROAD...

Visualization of High-Resolution LiDAR Topography in Google Earth

NASA Astrophysics Data System (ADS)

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

2009-12-01

The growing availability of high-resolution LiDAR (Light Detection And Ranging) topographic data has proven to be revolutionary for Earth science research. These data allow scientists to study the processes acting on the Earth’s surfaces at resolutions not previously possible yet essential for their appropriate representation. In addition to their utility for research, the data have also been recognized as powerful tools for communicating earth science concepts for education and outreach purposes. Unfortunately, the massive volume of data produced by LiDAR mapping technology can be a barrier to their use. To facilitate access to these powerful data for research and educational purposes, we have been exploring the use of Keyhole Markup Language (KML) and Google Earth to deliver LiDAR-derived visualizations. The OpenTopography Portal (http://www.opentopography.org/) is a National Science Foundation-funded facility designed to provide access to Earth science-oriented LiDAR data. OpenTopography hosts a growing collection of LiDAR data for a variety of geologic domains, including many of the active faults in the western United States. We have found that the wide spectrum of LiDAR users have variable scientific applications, computing resources, and technical experience and thus require a data distribution system that provides various levels of access to the data. For users seeking a synoptic view of the data, and for education and outreach purposes, delivering full-resolution images derived from LiDAR topography into the Google Earth virtual globe is powerful. The virtual globe environment provides a freely available and easily navigated viewer and enables quick integration of the LiDAR visualizations with imagery, geographic layers, and other relevant data available in KML format. Through region-dependant network linked KML, OpenTopography currently delivers over 20 GB of LiDAR-derived imagery to users via simple, easily downloaded KMZ files hosted at the Portal

Adakitic volcanism in the eastern Aleutian arc: Petrology and geochemistry of Hayes volcano, Cook Inlet, Alaska

NASA Astrophysics Data System (ADS)

McHugh, K.; Hart, W. K.; Coombs, M. L.

2012-12-01

Located in south-central Alaska, 135 km northwest of Anchorage, Hayes volcano is responsible for the most widespread tephra fall deposit in the regional Holocene record (~3,500 BP). Hayes is bounded to the west by the Cook Inlet volcanoes (CIV; Mt. Spurr, Redoubt, Iliamna, and Augustine) and separated from the nearest volcanism to the east, Mount Drum of the Wrangell Volcanic Field (WVF), by a 400 km-wide volcanic gap. We report initial results of the first systematic geochemical and petrologic study of Hayes volcano. Hayes eruptive products are calc-alkaline dacites and rhyolites that have anomalous characteristics within the region. Major and trace element analyses reveal that the Hayes rhyolites are more silicic (~74 wt. % SiO2) than compositions observed in other CIV, and its dacitic products possess the distinctive geochemical signatures of adakitic magmas. Key aspects of the Hayes dacite geochemistry include: 16.03 - 17.54 wt. % Al2O3, 0.97 - 2.25 wt. % MgO, Sr/Y = 60 - 78, Yb = 0.9 - 1.2 ppm, Ba/La = 31 - 79. Such signatures are consistent with melting of a metamorphosed basaltic source that leaves behind a residue of garnet ± amphibole ± pyroxene via processes such as melting of a subducting oceanic slab or underplated mafic lower crust, rather than flux melting of the mantle wedge by dehydration of the down-going slab. Additionally, Hayes tephras display a distinctive mineralogy of biotite with amphibole in greater abundance than pyroxene, a characteristic not observed at other CIV. Furthermore, Hayes rhyolites and dacites exhibit little isotopic heterogeneity (87Sr/86Sr = 0.70384 - 0.70395, 206Pb/204Pb = 18.866 - 18.889) suggesting these lavas originate from the same source. Hayes volcano is approximately situated above the western margin of the subducting Yakutat terrane and where the dip of the Pacific slab beneath Cook Inlet shallows northward. Due to its position along the margin of the subducting Yakutat terrane, it is plausible that Hayes magmas

Effects of emergency haying on vegetative characteristics within selected Conservation Reserve Program fields in the Northern Great Plains

USGS Publications Warehouse

Allen, A.W.; Cade, B.S.; Vandever, M.W.

2001-01-01

Successional changes in vegetation composition within seeded grasslands may effect attainment of long term conservaation objectives. Comparisons between vegetation composition within Conservation Reserve Program (CRP) fields planted to cool season, introduced grasses hayed for emergency we, and non hayed fields of the same age and species composition were completed to determine potential effects of periodic haying. Emergency haying had little long term effect on vegetation height/density, percent cover of live pass, or forb cover when compared to characteristics within non hayed fields?. The presence of legumes [primarily alfalfa (Medicago sativa L)] increased in response to haying, whereas, abundance of noxious weeds [chiefly Canada thistle (Cirsium arvense (L) Scop.)] diminished. Implications for long term management CRP grassland to achieve wildlife habitat objectives are discussed.

Important LiDAR metrics for discriminating forest tree species in Central Europe

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed Central

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

2004-01-01

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

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

DOT National Transportation Integrated Search

2013-02-01

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

Association of asthma and hay fever with irregular menstruation.

PubMed

Svanes, C; Real, F Gomez; Gislason, T; Jansson, C; Jögi, R; Norrman, E; Nyström, L; Torén, K; Omenaas, E

2005-06-01

There is some evidence that asthmatic women are more likely to have abnormal sex hormone levels. A study was undertaken to determine whether asthma and allergy were associated with irregular menstruation in a general population, and the potential role of asthma medication for this association. A total of 8588 women (response rate 77%) participated in an 8 year follow up postal questionnaire study of participants of the ECRHS stage I in Denmark, Estonia, Iceland, Norway, and Sweden. Only non-pregnant women not taking exogenous sex hormones were included in the analyses (n = 6137). Irregular menstruation was associated with asthma (OR 1.54 (95% CI 1.11 to 2.13)), asthma symptoms (OR 1.47 (95% CI 1.16 to 1.86)), hay fever (OR 1.29 (95% CI 1.05 to 1.57)), and asthma preceded by hay fever (OR 1.95 (95% CI 1.30 to 2.96)) among women aged 26-42 years. This was also observed in women not taking asthma medication (asthma symptoms: OR 1.44 (95% CI 1.09 to 1.91); hay fever: OR 1.27 (95% CI 1.03 to 1.58); wheeze preceded by hay fever: OR 1.76 (95% CI 1.18 to 2.64)). Irregular menstruation was associated with new onset asthma in younger women (OR 1.58 (95% CI 1.03 to 2.42)) but not in women aged 42-54 years (OR 0.62 (95% CI 0.32 to 1.18)). The results were consistent across centres. Younger women with asthma and allergy were more likely to have irregular menstruation. This could not be attributed to current use of asthma medication. The association could possibly be explained by common underlying metabolic or developmental factors. The authors hypothesise that insulin resistance may play a role in asthma and allergy.

LiDAR Applications in Resource Geology and Benefits for Land Management

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

LiDAR error estimation with WAsP engineering

NASA Astrophysics Data System (ADS)

Bingöl, F.; Mann, J.; Foussekis, D.

2008-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

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

2018-05-14

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

Beverly Hayes | Frederick National Laboratory for Cancer Research

Cancer.gov

Employee name: Bev Hayes Directorate: Management Operations Department or lab: Contracts and Acquisitions How many years have you worked at the Frederick National Laboratory? Four months going on one year! Job responsibilities: With the C&A manageme

Treatment of hay fever.

PubMed Central

Wood, S F

1989-01-01

The range of treatments for hay fever available to the general practitioner has changed considerably in recent years. New antihistamines have addressed the problem of sedation and moved towards one daily dose; nasally applied corticosteroids avoid the need for systemic steroid therapy and its potential adverse effect; and regulatory decisions have set a trend away from immunotherapy in general practice. However, knowledge about the mechanism of action of immunotherapy is increasing and new developments with improved safety profiles include allergen polymers, allergoids, oral immunotherapy and nasal immunotherapy. Choice of treatment depends, as always, on the individual circumstances of the patient and his or her disease. PMID:2556545

Toxicity of endophyte-infected ryegrass hay containing high ergovaline level in lactating ewes.

PubMed

Zbib, N; Repussard, C; Tardieu, D; Priymenko, N; Domange, C; Guerre, P

2015-08-01

The symbiotic association of var. (formerly named ) with perennial ryegrass () leads to the production of ergovaline (EV) and lolitrem B (LB) that are toxic for livestock. The objectives of this study were to determine the effects of feeding endophyte-infected ryegrass (SE+) hay on 16 lactating ewes (BW 80 ± 10 kg) in comparison with endophyte-free ryegrass (SE-) hay to investigate the putative mechanisms of action of EV and LB and to evaluate their persistence in milk and animal tissues. The mean EV and LB concentrations in SE+ hay were 851 and 884 μg/kg DM, respectively, whereas these alkaloids were below the limit of detection in SE- hay. No effect of SE+ was observed on animal health and skin temperature whereas prolactin decreased and significant differences between hays were observed from d 7 to 28 of the study ( < 0.03) but had no effect on milk production. Hematocrit and biochemical analyses of plasma revealed no significant difference between SE+ and SE-, whereas cortisol concentration differed significantly on d 28 ( = 0.001). Measurement of oxidative damage and antioxidant enzyme activities in plasma, liver, and kidneys revealed a slight increase in some enzyme activities involved in defense against oxidative damage in the SE+ fed ewes. Slight variations in the activities of hepatic and kidney flavin monooxygenase enzymes were observed, whereas in the kidney, glutathione -transferase activity decreased significantly ( = 0.002) in the SE+ fed ewes, whereas uridine diphosphate glucuronosyltransferase activity increased ( = 0.001). After 28 d of exposure of ewes to the SE+ hay, low EV and LB concentrations were measured in tissues. The highest concentration of EV was observed in the liver (0.68 μg/kg) whereas fat contained the highest concentration of LB (2.39 μg/kg). Both toxins were also identified at the trace level in milk.

High Density LiDAR and Orthophotography in UXO Wide Area Assessment

DTIC Science & Technology

2008-01-01

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

Significance of a near-source tephra-stratigraphic sequence to the eruptive history of Hayes Volcano, south-central Alaska

USGS Publications Warehouse

Wallace, Kristi; Coombs, Michelle L.; Hayden, Leslie A.; Waythomas, Christopher F.

2014-01-01

Bluffs along the Hayes River valley, 31 km northeast and 40 km downstream from Hayes Volcano, reveal volcanic deposits that shed new light on its eruptive history. Three thick (>10 cm) and five thin (<10 cm) tephra-fall deposits are dacitic in whole rock composition and contain high proportions of amphibole to pyroxene and minor biotite and broadly correlate to Hayes tephra set H defined by earlier investigators. Two basal ages for the tephra-fall sequence of 3,690±30 and 3,750±30 14C yr B.P. are also consistent with the Hayes tephra set H timeframe. Distinguishing among Hayes tephra set H units is critical because the set is an important time-stratigraphic marker in south-central Alaska and this section provides a new reference section for Hayes tephra set H. Analysis of Fe-Ti oxide grains in the tephras shows promise for identifying individual Hayes deposits. Beneath the dacitic tephra sequence lies an older, poorly sorted tephra (tephra A) that contains dacite and rhyolite lapilli and whose basal age is 4,450±30 14C yr B.P. Immediately below the tephra-fall sequence (Unit III) lies a series of mass-flow deposits that are rich in rhyodacitic clasts (Unit II). Below Unit II and possibly coeval with it, is a 20–30 m thick pumiceous pyroclastic-flow deposit (Unit I) that extends to the valley floor. Here informally named the Hayes River ignimbrite, this deposit contains pumice clasts of rhyolite with quartz, sanidine, plagioclase, and biotite phenocrysts, an assemblage that is unique among known Quaternary volcanic products of Hayes and other Alaskan volcanoes. Units I, II, and tephra A of Unit III represent at least two previously unrecognized eruptions of Hayes Volcano that occurred prior to ~3,700 yr B.P. No compositionally equivalent distal tephra deposits correlative with Hayes Volcano rhyodacites or rhyolites have yet been identified, perhaps indicating that some of these deposits are pre-Holocene, and were largely removed by glacial ice during the last

Advances in animal ecology from 3D ecosystem mapping with LiDAR

NASA Astrophysics Data System (ADS)

Davies, A.; Asner, G. P.

2015-12-01

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

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

USGS Publications Warehouse

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

Treesearch

Jeffrey S. Evans; Andrew T. Hudak

2007-01-01

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

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

NASA Astrophysics Data System (ADS)

Bolkas, Dimitrios; Fotopoulos, Georgia; Glennie, Craig

2016-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Utility of LiDAR for large area forest inventory applications

Treesearch

Nicholas S. Skowronski; Andrew J. Lister

2012-01-01

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

9 CFR 95.28 - Hay or straw and similar material from tick-infested areas.

Code of Federal Regulations, 2012 CFR

2012-01-01

... tick-infested areas. 95.28 Section 95.28 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... THE UNITED STATES § 95.28 Hay or straw and similar material from tick-infested areas. Hay or straw, grass, or similar material from tick-infested pastures, ranges, or premises may disseminate the...

9 CFR 95.28 - Hay or straw and similar material from tick-infested areas.

Code of Federal Regulations, 2014 CFR

2014-01-01

... tick-infested areas. 95.28 Section 95.28 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... THE UNITED STATES § 95.28 Hay or straw and similar material from tick-infested areas. Hay or straw, grass, or similar material from tick-infested pastures, ranges, or premises may disseminate the...

9 CFR 95.28 - Hay or straw and similar material from tick-infested areas.

Code of Federal Regulations, 2013 CFR

2013-01-01

... tick-infested areas. 95.28 Section 95.28 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... THE UNITED STATES § 95.28 Hay or straw and similar material from tick-infested areas. Hay or straw, grass, or similar material from tick-infested pastures, ranges, or premises may disseminate the...

LiDAR as an Exploration Tool

DOE Data Explorer

Boschmann, D.; Diles, J.; Clarno, J.; Meigs, A.; Walsh, P.

2011-01-01

Using LiDAR to identify structural and volcanic evolution of a Miocene-Pleistocene age bimodal volcanic complex and implications for geothermal potential. The file includes an updated geologic map, methods, and preliminary results.

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

USGS Publications Warehouse

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

2015-01-01

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

Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

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

Danny L. Anderson

Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates amore » new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed “mDn”, is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mDn method yielded the smallest LRMSE.« less

Geotechnical applications of LiDAR pertaining to geomechanical evaluation and hazard identification

NASA Astrophysics Data System (ADS)

Lato, Matthew J.

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

34 CFR 662.1 - What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program?

Code of Federal Regulations, 2014 CFR

2014-07-01

... Research Abroad Fellowship Program? 662.1 Section 662.1 Education Regulations of the Offices of the... DOCTORAL DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM General § 662.1 What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program? (a) The Fulbright-Hays Doctoral Dissertation...

34 CFR 662.1 - What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program?

Code of Federal Regulations, 2011 CFR

2011-07-01

... Research Abroad Fellowship Program? 662.1 Section 662.1 Education Regulations of the Offices of the... DOCTORAL DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM General § 662.1 What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program? (a) The Fulbright-Hays Doctoral Dissertation...

34 CFR 662.1 - What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program?

Code of Federal Regulations, 2012 CFR

2012-07-01

... Research Abroad Fellowship Program? 662.1 Section 662.1 Education Regulations of the Offices of the... DOCTORAL DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM General § 662.1 What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program? (a) The Fulbright-Hays Doctoral Dissertation...

34 CFR 662.1 - What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program?

Code of Federal Regulations, 2010 CFR

2010-07-01

... Research Abroad Fellowship Program? 662.1 Section 662.1 Education Regulations of the Offices of the... DOCTORAL DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM General § 662.1 What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program? (a) The Fulbright-Hays Doctoral Dissertation...

34 CFR 662.1 - What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program?

Code of Federal Regulations, 2013 CFR

2013-07-01

... Research Abroad Fellowship Program? 662.1 Section 662.1 Education Regulations of the Offices of the... DOCTORAL DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM General § 662.1 What is the Fulbright-Hays Doctoral Dissertation Research Abroad Fellowship Program? (a) The Fulbright-Hays Doctoral Dissertation...

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

KML-Based Access and Visualization of High Resolution LiDAR Topography

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Rumen volatile fatty acids and milk composition from cows fed hay, haylage, or urea-treated corn silage.

PubMed

Schingoethe, D J; Voelker, H H; Beardsley, G L; Parsons, J G

1976-05-01

Alfalfa-brome hay, haylage, .5% urea-treated corn silage, or .5% urea plus 1% dried whey-treated corn silage was fed as the only forage to one of four groups of 10 lactating cows per group for a lactation trial of 10 wk. Rumen samples were collected via stomach tube 3 to 4 h after the morning feeding. The pH of the rumen samples from cows fed hay was higher than for cows fed haylage, urea-treated corn silage, and urea-whey corn silage, 6.69 versus 6.36, 6.40, and 6.50. Total volatile fatty acids and propionate were highest from cows fed urea-whey corn silage and were higher on all three fermented forages than cows fed hay. Acetate/propionate ratio was highest from cows fed hay and lowest from cows fed corn silages. Butyrate was highest from cows fed haylage or hay. Milk protein composition was not affected by ration although nonprotein nitrogen of milk was highest from cows fed the urea-treated corn silages. Oleic acid and total unsaturated fatty acids were lowest in milk fat from cows fed hay while palmitic acid was highest from cows fed hay and haylage. These results suggest that type of forage fed may cause small changes in rumen fermentation and in milk composition. The importance of these changes is unknown but may affect properties of dairy products produced from this milk.

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

Treesearch

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...

Automatic extraction of building boundaries using aerial LiDAR data

NASA Astrophysics Data System (ADS)

Wang, Ruisheng; Hu, Yong; Wu, Huayi; Wang, Jian

2016-01-01

Building extraction is one of the main research topics of the photogrammetry community. This paper presents automatic algorithms for building boundary extractions from aerial LiDAR data. First, segmenting height information generated from LiDAR data, the outer boundaries of aboveground objects are expressed as closed chains of oriented edge pixels. Then, building boundaries are distinguished from nonbuilding ones by evaluating their shapes. The candidate building boundaries are reconstructed as rectangles or regular polygons by applying new algorithms, following the hypothesis verification paradigm. These algorithms include constrained searching in Hough space, enhanced Hough transformation, and the sequential linking technique. The experimental results show that the proposed algorithms successfully extract building boundaries at rates of 97%, 85%, and 92% for three LiDAR datasets with varying scene complexities.

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

PubMed

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

2017-06-01

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

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

DTIC Science & Technology

2013-05-10

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

[A review on studies and applications of near infrared spectroscopy technique(NIRS) in detecting quality of hay].

PubMed

Ding, Wu-Rong; Gan, You-Min; Guo, Xu-Sheng; Yang, Fu-Yu

2009-02-01

The quality of hay can directly affect the price of hay and also livestock productivity. Many kinds of methods have been developed for detecting the quality of hay and the method of near infrared spectroscopy (NIRS) has been widely used with consideration of its fast, effective and nondestructive characteristics during detecting process. In the present paper, the feasibility and effectiveness of application of NIRS to detecting hay quality were expounded. Meanwhile, the advance in the study of using NIRS to detect chemical compositions, extent of incursion by epiphyte, amount of toxicant excreted by endogenetic epiphyte and some minim components that can not be detected by using chemical methods were also introduced detailedly. Based on the review of the progresses in using NIRS to detect the quality of hay, it can be concluded that using NIRS to detect hay quality can avoid the disadvantages of time wasting, complication and high cost when using traditional chemical method. And for better utilization of NIRS in practice, some more studies still need to be implemented to further perfect and improve the utilization of NIRS for detecting forage quality, and more accurate modes and systematic analysis software need to be established in times to come.

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

PubMed Central

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

2016-01-01

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

The HayWired Earthquake Scenario—Earthquake Hazards

USGS Publications Warehouse

Detweiler, Shane T.; Wein, Anne M.

2017-04-24

The HayWired scenario is a hypothetical earthquake sequence that is being used to better understand hazards for the San Francisco Bay region during and after an earthquake of magnitude 7 on the Hayward Fault. The 2014 Working Group on California Earthquake Probabilities calculated that there is a 33-percent likelihood of a large (magnitude 6.7 or greater) earthquake occurring on the Hayward Fault within three decades. A large Hayward Fault earthquake will produce strong ground shaking, permanent displacement of the Earth’s surface, landslides, liquefaction (soils becoming liquid-like during shaking), and subsequent fault slip, known as afterslip, and earthquakes, known as aftershocks. The most recent large earthquake on the Hayward Fault occurred on October 21, 1868, and it ruptured the southern part of the fault. The 1868 magnitude-6.8 earthquake occurred when the San Francisco Bay region had far fewer people, buildings, and infrastructure (roads, communication lines, and utilities) than it does today, yet the strong ground shaking from the earthquake still caused significant building damage and loss of life. The next large Hayward Fault earthquake is anticipated to affect thousands of structures and disrupt the lives of millions of people. Earthquake risk in the San Francisco Bay region has been greatly reduced as a result of previous concerted efforts; for example, tens of billions of dollars of investment in strengthening infrastructure was motivated in large part by the 1989 magnitude 6.9 Loma Prieta earthquake. To build on efforts to reduce earthquake risk in the San Francisco Bay region, the HayWired earthquake scenario comprehensively examines the earthquake hazards to help provide the crucial scientific information that the San Francisco Bay region can use to prepare for the next large earthquake, The HayWired Earthquake Scenario—Earthquake Hazards volume describes the strong ground shaking modeled in the scenario and the hazardous movements of

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

PubMed Central

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

2008-01-01

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

34 CFR 664.3 - Who is eligible to participate in projects funded under the Fulbright-Hays Group Projects Abroad...

Code of Federal Regulations, 2014 CFR

2014-07-01

... the Fulbright-Hays Group Projects Abroad Program? 664.3 Section 664.3 Education Regulations of the... EDUCATION FULBRIGHT-HAYS GROUP PROJECTS ABROAD PROGRAM General § 664.3 Who is eligible to participate in projects funded under the Fulbright-Hays Group Projects Abroad Program? An individual is eligible to...

34 CFR 664.3 - Who is eligible to participate in projects funded under the Fulbright-Hays Group Projects Abroad...

Code of Federal Regulations, 2012 CFR

2012-07-01

... the Fulbright-Hays Group Projects Abroad Program? 664.3 Section 664.3 Education Regulations of the... EDUCATION FULBRIGHT-HAYS GROUP PROJECTS ABROAD PROGRAM General § 664.3 Who is eligible to participate in projects funded under the Fulbright-Hays Group Projects Abroad Program? An individual is eligible to...

34 CFR 664.3 - Who is eligible to participate in projects funded under the Fulbright-Hays Group Projects Abroad...

Code of Federal Regulations, 2013 CFR

2013-07-01

... the Fulbright-Hays Group Projects Abroad Program? 664.3 Section 664.3 Education Regulations of the... EDUCATION FULBRIGHT-HAYS GROUP PROJECTS ABROAD PROGRAM General § 664.3 Who is eligible to participate in projects funded under the Fulbright-Hays Group Projects Abroad Program? An individual is eligible to...

Assessing Tennessee Livestock Producers' Awareness, Attitudes, and Perceptions of Right-of-Way Hay Harvesting

ERIC Educational Resources Information Center

Greer, Sarah Joy F.; Stripling, Christopher T.; Griffith, Andrew P.; Stephens, Carrie Ann

2017-01-01

Tennessee Statute 54-5-134, Cutting Hay Along Controlled Access Highway Right-of-Way, provided agriculturalists the right to harvest hay along interstate highways' and other controlled access roads' medians and shoulders. Maintenance of these medians and shoulders are routinely contracted to private mowing companies and funded by Tennessee…

34 CFR 662.20 - How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 3 2011-07-01 2011-07-01 false How is a Fulbright-Hays Doctoral Dissertation Research... DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 662.20 How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected? (a) The Secretary considers applications for fellowships under...

34 CFR 662.20 - How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false How is a Fulbright-Hays Doctoral Dissertation Research... DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 662.20 How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected? (a) The Secretary considers applications for fellowships under...

34 CFR 664.5 - What definitions apply to the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2012 CFR

2012-07-01

... Projects Abroad Program? 664.5 Section 664.5 Education Regulations of the Offices of the Department of... PROJECTS ABROAD PROGRAM General § 664.5 What definitions apply to the Fulbright-Hays Group Projects Abroad... apply to this program: The following definitions apply to the Fulbright-Hays Group Projects Abroad...

34 CFR 664.5 - What definitions apply to the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2014 CFR

2014-07-01

... Projects Abroad Program? 664.5 Section 664.5 Education Regulations of the Offices of the Department of... PROJECTS ABROAD PROGRAM General § 664.5 What definitions apply to the Fulbright-Hays Group Projects Abroad... apply to this program: The following definitions apply to the Fulbright-Hays Group Projects Abroad...

34 CFR 664.5 - What definitions apply to the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2013 CFR

2013-07-01

... Projects Abroad Program? 664.5 Section 664.5 Education Regulations of the Offices of the Department of... PROJECTS ABROAD PROGRAM General § 664.5 What definitions apply to the Fulbright-Hays Group Projects Abroad... apply to this program: The following definitions apply to the Fulbright-Hays Group Projects Abroad...

34 CFR 664.5 - What definitions apply to the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2010 CFR

2010-07-01

... Projects Abroad Program? 664.5 Section 664.5 Education Regulations of the Offices of the Department of... PROJECTS ABROAD PROGRAM General § 664.5 What definitions apply to the Fulbright-Hays Group Projects Abroad... apply to this program: The following definitions apply to the Fulbright-Hays Group Projects Abroad...

34 CFR 664.5 - What definitions apply to the Fulbright-Hays Group Projects Abroad Program?

Code of Federal Regulations, 2011 CFR

2011-07-01

... Projects Abroad Program? 664.5 Section 664.5 Education Regulations of the Offices of the Department of... PROJECTS ABROAD PROGRAM General § 664.5 What definitions apply to the Fulbright-Hays Group Projects Abroad... apply to this program: The following definitions apply to the Fulbright-Hays Group Projects Abroad...

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

Treesearch

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

2011-01-01

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

Modelling vertical error in LiDAR-derived digital elevation models

NASA Astrophysics Data System (ADS)

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

2010-01-01

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

Effects of feeding steers extruded flaxseed on its own before hay or mixed with hay on animal performance, carcass quality, and meat and hamburger fatty acid composition.

PubMed

Vahmani, P; Rolland, D C; McAllister, T A; Block, H C; Proctor, S D; Guan, L L; Prieto, N; López-Campos, Ó; Aalhus, J L; Dugan, M E R

2017-09-01

The objective of the present experiment was to determine if carcass quality and fatty acid profiles of longissimus thoracis (LT) and hamburger would be affected by feeding steers extruded flaxseed on its own followed by hay (non-TMR) compared to when hay and extruded flaxseed were fed together (TMR). Forty-eight steers in six pens were assigned to TMR or non-TMR for an average of 242days. Dry matter intake was lower for non-TMR versus TMR steers (10.56 vs. 11.42kg/d; P=0.02), but final live weight (610±0.50kg) and average daily gain (1.18±0.02kg/d) did not differ. Compared to TMR, feeding non-TMR enriched LT and hamburger with α-linolenic acid (ALA; 18:3n-3) by 14%, vaccenic acid (VA; t11-18:1) by 44%, rumenic acid (RA; c9,t11-18:2) by 40%, and conjugated linolenic acid (CLnA) by 58%. Overall, feeding extruded flaxseed separately from hay in a non-TMR was more effective at enhancing deposition of ALA, VA, RA and CLnA in beef. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Effect of genotype, housing system and hay supplementation on carcass traits and meat quality of growing rabbits.

PubMed

Dalle Zotte, A; Szendrő, K; Gerencsér, Zs; Szendrő, Zs; Cullere, M; Odermatt, M; Radnai, I; Matics, Zs

2015-12-01

The aim of the study was to examine the effects of genotype (Pannon Large × Pannon Ka/Large/or Hungarian Giant × Pannon Ka/Hung), housing system (Cage or small Pen) and hay supplementation (Pellet without or with Hay/P+Hay/) on carcass and meat (Longissimus dorsi/LD/ and hind leg/HL/) quality of growing rabbits. Large rabbits showed higher carcass weights, as well as higher fatness and meatiness compared to Hung rabbits. Caged rabbits were heavier, with higher prevalence of the mid part of the carcass, and showed higher fatness and lower meat toughness than Penned rabbits. Caged rabbits meat was richer in MUFA, but poorer in PUFA and Σ n-6 FA. Hay supplementation impaired carcass weight, carcass fatness, L* and a* color, and lipids content. P+Hay increased the HL meat content of C18:3 n-6 and C20:5 n-3 FA. Overall results offer further information on how alternative breeds, housing systems and feeding strategies can affect carcass traits and meat quality. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sporotrichosis outbreak and mouldy 
hay in NSW.

PubMed

Dhingra, Deeksha; Durrheim, David; Porigneaux, Philippe

2015-04-01

Sporotrichosis is a subacute/chronic fungal infection caused by Sporothrix schenckii. The fungus thrives on organic matter including hay, wood, moss, soil and plants. Zoonotic transmission has also been reported. Lesions present as superficial skin nodules that become purulent and ulcerate. Lymphocutaneous spread is common. Haematogenous spread is uncommon and case fatality is rare. The aim of this article is to describe an outbreak of sporotrichosis in New South Wales. A cluster of six cases was identified in the NSW mid-north coast area in the first half of 2013. Telephone interviews were conducted in an attempt to identify possible exposures. General practitioners were contacted to report on patients with chronic non-healing skin lesions. A batch of mouldy hay supplied by a local farmer was identified as the potential source of exposure. Despite effective treatment with oral antifungals, diagnosis of sporotrichosis is often delayed and prolonged courses of antibiotics are unnecessarily prescribed. Timely detection and management (including referral to a dermatologist or infectious diseases specialist) significantly reduces morbidity. Personal protection is the key to prevention.

34 CFR 664.40 - Can participation in a Fulbright-Hays Group Projects Abroad be terminated?

Code of Federal Regulations, 2010 CFR

2010-07-01

... PROJECTS ABROAD PROGRAM What Conditions Must Be Met by a Grantee? § 664.40 Can participation in a Fulbright-Hays Group Projects Abroad be terminated? (a) Participation may be terminated only by the J. William... 34 Education 3 2010-07-01 2010-07-01 false Can participation in a Fulbright-Hays Group Projects...

Real-time computational photon-counting LiDAR

NASA Astrophysics Data System (ADS)

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.

Electromyographic evaluation of masseter muscle activity in horses fed (i) different types of roughage and (ii) maize after different hay allocations.

PubMed

Vervuert, I; Brüssow, N; Bochnia, M; Cuddeford, D; Coenen, M

2013-06-01

The aims of this study were to monitor electromyographic (EMG) activity of masseter muscle in healthy horses fed (i) different types of roughage and (ii) maize after different hay allocations. Four horses were offered the following three diets ad libitum: hay, haylage or straw/alfalfa chaff (SAC). In a second trial, four horses were fed cracked maize (CM) and hay in three different orders: (i) CM after a 12-h overnight fast; (ii) CM immediately after restricted hay intake (0.6 kg hay/100 kg BW); or 3) CM after hay intake ad libitum. The activity of the masseter muscle was determined by EMG (IED(®) ), and the following were measured: amplitude (muscle action potential = MAP, maximum voltage) and duration of MAP (s). The intake of hay or haylage was associated with intense masseter muscle activity (MAP: hay, 10 ± 1.7 V; haylage, 11 ± 3.3 V; and duration of MAP: hay, 0.31 ± 0.04 s; haylage, 0.30 ± 0.04 s). Similar intense chewing was measured for SAC (MAP 13 ± 3.8 V), although duration of the chewing cycle was relatively short (0.22 ± 0.03 s, diet p < 0.05), which is possibly related to the shorter fibre length. CM was consumed rapidly, with less intense masseter muscle activity (MAP 6.0 ± 1.5 V). Hay intake before CM did not affect chewing force of CM, but duration of chewing cycle was significantly prolonged by feeding hay ad libitum before CM was fed. The consumption of hay, haylage or SAC was associated with intensive masseter muscle activity that was likely to stimulate salivary flow rate. In contrast to roughage, concentrates like CM are consumed rapidly with less intensive masseter muscle activity. This situation is associated with a low salivary flow that may have an adverse effect on gastric function. © 2012 Blackwell Verlag GmbH.

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

DOT National Transportation Integrated Search

2014-01-01

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

Detecting and connecting agricultural ditches using LiDAR data

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Greenhouse gas fluxes of grazed and hayed wetland catchments in the U.S. Prairie Pothole Ecoregion

USGS Publications Warehouse

Finocchiaro, Raymond G.; Tangen, Brian A.; Gleason, Robert A.

2014-01-01

Wetland catchments are major ecosystems in the Prairie Pothole Region (PPR) and play an important role in greenhouse gases (GHG) flux. However, there is limited information regarding effects of land-use on GHG fluxes from these wetland systems. We examined the effects of grazing and haying, two common land-use practices in the region, on GHG fluxes from wetland catchments during 2007 and 2008. Fluxes of methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2), along with soil water content and temperature, were measured along a topographic gradient every other week during the growing season near Ipswich, SD, USA. Closed, opaque chambers were used to measure fluxes of soil and plant respiration from native sod catchments that were grazed or left idle, and from recently restored catchments which were seeded with native plant species; half of these catchments were hayed once during the growing season. Catchments were adjacent to each other and had similar soils, soil nitrogen and organic carbon content, precipitation, and vegetation. When compared with idle catchments, grazing as a land-use had little effect on GHG fluxes. Likewise, haying had little effect on fluxes of CH4 and N2O compared with non-hayed catchments. Haying, however, did have a significant effect on combined soil and vegetative CO2 flux in restored wetland catchments owing to the immediate and comprehensive effect haying has on plant productivity. This study also examined soil conditions that affect GHG fluxes and provides cumulative annual estimates of GHG fluxes from wetland catchment in the PPR.

India, '95. Fulbright-Hays Summer Seminar Abroad Project 1997.

ERIC Educational Resources Information Center

Johnson, Cheryl

This paper describes benefits gained from a Fulbright-Hays summer study program to India. Included are examples of classroom materials used to teach classes about Indian folk art: puppets, silhouettes, surface embellishment (body ornamentation) including pierced design, visual communication pins, and T-shirt logos. (EH)

The combined effects of family size and farm exposure on childhood hay fever and atopy.

PubMed

Genuneit, Jon; Strachan, David P; Büchele, Gisela; Weber, Juliane; Loss, Georg; Sozanska, Barbara; Boznanski, Andrzej; Horak, Elisabeth; Heederik, Dick; Braun-Fahrländer, Charlotte; von Mutius, Erika

2013-05-01

Exposure to farming environments and siblings is associated with reduced risks of childhood hay fever and atopy. We explored the independence and interaction of these protective effects in the GABRIELA study. Questionnaire surveys on farming, asthma, and allergies were conducted in four central European areas among 79,888 6-12-yr-old children. Aeroallergen-specific serum IgE was measured in a stratified sample of 8,023 children. Multiple logistic regression was used to compare gradients in allergy prevalence by sibship size across three categories of exposure to farming environments. The prevalence of hay fever ranged from 2% (95% confidence interval 1.6%; 2.7%) among farmers' children with more than two siblings to 12% (11.2%; 13.0%) among children with no farm exposure and no siblings. Farming families were larger on average. More siblings and exposure to farming environments independently conferred protection from hay fever and atopy. There was no substantial effect modification between family size and exposure to farming environments. The odds ratios for hay fever per additional sibling were 0.79 among unexposed non-farm children, 0.77 among farm-exposed non-farm children, and 0.72 among children from farming families (2df interaction test: p = 0.41). The inverse association of exposure to farming environments with hay fever is found in all sizes of family, with no substantial tendency to saturation or synergism. This suggests that different biological mechanisms may underlie these two protective factors. Combinations of a large family and exposure to farming environments markedly reduce the prevalence of hay fever and indicate the strength of its environmental determinants. © 2013 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.

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

PubMed

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

2013-07-03

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

The Effect of Five Different Wetting Treatments on the Nutrient Content and Microbial Concentration in Hay for Horses

PubMed Central

Moore-Colyer, Meriel Jean Scott; Lumbis, Kimberly; Longland, Annette; Harris, Patricia

2014-01-01

Five different hays were used to determine the effect of 5 different soaking and steaming treatments on the water soluble carbohydrate and microbial (bacteria and mould) contents of UK hay. Hays were subjected to the following 5 treatments: 1. Dry; 2. Steamed for 50 minutes in the Haygain- 600 steamer; 3. Soaked in water at 16°C for 9 hours; 4. Steamed then soaked and 5. Soaked then steamed. Post treatment hays were tested for water soluble carbohydrates, bacteria and mould contents. Differences between means were determined using ANOVA and least significant difference with hay (5), bale (3) and treatment (5) as fixed factors, thus n = 75. Protein and ash proportions were unaltered in any of the treatments. Soaked, steamed then soaked and soaked then steamed treatments were all equally effective at reducing water soluble carbohydrates, with significantly (P<0.05) lower mean contents (79–83 g/kg DM) compared with 126 and 122 g/kg dry matter (DM) for dry and steamed respectively. Steamed and soaked then steamed had significantly (P<0.05) less bacteria (1.04×103 and 4.9×102 CFU/g DM) compared with soaked which increased CFU/g DM from 6.0×104 in dry hay up to 3.5×105. Mould contents CFU/g DM were significantly (P<0.05) reduced by steaming (2) and soaking then steaming (1.9) but no difference was seen between dry (1148), soaked (692) or steamed then soaked (501). Soaking for 9 hours followed by steaming for 50 minutes in the Haygain steamer was the most effective method for reducing water soluble carbohydrates and microbial contamination in hay. Soaking or steaming+soaking lowered water soluble carbohydrates but significantly reduced the hygienic quality of the hay which could potentially compromise the health of the horse. PMID:25426729

Diversity arrays technology (DArT) markers in apple for genetic linkage maps.

PubMed

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

2012-03-01

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

Effects of feeding ratio of beet pulp to alfalfa hay or grass hay on ruminal mat characteristics and chewing activity in Holstein dry cows.

PubMed

Izumi, Kenichi; Unno, Chigusa

2010-04-01

The influence of the feeding ratio of a non-forage fiber source and hay on ruminal mat characteristics and chewing activity was evaluated in dairy dry cows. Cows were fed four different diets: the ratios of alfalfa hay (AH) to beet pulp (BP) were 8:2 (dry matter basis, A8B2) and 2:8 (A2B8), and those of grass hay (GH) to BP were 8:2 (G8B2) and 2:8 (G2B8). Total eating time was decreased with increasing BP content (P < 0.01). Total rumination time for AH was shorter than that for GH (P < 0.01), and it decreased with increasing BP content (P < 0.01). The ruminal mat was detected by using a penetration resistance test of the rumen digesta. Penetration resistance value (PRV) of ruminal mat was highest with the G8B2 diet and PRV decreased with increasing BP content (P < 0.05) and feeding AH (P < 0.05). Thickness of the ruminal mat was greater for increasing BP content (P < 0.05). Simple linear regression of ruminal mat PRV on total rumination time resulted in a high positive correlation (r = 0.744; P < 0.001; n = 16). The results demonstrated that increasing the PRV of the ruminal mat stimulated rumination activity and a ruminal mat could be formed, although it was soft even when cows were offered a large quantity of BP.

Geospatial revolution and remote sensing LiDAR in Mesoamerican archaeology

PubMed Central

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

2012-01-01

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

Geospatial revolution and remote sensing LiDAR in Mesoamerican archaeology.

PubMed

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

2012-08-07

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.

Airborne hyperspectral and LiDAR data integration for weed detection

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Gasification of hybrid feedstock using animal manures and hays

USDA-ARS?s Scientific Manuscript database

The objective of this study is to evaluate the efficiency of a proprietary integrated gasification-internal combustion system in producing electricity from mixtures of animal manures such as swine solids, chicken litter, and hays. Five to 10 gallons of mixtures of swine manure, chicken litter, and h...

Soil changes after hay meadow abandonment in southwestern Wisconsin.

Treesearch

M. Dean Knighton

1977-01-01

Soil properties were monitored in early spring and late fall for 3 years following hay meadow abandonment. Bulk density decreased, organic carbon increased, total porosity increased in the large pore fraction, and infiltration rate increased 100%. Earthworm activity was considered to be primarily responsible for the improvement.

Design, experimental and economic evaluation of a commercial-type solar dryer for production of high-quality hay

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

Arinze, E.A.; Sokhansanj, S.; Schoenau, G.J.

1998-03-01

Design features, development, experimental functional performance and economic evaluation of an energy efficient solar energy dryer for commercial production of high-quality hay and processed forage products are presented. The solar hay dryer consists of an improved solar collector with selective coated aluminum absorber plate and spaced fins, and a drying shed connected to the collector by an insulated duct and having a perforated metal grate floor, swing-away plywood frames and polyethylene curtains for effectively sealing the hay stack, and a crawl space below the floor where a 3-hp in-line centrifugal fan is housed for air circulation by suction. In latemore » August and in early September, 1996, 160 small rectangular bales of alfalfa hay with about 25% bromegrass were successfully dried from 33% initial moisture content to 13%, and from 25% to 11% moisture in 4 and 3 days, respectively, under average weather conditions in Saskatoon, Saskatchewan, Canada. With about 18 m{sup 3}/min per tonne airflow, 10--15 C temperature rise above ambient was obtained during peak bright sunshine hours. Relatively high daily average collector efficiency of 76%, high drying effectiveness, drying uniformity, uniform air distribution and tight sealing of the stack were achieved which resulted in an attractive green color of hay, no mold growth on hay, and an overall system drying efficiency of about 79%. Compared to a conventional natural gas drying system or field-drying method, the payback period on extra investment costs recovered through drying cost savings of $3/t to $6/t or through over two times higher prices for high-quality hay produced by the solar drying system may be just one or two years, respectively.« less

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

PubMed

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

2011-04-01

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

Efficacy of cyromazine to control immature stable flies (Diptera: Muscidae) developing in winter hay feeding sites

USDA-ARS?s Scientific Manuscript database

The hay mixed with manure and urine residues at sites where hay has been provided as supplemental winter feed for cattle provide an excellent substrate for the development of immature stable flies, Stomoxys calcitrans (L.). Such sites are primary sources of early summer stable flies in the central U...

Phenology of stable fly (Diptera: Muscidae) larvae in round bale hay feeding sites in Eastern Nebraska

USDA-ARS?s Scientific Manuscript database

The temporal and spatial patterns of adult stable fly, Stomoxys calcitrans (L.), emergence from six sites where large round baled hay had been provided to pastured cattle as winter feed were studied using emergence traps. The substrate at these sites, consisting of waste hay mixed with bovine manure...

Status and prospects for LiDAR remote sensing of forested ecosystems

Treesearch

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

2013-01-01

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

Effects of feeding birdsfoot trefoil hay on neutral detergent fiber digestion, nitrogen utilization efficiency, and lactational performance by dairy cows.

PubMed

Christensen, R G; Yang, S Y; Eun, J-S; Young, A J; Hall, J O; MacAdam, J W

2015-11-01

This experiment was conducted to determine effects of feeding birdsfoot trefoil hay-based diets in comparison with an alfalfa hay-based diet on N utilization efficiency, ruminal fermentation, and lactational performance by mid-lactation dairy cows. Nine multiparous lactating Holstein cows (131 ± 22.6 d in milk), 3 of which were rumen fistulated, were fed 3 experimental diets in a replicated 3 × 3 Latin square design with 3 periods of 14 d of adaptation and 7 d of data and sample collection. Within squares, cows were randomly assigned to diets as follows: alfalfa hay-based diet (AHT), alfalfa and birdsfoot trefoil hay-based diet (ABT), and birdsfoot trefoil hay-based diet (BT). Intakes of dry matter and crude protein were similar across treatments, whereas ABT and BT diets resulted in decreased fiber intake compared with AHT. Feeding BT tended to increase neutral detergent fiber digestibility compared with AHT and ABT. Milk yield tended to increase for cows consuming ABT or BT diets. Milk true protein concentration and yield were greater for cows consuming ABT relative to those fed AHT. Concentration of total volatile fatty acids tended to increase by cows fed BT compared with those fed AHT and ABT. Feeding birdsfoot trefoil hay in a total mixed ration resulted in a tendency to decrease acetate proportion, but it tended to increase propionate proportion, leading to a tendency to decrease acetate-to-propionate ratio. Whereas concentration of ammonia-N was similar across treatments, cows offered BT exhibited greater microbial protein yield relative to those fed AHT and ABT. Cows offered birdsfoot trefoil hay diets secreted more milk N than AHT, resulting in improved N utilization efficiency for milk N. The positive effects due to feeding birdsfoot trefoil hay were attributed to enhanced neutral detergent fiber digestion, and thus it could replace alfalfa hay in high-forage dairy diets while improving N utilization efficiencies and maintaining lactational performance

Weaned beef calves fed selenium-biofortified alfalfa hay have an enriched nasal microbiota compared with healthy controls.

PubMed

Hall, Jean A; Isaiah, Anitha; Estill, Charles T; Pirelli, Gene J; Suchodolski, Jan S

2017-01-01

Selenium (Se) is an essential trace mineral important for immune function and overall health of cattle. The nasopharyngeal microbiota in cattle plays an important role in overall respiratory health, especially when stresses associated with weaning, transport, and adaptation to a feedlot affect the normal respiratory defenses. Recent evidence suggests that cattle diagnosed with bovine respiratory disease complex have significantly less bacterial diversity. The objective of this study was to determine whether feeding weaned beef calves Se-enriched alfalfa (Medicago sativa) hay for 9 weeks in a preconditioning program prior to entering the feedlot alters nasal microbiota. Recently weaned beef calves (n = 45) were blocked by sex and body weight, randomly assigned to 3 treatment groups with 3 pens of 5 calves per treatment group, and fed an alfalfa hay based diet for 9 weeks. Alfalfa hay was harvested from fields fertilized with sodium selenate at a rate of 0, 45.0 or 89.9 g Se/ha. Blood samples were collected biweekly and analyzed for whole-blood Se concentrations. Nasal swabs were collected during week 9 from one or two calves from each pen (total n = 16). Calculated Se intake from dietary sources was 3.0, 15.6, and 32.2 mg Se/head/day for calves consuming alfalfa hay with Se concentrations of 0.34 to 2.42 and 5.17 mg Se/kg dry matter, respectively. Whole-blood Se concentrations after 8 weeks of feeding Se-fertilized alfalfa hay were dependent upon Se-application rates (0, 45.0, or 89.9 g Se/ha) and were 155, 345, and 504 ng/mL (PLinear < 0.0001). Microbial DNA was extracted from nasal swabs and amplified and sequenced. Alpha rarefaction curves comparing the species richness (observed OTUs) and overall diversity (Chao1, Observed OTU, and Shannon index) between calves fed selenium-biofortified alfalfa hay compared with control calves showed that Se-supplementation tended to be associated with an enriched nasal microbiota. ANOSIM of unweighted UniFrac distances showed

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

PubMed

Wu, J R; Yeh, Y C

1975-05-01

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

What I Did Last Summer: The Fulbright-Hays Seminars Abroad.

ERIC Educational Resources Information Center

Martin, Marlene

2003-01-01

Describes the Fulbright-Hays seminar and the author's experience with it. Discusses the application process and experiences with Fulbright seminars in Poland, Hungary, Peru, and Ecuador. Notes how she and her colleagues use Fulbright information in their classrooms. (SG)

A CONTINUATION OF REMEDIATION OF BRINE SPILLS WITH HAY

EPA Science Inventory

First order rate constants for salt removal are shown in Table 1. For Gibbs 7, tilling with hay and fertilizers proved to be the best treatment for salt removal (80% confidence level, CL). For Gibbs 9, which is rockier than Gibbs 7, tilling was the best treatment for salt remo...

Carbohydrate and lipid spectroscopic molecular structures of different alfalfa hay and their relationship with nutrient availability in ruminants

PubMed Central

Yari, Mojtaba; Valizadeh, Reza; Nnaserian, Abbas Ali; Jonker, Arjan; Yu, Peiqiang

2017-01-01

Objective This study was conducted to determine molecular structures related to carbohydrates and lipid in alfalfa hay cut at early bud, late bud and early flower and in the afternoon and next morning using Fourier transform infrared spectroscopy (FT/IR) and to determine their relationship with alfalfa hay nutrient profile and availability in ruminants. Methods Chemical composition analysis, carbohydrate fractionation, in situ ruminal degradability, and DVE/OEB model were used to measure nutrient profile and availability of alfalfa hay. Univariate analysis, hierarchical cluster analysis (CLA) and principal components analysis (PCA) were conducted to identify FT/IR spectra differences. Results The FT/IR non-structural carbohydrate (NSCHO) to total carbohydrates and NSCHO to structural carbohydrate ratios decreased (p<0.05), while lignin to NSCHO and lipid CH3 symmetric to CH2 symmetric ratios increased with advancing maturity (p<0.05). The FT/IR spectra related to structural carbohydrates, lignin and lipids were distinguished for alfalfa hay at three maturities by PCA and CLA, while FT/IR molecular structures related to carbohydrates and lipids were similar between alfalfa hay cut in the morning and afternoon when analyzed by PCA and CLA analysis. Positive correlations were found for FT/IR NSCHO to total carbohydrate and NSCHO to structural carbohydrate ratios with non-fiber carbohydrate (by wet chemistry), ruminal fast and intermediately degradable carbohydrate fractions and total ruminal degradability of carbohydrates and predicted intestinal nutrient availability in dairy cows (r≥0.60; p<0.05) whereas FT/IR lignin to NSCHO and CH3 to CH2 symmetric stretching ratio had negative correlation with predicted ruminal and intestinal nutrient availability of alfalfa hay in dairy cows (r≥−0.60; p<0.05). Conclusion FT/IR carbohydrate and lipid molecular structures in alfalfa hay changed with advancing maturity from early bud to early flower, but not during the day

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

PubMed

Huang, Rongyong; Zheng, Shunyi; Hu, Kun

2018-06-01

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

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

PubMed Central

Liu, Wanli

2017-01-01

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

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

PubMed

Liu, Wanli

2017-03-08

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

Similarity, Induction, Naming, and Categorization (SINC): Generalization or Inductive Reasoning? Reply to Heit and Hayes (2005)

ERIC Educational Resources Information Center

Sloutsky, Vladimir M.; Fisher, Anna V.

2006-01-01

This article is a response to E. Heit and B. K. Hayes's comment on the target article "Induction and Categorization in Young Children: A Similarity-Based Model" (V. M. Sloutsky & A. V. Fisher, 2004a). The response discusses points of agreement and disagreement with Heit and Hayes; phenomena predicted by similarity, induction, naming, and…

Fulbright-Hays Seminars Abroad Program: Malaysia 1995. Participants' Reports.

ERIC Educational Resources Information Center

Malaysian-American Commission on Educational Exchange, Kuala Lumpur.

These reports and lesson plans were developed by teachers and coordinators who traveled to Malaysia during the summer of 1995 as part of the U.S. Department of Education's Fulbright-Hays Seminars Abroad Program. Sections of the report include: (1) "Gender and Economics: Malaysia" (Mary C. Furlong); (2) "Malaysia: An Integrated,…

Fulbright-Hays Seminars Abroad Program and Special Bilateral Projects

ERIC Educational Resources Information Center

Office of Postsecondary Education, US Department of Education, 2012

2012-01-01

The Fulbright-Hays Seminars Abroad Program and Special Bilateral Projects provides short-term study and travel seminars abroad for U.S. educators in the social sciences and humanities for the purpose of improving their understanding and knowledge of the people and culture of other countries. There are approximately 10 seminars with 16 participants…

Estimating stem volume and biomass of Pinus koraiensis using LiDAR data.

PubMed

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

2010-07-01

The objective of this study was to estimate the stem volume and biomass of individual trees using the crown geometric volume (CGV), which was extracted from small-footprint light detection and ranging (LiDAR) data. Attempts were made to analyze the stem volume and biomass of Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes of tree density: low (240 N/ha), medium (370 N/ha), and high (1,340 N/ha). To delineate individual trees, extended maxima transformation and watershed segmentation of image processing methods were applied, as in one of our previous studies. As the next step, the crown base height (CBH) of individual trees has to be determined; information for this was found in the LiDAR point cloud data using k-means clustering. The LiDAR-derived CGV and stem volume can be estimated on the basis of the proportional relationship between the CGV and stem volume. As a result, low tree-density plots had the best performance for LiDAR-derived CBH, CGV, and stem volume (R (2) = 0.67, 0.57, and 0.68, respectively) and accuracy was lowest for high tree-density plots (R (2) = 0.48, 0.36, and 0.44, respectively). In the case of medium tree-density plots accuracy was R (2) = 0.51, 0.52, and 0.62, respectively. The LiDAR-derived stem biomass can be predicted from the stem volume using the wood basic density of coniferous trees (0.48 g/cm(3)), and the LiDAR-derived above-ground biomass can then be estimated from the stem volume using the biomass conversion and expansion factors (BCEF, 1.29) proposed by the Korea Forest Research Institute (KFRI).

AmeriFlux US-A32 ARM-SGP Medford hay pasture

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

Kueppers, Lara; Torn, Margaret; Biraud, Sebastien

This is the AmeriFlux version of the carbon flux data for the site US-A32 ARM-SGP Medford hay pasture. Site Description - This site is located at the ARM SGP Extended Facility E32, 8 km West of Medford, OK

Development and validation of a 5-day-ahead hay fever forecast for patients with grass-pollen-induced allergic rhinitis.

PubMed

de Weger, Letty A; Beerthuizen, Thijs; Hiemstra, Pieter S; Sont, Jacob K

2014-08-01

One-third of the Dutch population suffers from allergic rhinitis, including hay fever. In this study, a 5-day-ahead hay fever forecast was developed and validated for grass pollen allergic patients in the Netherlands. Using multiple regression analysis, a two-step pollen and hay fever symptom prediction model was developed using actual and forecasted weather parameters, grass pollen data and patient symptom diaries. Therefore, 80 patients with a grass pollen allergy rated the severity of their hay fever symptoms during the grass pollen season in 2007 and 2008. First, a grass pollen forecast model was developed using the following predictors: (1) daily means of grass pollen counts of the previous 10 years; (2) grass pollen counts of the previous 2-week period of the current year; and (3) maximum, minimum and mean temperature (R (2)=0.76). The second modeling step concerned the forecasting of hay fever symptom severity and included the following predictors: (1) forecasted grass pollen counts; (2) day number of the year; (3) moving average of the grass pollen counts of the previous 2 week-periods; and (4) maximum and mean temperatures (R (2)=0.81). Since the daily hay fever forecast is reported in three categories (low-, medium- and high symptom risk), we assessed the agreement between the observed and the 1- to 5-day-ahead predicted risk categories by kappa, which ranged from 65 % to 77 %. These results indicate that a model based on forecasted temperature and grass pollen counts performs well in predicting symptoms of hay fever up to 5 days ahead.

Development and validation of a 5-day-ahead hay fever forecast for patients with grass-pollen-induced allergic rhinitis

NASA Astrophysics Data System (ADS)

de Weger, Letty A.; Beerthuizen, Thijs; Hiemstra, Pieter S.; Sont, Jacob K.

2014-08-01

One-third of the Dutch population suffers from allergic rhinitis, including hay fever. In this study, a 5-day-ahead hay fever forecast was developed and validated for grass pollen allergic patients in the Netherlands. Using multiple regression analysis, a two-step pollen and hay fever symptom prediction model was developed using actual and forecasted weather parameters, grass pollen data and patient symptom diaries. Therefore, 80 patients with a grass pollen allergy rated the severity of their hay fever symptoms during the grass pollen season in 2007 and 2008. First, a grass pollen forecast model was developed using the following predictors: (1) daily means of grass pollen counts of the previous 10 years; (2) grass pollen counts of the previous 2-week period of the current year; and (3) maximum, minimum and mean temperature ( R 2 = 0.76). The second modeling step concerned the forecasting of hay fever symptom severity and included the following predictors: (1) forecasted grass pollen counts; (2) day number of the year; (3) moving average of the grass pollen counts of the previous 2 week-periods; and (4) maximum and mean temperatures ( R 2 = 0.81). Since the daily hay fever forecast is reported in three categories (low-, medium- and high symptom risk), we assessed the agreement between the observed and the 1- to 5-day-ahead predicted risk categories by kappa, which ranged from 65 % to 77 %. These results indicate that a model based on forecasted temperature and grass pollen counts performs well in predicting symptoms of hay fever up to 5 days ahead.

Comparison of silage and hay of dwarf Napier grass (Pennisetum purpureum) fed to Thai native beef bulls.

PubMed

Mapato, Chaowarit; Wanapat, Metha

2018-03-23

Both quantity and quality of forages are important in dry season feeding. Eight Thai native beef bulls were arranged in a Completely randomized design to evaluate dwarf Napier namely Sweet grass (Pennisetum purpureum cv. Mahasarakham) preserved as silage or hay on feed intake, digestibility, and rumen fermentation. The animals were fed with forage ad libitum supplemented with concentrate mixture at 1.0% of BW for 21 days; data were collected during the last 7 days. The results showed that there were differences (P < 0.05) between treatments in dry matter (DM) intake, DM digestibility, and ruminal pH, in which hay feeding gave enhanced feed intake and more favorable ruminal pH. Nevertheless, mean ruminal ammonia nitrogen, total volatile fatty acids (TVFAs), proportion of VFAs, bacterial and protozoal population, and blood urea nitrogen were similar (P > 0.05) in animals fed silage and hay. Sweet grass is better preserved as hay rather than silage.

Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys

Treesearch

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

2012-01-01

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

A universal airborne LiDAR approach for tropical forest carbon mapping.

PubMed

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

2012-04-01

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

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

PubMed Central

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

2009-01-01

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

Localized Segment Based Processing for Automatic Building Extraction from LiDAR Data

NASA Astrophysics Data System (ADS)

Parida, G.; Rajan, K. S.

2017-05-01

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

Multispectral LiDAR Data for Land Cover Classification of Urban Areas

PubMed Central

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

2017-01-01

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. PMID:28445432

Multispectral LiDAR Data for Land Cover Classification of Urban Areas.

PubMed

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.

Effects of cattle grazing and haying on wildlife conservation at National Wildlife Refuges in the United States

NASA Astrophysics Data System (ADS)

Strassmann, Beverly I.

1987-01-01

The National Wildlife Refuge System is perhaps the most important system of federal lands for protecting wildlife in the United States. Only at refuges has wildlife conservation been legislated to have higher priority than either recreational or commercial activities. Presently, private ranchers and farmers graze cattle on 981,954 ha and harvest hay on 12,021 ha at 123 National Wildlife Refuges. US Fish and Wildlife Service policy is to permit these uses primarily when needed to benefit refuge wildlife. To evaluate the success of this policy, I surveyed grassland management practices at the 123 refuges. The survey results indicate that in fiscal year 1980 there were 374,849 animal unit months (AUMs) of cattle grazing, or 41% more than was reported by the Fish and Wildlife Service. According to managers' opinions, 86 species of wildlife are positively affected and 82 are negatively affected by refuge cattle grazing or haying. However, quantitative field studies of the effect of cattle grazing and haying on wildlife coupled with the survey data on how refuge programs are implemented suggest that these activities are impeding the goal of wildlife conservation. Particular management problems uncovered by the survey include overgrazing of riparian habitats, wildlife mortality due to collisions with cattle fences, and mowing of migratory bird habitat during the breeding season. Managers reported that they spend 919,740 administering cattle grazing and haying; thus refuge grazing and haying programs are also expensive. At any single refuge these uses occupy up to 50% of refuge funds and 55% of staff time. In light of these results, prescribed burning may be a better wildlife management option than is either cattle grazing or haying.

Rockfall hazard analysis using LiDAR and spatial modeling

NASA Astrophysics Data System (ADS)

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].

PubMed

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

2014-11-01

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

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

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

Treesearch

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

2010-01-01

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

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

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

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

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

Treesearch

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

2016-01-01

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

Religious Literacy or Spiritual Awareness? Comparative Critique of Andrew Wright's and David Hay's Approaches to Spiritual Education

ERIC Educational Resources Information Center

Filipsone, Anta

2009-01-01

On the basis of a comparison of the educational approaches of Andrew Wright and David Hay this paper illustrates the persisting problem of dichotomising cognitive and trans-cognitive aspects of spiritual development and education. Even though both Wright and Hay speak of the same topic--spirituality and spiritual education--they define these terms…

40 CFR 180.123a - Inorganic bromide residues in peanut hay and peanut hulls; statement of policy.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 24 2011-07-01 2011-07-01 false Inorganic bromide residues in peanut hay and peanut hulls; statement of policy. 180.123a Section 180.123a Protection of Environment... RESIDUES IN FOOD Specific Tolerances § 180.123a Inorganic bromide residues in peanut hay and peanut hulls...

40 CFR 180.123a - Inorganic bromide residues in peanut hay and peanut hulls; statement of policy.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 23 2010-07-01 2010-07-01 false Inorganic bromide residues in peanut hay and peanut hulls; statement of policy. 180.123a Section 180.123a Protection of Environment... combines and leave the hay on the ground to be incorporated into the soil, some growers follow the practice...

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

DOT National Transportation Integrated Search

2009-02-01

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

Gravid Anopheles gambiae sensu stricto avoid ovipositing in Bermuda grass hay infusion and it's volatiles in two choice egg-count bioassays.

PubMed

Eneh, Lynda K; Okal, Michael N; Borg-Karlson, Anna-Karin; Fillinger, Ulrike; Lindh, Jenny M

2016-05-12

A number of mosquito species in the Culex and Aedes genera prefer to lay eggs in Bermuda grass (Cynodon dactylon) hay infusions compared to water alone. These mosquitoes are attracted to volatile compounds from the hay infusions making the infusions effective baits in gravid traps used for monitoring vectors of arboviral and filarial pathogens. Since Bermuda grass is abundant and widespread, it is plausible to explore infusions made from it as a potential low cost bait for outdoor monitoring of the elusive malaria vector Anopheles gambiae s.s. This study investigated preferential egg laying of individual An. gambiae s.s. in hay infusion or in tap water treated with volatiles detected in hay infusion headspace compared to tap water alone, using two-choice egg-count bioassays. Infusions were prepared by mixing 90 g of dried Bermuda grass (hay) with 24 L of unchlorinated tap water in a bucket, and leaving it for 3 days at ambient temperature and humidity. The volatiles in the headspace of the hay infusion were sampled with Tenax TA traps for 20 h and analysed using gas chromatography coupled to mass spectrometry. In total, 18 volatiles were detected in the infusion headspace. Nine of the detected compounds and nonanal were selected for bioassays. Eight of the selected compounds have previously been suggested to attract/stimulate egg laying in An. gambiae s.s. Gravid females were significantly (p < 0.05) less likely to lay eggs in hay infusion dilutions of 25, 50 and 100 % and in tap water containing any of six compounds (3-methylbutanol, phenol, 4-methylphenol, nonanal, indole, and 3-methylindole) compared to tap water alone. The oviposition response to 10 % hay infusion or any one of the remaining four volatiles (4-hepten-1-ol, phenylmethanol, 2-phenylethanol, or 4-ethylphenol) did not differ from that in tap water. Anopheles gambiae s.s. prefers to lay eggs in tap water rather than Bermuda grass hay infusion. This avoidance of the hay infusion appears to be

Building Damage Assessment after Earthquake Using Post-Event LiDAR Data

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Experimental lead toxicosis in ponies: comparison of the effects of smelter effluent-contaminated hay and lead acetate

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

Burrows, G.E.; Borchard, R.E.

1982-12-01

Grass hay produced in the Coeur d'Alene River Basin of northern Idaho was fed to a group of 4 ponies. The hay contained Pb in concentration of 423 +/- 82 mg/kg and Cd in concentration of 10.8 +/- 1.4 mg/kg, resulting in daily exposures of the ponies to approximately 7.4 mg of Pb/kg and 0.19 mg of Cd/kg/day. The results in this group of ponies were compared with those from a group fed noncontaminated grass hay and given a daily dose of 10 mg of Pb/kg of body weight, in the form of lead acetate. Clinical toxicologic signs, hematologic changes,more » and blood and tissue Pb concentrations were similar in the 2 groups. However, the severity of the disease process appeared to be greater in the ponies fed the Pb- and Cd-contaminated hay. This was shown clearly by the shorter interval between onset of clinical changes and death in the ponies fed contaminated hay. The possibility of multiple heavy metal effects is discussed. Clinical toxicologic signs observed include incoordination, labial paresis, pharyngeal paresis, CNS depression, anorexia, and body weight loss. Anemia or marginal anemia was common and was often accompanied by the appearance of nucleated RBC and Howell-Jolly bodies in peripheral blood. Neither the hematologic response nor the blood Pb concentrations were reflective of the severity of poisoning, although blood Pb concentrations were greater than 0.35 micrograms/ml once clinical signs of toxicity were observed. Liver, kidney, spleen, brain, and bone Pb concentrations and liver, kidney, and brain Cd concentrations were increased in both the ponies fed contaminated hay and the ponies given lead acetate.« less

International Students at Fort Hays State University: An Impact Analysis.

ERIC Educational Resources Information Center

Potts, Joe D.

This paper presents a summary of selected data and issues related to international education at Fort Hays State University (FHSU) in Kansas focusing specifically on international student populations. The paper also outlines results of recent initiatives to increase international student enrollment at FHSU together with a summary of arguments…

Association between climate factors, pollen counts, and childhood hay fever prevalence in the United States.

PubMed

Silverberg, Jonathan I; Braunstein, Marc; Lee-Wong, Mary

2015-02-01

Climate factors and pollen counts may play a role in hay fever. We sought to determine the impact of specific climate factors and pollen counts on the US prevalence of hay fever and statewide variation in prevalence. We used a merged analysis of the 2007 National Survey of Children's Health from a representative sample of 91,642 children aged 0 to 17 years and the 2006-2007 National Climate Data Center and Weather Service measurements of relative humidity (%), indoor heating degree days, precipitation, Palmer Hydrological Drought Index, clear sky and issued ultraviolet indices, stratospheric ozone levels, and outdoor air temperature and National Allergy Bureau total pollen counts. Multivariate survey logistic regression models controlled for sex, race/ethnicity, age, household income, and birthplace. The US prevalence of hay fever in childhood was 18.0% (95% CI, 17.7% to 18.2%), with the highest prevalence in southeastern and southern states. Hay fever prevalence was significantly lower with second and third quartile mean annual relative humidity (logistic regression, P ≤ .01 for both), fourth quartile mean annual Palmer Hydrological Drought Index (P = .02), third and fourth quartile mean annual heating degree days (P < .0001 for both), and third and fourth quartile mean annual stratospheric ozone levels but increased with second, third, and fourth quartile mean annual temperature (P ≤ .02 for both), fourth quartile mean annual precipitation (P = .0007), mean total pollen counts (P = .01), and second, third, and fourth quartile issued ultraviolet index (P ≤ .0001 for all). Principal-component analysis was also used to determine the combined effects of correlated climate variables and pollen counts. This study provides evidence of the influence of climate on the US prevalence of childhood hay fever. Copyright © 2014 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Surface characteristics modeling and performance evaluation of urban building materials using LiDAR data.

PubMed

Li, Xiaolu; Liang, Yu

2015-05-20

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

The IsoDAR high intensity H2+ transport and injection tests

NASA Astrophysics Data System (ADS)

Alonso, J.; Axani, S.; Calabretta, L.; Campo, D.; Celona, L.; Conrad, J. M.; Day, A.; Castro, G.; Labrecque, F.; Winklehner, D.

2015-10-01

This technical report reviews the tests performed at the Best Cyclotron Systems, Inc. facility in regards to developing a cost effective ion source, beam line transport system, and acceleration system capable of high H2+ current output for the IsoDAR (Isotope Decay At Rest) experiment. We begin by outlining the requirements for the IsoDAR experiment then provide overviews of the Versatile Ion Source (VIS), Low Energy Beam Transport (LEBT) system, spiral inflector, and cyclotron. The experimental measurements are then discussed and the results are compared with a thorough set of simulation studies. Of particular importance we note that the VIS proved to be a reliable ion source capable of generating a large amount of H2+ current. The results suggest that with further upgrades, the VIS could potentially be a suitable candidate for IsoDAR. The conclusion outlines the key results from our tests and introduces the forthcoming work this technical report has motivated.

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

PubMed

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

1994-11-01

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

Monensin and ammoniation or urea supplementation of bermudagrass hay diets for steers.

PubMed

Vagnoni, D B; Craig, W M; Gates, R N; Wyatt, W E; Southern, L L

1995-06-01

One growth trial using crossbred beef steers (297 +/- 2 kg, Exp. 1) and one metabolism trial using Holstein steers (405 +/- 14 kg, Exp. 2) were conducted to evaluate effects of ammoniation (3% of hay DM, added as anhydrous NH3) vs urea supplementation with or without monensin supplementation of mature 'Alicia' bermudagrass hay-based diets for steers. Ammoniation (P < .05), but not urea (P = .26) or monensin (P = .70) supplementation, increased ADG in Exp. 1. In Exp. 2 ammoniation increased hay DMI (P < .05), but urea (P = .88) or monensin (P = .16) had no effect. Supplementation with either monensin (P < .05) or urea (P < .05) decreased ruminal total VFA concentrations. Monensin also decreased the ruminal acetate:propionate ratio (P < .001) and increased ruminal pH (P < .05). Addition of urea to the concentrate supplement decreased the rate of concentrate intake. Both the rate (P < .05) and the potential extent (P < .001) of ruminal forage in situ DM and NDF disappearance were increased by ammonia treatment. Dietary interactions (P < .10) were detected between monensin and ammoniation for rate and potential extent of in situ NDF disappearance and between monensin and urea supplementation (P < .05) for ruminal total free amino acid concentrations. Decreased concentrations of VFA and lower forage digestibilities observed with monensin supplementation in Exp. 2 may explain the failure of monensin to affect ADG in Exp. 1.

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

PubMed

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

2016-12-31

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

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

PubMed Central

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

2016-01-01

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

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

USGS Publications Warehouse

Reddy, Ashwan D.; Hawbaker, Todd J.; Wurster, F.; Zhu, Zhiliang; Ward, S.; Newcomb, Doug; Murray, R.

2015-01-01

Peatlands are a major reservoir of global soil carbon, yet account for just 3% of global land cover. Human impacts like draining can hinder the ability of peatlands to sequester carbon and expose their soils to fire under dry conditions. Estimating soil carbon loss from peat fires can be challenging due to uncertainty about pre-fire surface elevations. This study uses multi-temporal LiDAR to obtain pre- and post-fire elevations and estimate soil carbon loss caused by the 2011 Lateral West fire in the Great Dismal Swamp National Wildlife Refuge, VA, USA. We also determine how LiDAR elevation error affects uncertainty in our carbon loss estimate by randomly perturbing the LiDAR point elevations and recalculating elevation change and carbon loss, iterating this process 1000 times. We calculated a total loss using LiDAR of 1.10 Tg C across the 25 km2 burned area. The fire burned an average of 47 cm deep, equivalent to 44 kg C/m2, a value larger than the 1997 Indonesian peat fires (29 kg C/m2). Carbon loss via the First-Order Fire Effects Model (FOFEM) was estimated to be 0.06 Tg C. Propagating the LiDAR elevation error to the carbon loss estimates, we calculated a standard deviation of 0.00009 Tg C, equivalent to 0.008% of total carbon loss. We conclude that LiDAR elevation error is not a significant contributor to uncertainty in soil carbon loss under severe fire conditions with substantial peat consumption. However, uncertainties may be more substantial when soil elevation loss is of a similar or smaller magnitude than the reported LiDAR error.

Independent evaluation of the SNODAS snow depth product using regional scale LiDAR-derived measurements

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Erratum: Food hygiene assessment in catering establishments in Hay Hassani district-Casablanca

PubMed Central

2017-01-01

This erratum corrects “Food hygiene assessment in catering establishments in Hay Hassani district-Casablanca.” The Pan African Medical Journal. 2016;24:335. doi:10.11604/pamj.2016.24.335.9171 PMID:29158859

FT-IR spectroscopic analysis for studying Clostridium cell response to conversion of enzymatically hydrolyzed hay

NASA Astrophysics Data System (ADS)

Grube, Mara; Gavare, Marita; Nescerecka, Alina; Tihomirova, Kristina; Mezule, Linda; Juhna, Talis

2013-07-01

Grass hay is one of assailable cellulose containing non-food agricultural wastes that can be used as a carbohydrate source by microorganisms producing biofuels. In this study three Clostridium strains Clostridium acetobutylicum, Clostridium beijerinckii and Clostridium tetanomorphum, capable of producing acetone, butanol and ethanol (ABE) were adapted to convert enzymatically hydrolyzed hay used as a growth media additive. The results of growth curves, substrate degradation kinetics and FT-IR analyses of bacterial biomass macromolecular composition showed diverse strain-specific cell response to the growth medium composition.

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

NASA Astrophysics Data System (ADS)

Suiter, Ashley Elizabeth

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

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

PubMed Central

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

1994-01-01

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

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

Onojeghuo, Alex Okiemute; Onojeghuo, Ajoke Ruth

2017-07-01

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

Automatic 3d Building Model Generations with Airborne LiDAR Data

NASA Astrophysics Data System (ADS)

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

INTERIOR VIEW OF HAY STORAGE, LOOKING NORTH. The barn is ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

INTERIOR VIEW OF HAY STORAGE, LOOKING NORTH. The barn is constructed of hand-hewn, 10" square post and beams with mortise and tenon, pegged joints. The photograph also shows the hayfork and track, double doors on the north façade, and window opening. - Boyer Farm, Barn, 711 South Fort Casey Road, Coupeville, Island County, WA

A broader definition of occupancy: Comment on Hayes and Monfils

Treesearch

Quresh S. Latif; Martha M. Ellis; Courtney L. Amundson

2016-01-01

Occupancy models are widely used to analyze presence-absence data for a variety of taxa while accounting for observation error (MacKenzie et al. 2002, 2006; Tyre et al. 2003; Royle and Dorazio 2008). Hayes and Monfils (2015) question their use for analyzing avian point count data based on purported violations of model assumptions incurred by avian mobility....

LiDAR collection in August 2015 over the East River Watershed, Colorado, USA

DOE Data Explorer

Wainwright, Haruko [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Kenneth

2017-01-01

Airborne LiDAR data were acquired over the study area on August 10th, 2015, using a Riegl Q1560 dual-channel LiDAR system mounted on a Piper Navajo. The survey was performed by Quantum Spatial in collaboration with Eagle Mapping Ltd. The data complies with the USGS QL1 standard [Heideman, 2014] with the point density more than 8 pulse per m2.

Rapid topographic and bathymetric reconnaissance using airborne LiDAR

NASA Astrophysics Data System (ADS)

Axelsson, Andreas

2010-10-01

Today airborne LiDAR (Light Detection And Ranging) systems has gained acceptance as a powerful tool to rapidly collect invaluable information to assess the impact from either natural disasters, such as hurricanes, earthquakes and flooding, or human inflicted disasters such as terrorist/enemy activities. Where satellite based imagery provides an excellent tool to remotely detect changes in the environment, the LiDAR systems, being active remote sensors, provide an unsurpassed method to quantify these changes. The strength of the active laser based systems is especially evident in areas covered by occluding vegetation or in the shallow coastal zone as the laser can penetrate the vegetation or water body to unveil what is below. The purpose of this paper is to address the task to survey complex areas with help of the state-of-the-art airborne LiDAR systems and also discuss scenarios where the method is used today and where it may be used tomorrow. Regardless if it is a post-hurricane survey or a preparation stage for a landing operation in unchartered waters, it is today possible to collect, process and present a dense 3D model of the area of interest within just a few hours from deployment. By utilizing the advancement in processing power and wireless network capabilities real-time presentation would be feasible.

LiDAR observation of the flow structure in typhoons

NASA Astrophysics Data System (ADS)

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.

Food hygiene assessment in catering establishments in Hay Hassani district-Casablanca.

PubMed

Kadmiri, Nadia El; Bakouri, Halima; Bassir, Fatima; Barmaki, Saadia; Rachad, Laila; Nadifi, Sellama; Kadmiri, Omar El; Amina, Bouleghmane

2016-01-01

Contaminated food is responsible for a significant amount of illnesses. In Morocco, it has become a worrying concern. Numerous awareness campaigns are conducted to warn the population against the risks of such scourge in ways that will prevent foodborne illness. Lawful commissions are in charge of examining and ensuring food safety in production and catering establishments, in addition to the assessment of food poisoning risks. The aim of this study is to evaluate the hygienic quality of food handling, preparation, and storage in catering establishments within Hay Hassani prefecture in Casablanca. During the period 2006-2012 a total of 1765 food samples were taken and examined for microbiological quality tests. As analyzed, 562 per 1765 samples are declared unhealthy for consumption. We note that some products were highly contaminated as compared to other products (p <0.001), specifically vegetable dishes, and meat dishes. In Hay Hassani district food is generally prepared and sold under unhygienic conditions, adequate corrective measures have been announced to improve hygienic practices.

Hay fever, asthma, and eczema and early infectious diseases among children in Kilimanjaro, Tanzania.

PubMed

Wander, Katherine; Shell-Duncan, Bettina; Brindle, Eleanor; O'Connor, Kathleen

2017-05-06

To investigate the hygiene (or "old friends") hypothesis in a high-infectious disease (ID) environment, rural Kilimanjaro, Tanzania. Among a cross-sectional sample of 2- to 7-year-old children, we collected physician-diagnosed hay fever, asthma, and eczema, history of hospitalization, family size, and household environment information via questionnaire; performed active and passive surveillance for ID; and, evaluated total immunoglobulin E (IgE) and biomarkers of inflammation in dried blood spot specimens. We used regression models to describe patterns in allergic diseases. Complete information was available for 280 children: 12.5% had been diagnosed with hay fever; 18.9% with eczema; 2.1% with asthma. There was a positive association between hay fever and eczema diagnoses (π 2 : 4.07; P = 0.044); total IgE was positively associated with eczema (β: 0.24; P = 0.100) and allergic diseases together (β: 0.26; P = 0.042). ID were common: the incidence of any ID diagnosis was 28 per 100 children per month. Hay fever was inversely associated with household animals (OR: 0.27; P = 0.006), and positively associated with earth housing materials (OR: 1.93; P = 0.079) and hospitalization in infancy with an ID (3.16; P = 0.066); patterns were similar when allergic disease outcomes were considered together. Few associations between these predictors and eczema or asthma alone were apparent. Allergic diseases were common among children in Kilimanjaro. The inverse association between household animals and allergy is consistent with the hygiene/old friends hypothesis; however, positive associations between allergic diseases and earth housing materials and early hospitalization with ID bear further explanation. © 2017 Wiley Periodicals, Inc.

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

DTIC Science & Technology

2008-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

Franceschi, Silvia; Antonello, Andrea; Tonon, Giustino

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Predicting TDN losses from heat damaged hays and haylages with NIR

USDA-ARS?s Scientific Manuscript database

During the storage of hay or haylage, heating damage may occur and lead to losses of available protein and digestible nutrients. Recent research indicates that losses of TDN may be more significant economically than losses of available protein. Our objectives for this study were to establish a near-...

Volatile fatty acid profile for grass hay or alfalfa hay fed to alpacas (Vicugna pacos).

PubMed

Oldham, C L; Robinson, T F; Hunter, Z R; Taylor, L; White, J; Johnston, N P

2014-10-01

The purpose of this study was to determine the diurnal composition and concentration of volatile fatty acids (VFA) and to determine VFA composition and concentration differences between stomach compartment 1 (C1) and caecum of alpacas fed grass and alfalfa hay. The study was divided into two experiments. In Experiment 1 (EXP 1), 10 male alpacas (3+ years old, 65 kg BW) were divided into two groups, housed in drylot pens, provided ad libitum water and fed alfalfa (AH) or grass hay (GH) for 30 days. The alpacas were slaughtered and the digestive tract collected, divided into sub-tract sections, weighed and digesta sampled for pH, dry matter (DM) and NDF. Volatile fatty acid composition and concentration were determined on C1 and caecal material. Four adult male (3+ years old, 60 kg BW), C1 fistulated alpacas were housed in metabolism crates and divided into two forage groups for Experiment 2 (EXP 2). Alpacas were fed the forages as in EXP 1. Diurnal C1 VFA samples were drawn at 1, 3, 6, 9, 12, 18 and 24 h post-feeding. There were no differences between forages for tract weight, C1 and caecum digesta DM or NDF. Differences were noted (p < 0.05) for pH between forages and sub-tract site. Volatile fatty acids concentrations were different (p < 0.05) for forage and site, and total VFA was higher for AH than GH (110.6 and 79.1 mm) and C1 than caecum (40.7 and 27.6 mm). Proportion of VFA was significant (p < 0.05) for forage and site, C1 acetate highest for GH (84.8 vs. 74.0 mm) and caecum acetate 83.7 and 76.2 mm for GH and AH respectively. These data demonstrate the level of VFA produced in C1 and the caecum of alpacas and the diurnal VFA patterns. Composition of VFA is similar to other ruminant species. Journal of Animal Physiology and Animal Nutrition © 2013 Blackwell Verlag GmbH.

Abu Dhabi Basemap Update Using the LiDAR Mobile Mapping Technology

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Hayes Receives 2012 Ronald Greeley Early Career Award in Planetary Science: Citation

NASA Astrophysics Data System (ADS)

Leshin, Laurie A.

2013-10-01

Alexander G. Hayes Jr. received the 2012 Ronald Greeley Early Career Award in Planetary Science at the 2012 AGU Fall Meeting, held 3-7 December in San Francisco, Calif. The award recognizes significant early-career contributions to planetary science.

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

PubMed Central

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

2013-01-01

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

Effects of LiDAR point density and landscape context on estimates of urban forest biomass

NASA Astrophysics Data System (ADS)

Singh, Kunwar K.; Chen, Gang; McCarter, James B.; Meentemeyer, Ross K.

2015-03-01

Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional

Registration of Panoramic/Fish-Eye Image Sequence and LiDAR Points Using Skyline Features

PubMed Central

Zhu, Ningning; Jia, Yonghong; Ji, Shunping

2018-01-01

We propose utilizing a rigorous registration model and a skyline-based method for automatic registration of LiDAR points and a sequence of panoramic/fish-eye images in a mobile mapping system (MMS). This method can automatically optimize original registration parameters and avoid the use of manual interventions in control point-based registration methods. First, the rigorous registration model between the LiDAR points and the panoramic/fish-eye image was built. Second, skyline pixels from panoramic/fish-eye images and skyline points from the MMS’s LiDAR points were extracted, relying on the difference in the pixel values and the registration model, respectively. Third, a brute force optimization method was used to search for optimal matching parameters between skyline pixels and skyline points. In the experiments, the original registration method and the control point registration method were used to compare the accuracy of our method with a sequence of panoramic/fish-eye images. The result showed: (1) the panoramic/fish-eye image registration model is effective and can achieve high-precision registration of the image and the MMS’s LiDAR points; (2) the skyline-based registration method can automatically optimize the initial attitude parameters, realizing a high-precision registration of a panoramic/fish-eye image and the MMS’s LiDAR points; and (3) the attitude correction values of the sequences of panoramic/fish-eye images are different, and the values must be solved one by one. PMID:29883431

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

PubMed

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

2016-05-30

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

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Tradition and Transformation. Fulbright Hays Summer Seminar Abroad Program 1995 (China).

ERIC Educational Resources Information Center

National Committee on United States-China Relations, New York, NY.

These projects were completed by participants in the Fulbright-Hays seminar in China in 1995. The participants represented various regions of the U.S. and different grade levels and subject areas. The units include: (1) "Travel Guide to China" (Marcy Adelson); (2) "Traditional and Contemporary Values of China" (Peter Ciemins);…

Estimation of the fraction of absorbed photosynthetically active radiation (fPAR) in maize canopies using LiDAR data and hyperspectral imagery.

PubMed

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.

Supporting Indonesia's National Forest Monitoring System with LiDAR Observations

NASA Astrophysics Data System (ADS)

Hagen, S. C.

2015-12-01

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

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

PubMed

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

2013-08-01

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

LiDAR data and SAR imagery acquired by an unmanned helicopter for rapid landslide investigation

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Geologic framework and hydrogeologic characteristics of the Edwards Aquifer outcrop, Hays County, Texas

USGS Publications Warehouse

Hanson, John A.; Small, Ted A.

1995-01-01

All of the hydrogeologic subdivisions within the Edwards aquifer outcrop in Hays County have some porosity and permeability. The most porous and permeable appear to be hydrogeologic subdivision VI, the Kirschberg evaporite member of the Kainer Formation; hydrogeologic subdivision III, the leached and collapsed members, undivided; and hydrogeologic subdivision II, the cyclic and marine members, undivided, of the Person Formation. The two types of porosity in the Edwards aquifer outcrop are fabric selective, which is related to depositional or diagenetic elements and typically exists in specific stratigraphic horizons; and not fabric selective, which can exist in any lithostratigraphic horizon. Permeability, the capacity of porous rock to transmit water, depends on the physical properties of the rock such as size, shape, and distribution of pores, and fissuring and dissolution. Two faults, San Marcos Springs and Mustang Branch, completely, or almost completely, offset the Edwards aquifer by juxtaposing Edwards aquifer limestone against nearly impermeable upper confining units along parts of their traces across Hays County. These faults are thought to be barriers, or partial barriers, to groundwater flow where the beds are juxtaposed. In Hays County, the Edwards aquifer probably is most vulnerable to surface contamination in the rapidly urbanizing areas on the Edwards aquifer outcrop. Contamination can result from spills or leakage of hazardous materials; or runoff on the intensely faulted and fractured, karstic limestone outcrops characteristic of the recharge zone.

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

DOT National Transportation Integrated Search

2009-02-01

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

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

PubMed Central

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

2009-01-01

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

Timely binding of IHF and Fis to DARS2 regulates ATP–DnaA production and replication initiation

PubMed Central

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

2014-01-01

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

Timely binding of IHF and Fis to DARS2 regulates ATP-DnaA production and replication initiation.

PubMed

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

2014-12-01

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

Fulbright-Hays Seminars Abroad Program 1992: Morocco and Tunisia. Final Projects.

ERIC Educational Resources Information Center

AMIDEAST, Washington, DC.

The projects described in this document were submitted by U.S. teachers who spent time in Morocco and Tunisia as part of the 1992 Fulbright-Hays Seminars Abroad Program. The following are among the titles of the projects included: "Formal Education in Rural Morocco: Problems and Constraints" (Victoria Baker); "Continuity and Change…

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

NASA Astrophysics Data System (ADS)

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.

On Feature Extraction from Large Scale Linear LiDAR Data

NASA Astrophysics Data System (ADS)

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

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

PubMed

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

2015-09-30

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

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

NASA Technical Reports Server (NTRS)

Cook, Bruce D.; Asner, Gregory P.

2010-01-01

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

Effects of feeding pregnant beef cows selenium-enriched alfalfa hay on selenium status and antibody titers in their newborn calves.

PubMed

Wallace, L G; Bobe, G; Vorachek, W R; Dolan, B P; Estill, C T; Pirelli, G J; Hall, J A

2017-06-01

In newborn dairy calves, it has been demonstrated that supranutritional maternal and colostral Se supplementation using Se yeast or sodium selenite, respectively, improves passive transfer of IgG. In beef cattle, agronomic biofortification with Se is a more practical alternative for Se supplementation, whereby the Se concentration of hay is increased through the use of Se-containing fertilizer amendments. It has been previously demonstrated that agronomic Se biofortification is an effective strategy to improve immunity and performance in Se-replete weaned beef calves. The objective of this experiment was to determine the effects of feeding beef cows Se-enriched alfalfa () hay during the last 8 to 12 wk of gestation on passive transfer of antibodies to calves. At 10 wk ± 16 d before calving, 45 cows were assigned to 1 of 3 treatment groups with 3 pens (5 cows/pen) per treatment: Control cows were fed non-Se-fortified alfalfa hay plus a mineral supplement containing 120 mg/kg Se from sodium selenite, Med-Se cows were fed alfalfa hay fertilized with 45.0 g Se/ha as sodium selenate, and High-Se cows were fed alfalfa hay fertilized with 89.9 g Se/ha as sodium selenate; both the Med-Se and the High-Se groups received mineral supplement without added Se. Colostrum and whole blood (WB) were collected from cows at calving, and WB was collected from calves within 2 h of calving and at 12, 24, 36, and 48 h of age. Concentrations of IgG1 and J-5 antibody in cow colostrum and calf serum were quantified using ELISA procedures. Selenium concentrations linearly increased in WB ( < 0.001) and colostrum ( < 0.001) of cows and in WB of newborn calves ( < 0.001) with increasing Se concentration in alfalfa hay. Colostrum concentrations of IgG1 ( = 0.03) were increased in cows fed Se-biofortified alfalfa hay, but J-5 antibody ( = 0.43) concentrations were not. Calf serum IgG1 ( = 0.43) and J-5 antibody ( = 0.44) concentrations during the first 48 h of age were not affected by prior Se

Effects of alfalfa hay and its physical form (chopped versus pelleted) on performance of Holstein calves.

PubMed

Jahani-Moghadam, M; Mahjoubi, E; Hossein Yazdi, M; Cardoso, F C; Drackley, J K

2015-06-01

Inclusion of forage and its physical form in starter may affect rumen development, average daily gain (ADG), and dry matter intake (DMI) of dairy calves. To evaluate the effects of forage and its physical form (chopped vs. pelleted) on growth of calves under a high milk feeding regimen, 32 Holstein calves (38.8±1.1kg) were assigned at birth to 1 of 3 treatments in a completely randomized block design. Dietary treatments (% of dry matter) were (1) 100% semi-texturized starter (CON); (2) 90% semi-texturized starter + 10% chopped alfalfa hay (mean particle size=5.4mm) as a total mixed ration (TMR; CH); and (3) 90% semi-texturized starter + 10% pelleted alfalfa (mean=5.8mm) hay as a TMR (PH). Data were subjected to mixed model analysis with contrasts used to evaluate effect of forage inclusion. Calves were weaned at 76 d of age and the experiment finished 2 wk after weaning. Individual milk and solid feed consumption were recorded daily. Solid feed consumption and ADG increased as age increased (effect of week), but neither forage inclusion nor physical form of forage affected these variables pre- or postweaning. Plasma urea N was affected by treatments such that the CON group had a lower concentration than forage-fed groups. Forage inclusion, but not physical form, resulted in increased total protein in plasma. Although days with elevated rectal temperature, fecal score, and general appearance were not affected by dietary treatments, calves fed alfalfa hay during the first month of life had fewer days with respiratory issues, regardless of physical form of hay. We concluded that provision of forage does have some beneficial effects in calves fed large amounts of milk replacer, but pelleted alfalfa hay did not result in any improvement in calf performance or health. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

PubMed

Delagrange, Sylvain; Rochon, Pascal

2011-10-01

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

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

Treesearch

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

2013-01-01

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

A broader definition of occupancy: A reply to Hayes and Monofils

USGS Publications Warehouse

Fatif, Quresh; Ellis, Martha M.; Amundson, Courtney L.

2015-01-01

Occupancy models are widely used to analyze presence–absence data for a variety of taxa while accounting for observation error (MacKenzie et al. 2002, 2006; Tyre et al. 2003; Royle and Dorazio 2008). Hayes and Monfils (2015) question their use for analyzing avian point count data based on purported violations of model assumptions incurred by avian mobility. Animal mobility is an important consideration, not just for occupancy models, but for a variety of population and habitat models (Boyce 2006, Royle et al. 2009, Manning and Goldberg 2010, Dormann et al. 2013, Renner et al. 2015). Nevertheless, we believe the ultimate conclusions of Hayes and Monfils are shortsighted mainly due to a narrow interpretation of occupancy. Rather than turn away from the use of occupancy models, we believe they remain an appropriate method for analyzing many data sets collected from avian point count surveys. Further, we suggest that there is value in having a broader and more nuanced interpretation of occupancy that incorporates the potential for animal movement. 

Food hygiene assessment in catering establishments in Hay Hassani district-Casablanca

PubMed Central

Kadmiri, Nadia El; Bakouri, Halima; Bassir, Fatima; Barmaki, Saadia; Rachad, Laila; Nadifi, Sellama; Kadmiri, Omar El; Amina, Bouleghmane

2016-01-01

Contaminated food is responsible for a significant amount of illnesses. In Morocco, it has become a worrying concern. Numerous awareness campaigns are conducted to warn the population against the risks of such scourge in ways that will prevent foodborne illness. Lawful commissions are in charge of examining and ensuring food safety in production and catering establishments, in addition to the assessment of food poisoning risks. The aim of this study is to evaluate the hygienic quality of food handling, preparation, and storage in catering establishments within Hay Hassani prefecture in Casablanca. During the period 2006-2012 a total of 1765 food samples were taken and examined for microbiological quality tests. As analyzed, 562 per 1765 samples are declared unhealthy for consumption. We note that some products were highly contaminated as compared to other products (p <0.001), specifically vegetable dishes, and meat dishes. In Hay Hassani district food is generally prepared and sold under unhygienic conditions, adequate corrective measures have been announced to improve hygienic practices. PMID:28154690

Effects of feeding selenium-enriched alfalfa hay on immunity and health of weaned beef calves.

PubMed

Hall, Jean A; Bobe, Gerd; Vorachek, William R; Hugejiletu; Gorman, M Elena; Mosher, Wayne D; Pirelli, Gene J

2013-12-01

Previously, we reported that feeding selenium (Se)-enriched forage improves antibody titers in mature beef cows, and whole-blood Se concentrations and growth rates in weaned beef calves. Our current objective was to test whether beef calves fed Se-enriched alfalfa hay during the transition period between weaning and movement to a feedlot also have improved immune responses and slaughter weights. Recently weaned beef calves (n = 60) were fed an alfalfa-hay-based diet for 7 weeks, which was harvested from fields fertilized with sodium selenate at 0, 22.5, 45.0, or 89.9 g Se/ha. All calves were immunized with J-5 Escherichia coli bacterin. Serum was collected for antibody titers 2 weeks after the third immunization. Whole-blood neutrophils collected at 6 or 7 weeks were evaluated for total antioxidant potential, bacterial killing activity, and expression of genes associated with selenoproteins and innate immunity. Calves fed the highest versus the lowest level of Se-enriched alfalfa hay had higher antibody titers (P = 0.02), thioredoxin reductase-2 mRNA levels (P = 0.07), and a greater neutrophil total antioxidant potential (P = 0.10), whereas mRNA levels of interleukin-8 receptor (P = 0.02), L-selectin (P = 0.07), and thioredoxin reductase-1 (P = 0.07) were lower. In the feedlot, calves previously fed the highest-Se forage had lower mortality (P = 0.04) and greater slaughter weights (P = 0.02). Our results suggest that, in areas with low-forage Se concentrations, feeding beef calves Se-enriched alfalfa hay during the weaning transition period improves vaccination responses and subsequent growth and survival in the feedlot.

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

PubMed

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

2015-08-01

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

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

Treesearch

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

2017-01-01

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

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

Treesearch

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

2013-01-01

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

China: Tradition and Transformation. Curriculum Projects. 1993 Fulbright Hays Seminar Abroad Program.

ERIC Educational Resources Information Center

National Committee on United States-China Relations, New York, NY.

Sixteen participants in the 1993 Fulbright Hays Seminar Abroad Program present curriculum projects that focus on tradition and transformation in China. The curriculum projects highlight the diversity of interests and disciplines of the participants and offer ideas for various educational levels. The projects include: (1) "Beijing…

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

PubMed

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

2016-12-01

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

Effect of mixed hay supplementation during fattening on carcass traits and meat quality of Hanwoo steers.

PubMed

Utama, Dicky Tri; Choi, Ji Hye; Lee, Chang Woo; Park, Yeon Soo; Lee, Sung Ki

2017-01-01

This study was aim to observe the effects of feeding mixed local hay (MH) consisted of 55% orchard grass ( Dactylis glomerata L.), 35% tall fescue ( Festuca arundinacea ) and 10% red clover ( Trifolium pratense ) to Hanwoo steers on performance, carcass characteristics and meat quality ( longissimus thoracis ) compared with feeding imported timothy hay (TH) and local rice straw (RS). Although no significant effects were found on animal performance and carcass yield grade, the carcasses of MH group had higher marbling score and quality grade than those of RS and TH group ( P  < 0.05). Therefore, higher fat content ( P  < 0.001), lower shear force and hardness value in the beef of MH group than that of other groups were observed. Furthermore, the beef of MH group had higher CIE a* value (redness) than that of other groups and feeding MH to Hanwoo steers lowered n-6 to n-3 fatty acids ratio in beef. Mixed hay provided benefits on meat quality and could be used for Hanwoo fattening program.

Effects of LiDAR point density and landscape context on the retrieval of urban forest biomass

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

PubMed

Gao, Yanbin; Liu, Shifei; Atia, Mohamed M; Noureldin, Aboelmagd

2015-09-15

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.

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

PubMed Central

Gao, Yanbin; Liu, Shifei; Atia, Mohamed M.; Noureldin, Aboelmagd

2015-01-01

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory. PMID:26389906

9 CFR 95.28 - Hay or straw and similar material from tick-infested areas.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., grass, or similar material from tick-infested pastures, ranges, or premises may disseminate the... hay or straw, grass, or similar materials shall not be imported unless such material is first...

9 CFR 95.28 - Hay or straw and similar material from tick-infested areas.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., grass, or similar material from tick-infested pastures, ranges, or premises may disseminate the... hay or straw, grass, or similar materials shall not be imported unless such material is first...

Towards a political ontology of state power: a comment on Colin Hay's article.

PubMed

Jessop, Bob

2014-09-01

This article offers some critical realist, strategic-relational comments on Colin Hay's proposal to treat the state as an 'as-if-real' concept. The critique first develops an alternative account of ontology, which is more suited to analyses of the state and state power; it then distinguishes the 'intransitive' properties of the real world as an object of investigation from the 'transitive' features of its scientific investigation and thereby provides a clearer understanding of what is at stake in 'as-if-realism'; and it ends with the suggestion that a concern with the modalities of state power rather than with the state per se offers a more fruitful approach to the genuine issues raised in Hay's article and in his earlier strategic-relational contributions to political analysis. © London School of Economics and Political Science 2014.

Chemical Composition, In vivo Digestibility and Metabolizable Energy Values of Caramba (Lolium multiflorum cv. caramba) Fresh, Silage and Hay.

PubMed

Özelçam, H; Kırkpınar, F; Tan, K

2015-10-01

The experiment was conducted to determine nutritive values of caramba (Lolium multiflorum cv. caramba) fresh, silage and hay by in vivo and in vitro methods. There was a statistically significant difference (p<0.01) in crude protein content value between fresh caramba (12.83%) and silage (8.91%) and hay (6.35%). According to results of experiment, the crude fiber, neutral detergent fiber, acid detergent fiber (ADF), acid detergent lignin contents of the three forms of caramba varied between 30.22% to 35.06%, 57.41% to 63.70%, 35.32% to 43.29%, and 5.55% to 8.86% respectively. There were no significant differences between the three forms of caramba in digestibility of nutrients and in vivo metabolizable energy (ME) values (p>0.05). However, the highest MECN (ME was estimated using crude nutrients) and MEADF values were found in fresh caramba (p<0.01). As a result, it could be said that, there were no differences between the three forms of caramba in nutrient composition, digestibility and ME value, besides drying and ensiling did not affect digestibility of hay. Consequently, caramba either as fresh, silage or hay is a good alternative source of forage for ruminants.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

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

PubMed

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

2014-12-01

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

Evaluation of Landslide Mapping Techniques and LiDAR-based Conditioning Factors

NASA Astrophysics Data System (ADS)

Mahalingam, R.; Olsen, M. J.

2014-12-01

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

Spatial and temporal assessment of cumulative disturbance impacts due to military training, burning, haying, and their interactions on land condition of Fort Riley.

PubMed

Wang, Guangxing; Murphy, Dana; Oller, Adam; Howard, Heidi R; Anderson, Alan B; Rijal, Santosh; Myers, Natalie R; Woodford, Philip

2014-07-01

The effects of military training activities on the land condition of Army installations vary spatially and temporally. Training activities observably degrade land condition while also increasing biodiversity and stabilizing ecosystems. Moreover, other anthropogenic activities regularly occur on military lands such as prescribed burns and agricultural haying-adding to the dynamics of land condition. Thus, spatially and temporally assessing the impacts of military training, prescribed burning, agricultural haying, and their interactions is critical to the management of military lands. In this study, the spatial distributions and patterns of military training-induced disturbance frequency were derived using plot observation and point observation-based method, at Fort Riley, Kansas from 1989 to 2001. Moreover, spatial and variance analysis of cumulative impacts due to military training, burning, haying, and their interactions on the land condition of Fort Riley were conducted. The results showed that: (1) low disturbance intensity dominated the majority of the study area with exception of concentrated training within centralized areas; (2) high and low values of disturbance frequency were spatially clustered and had spatial patterns that differed significantly from a random distribution; and (3) interactions between prescribed burning and agricultural haying were not significant in terms of either soil erosion or disturbance intensity although their means and variances differed significantly between the burned and non-burned areas and between the hayed and non-hayed areas.

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

PubMed Central

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

2015-01-01

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

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

PubMed

Varga, Timothy A; Asner, Gregory P

2008-04-01

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

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

Treesearch

Brian C. Dietterick; Russell White; Ryan Hilburn

2012-01-01

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

Organic vs. conventional grassland management: do (15)N and (13)C isotopic signatures of hay and soil samples differ?

PubMed

Klaus, Valentin H; Hölzel, Norbert; Prati, Daniel; Schmitt, Barbara; Schöning, Ingo; Schrumpf, Marion; Fischer, Markus; Kleinebecker, Till

2013-01-01

Distinguishing organic and conventional products is a major issue of food security and authenticity. Previous studies successfully used stable isotopes to separate organic and conventional products, but up to now, this approach was not tested for organic grassland hay and soil. Moreover, isotopic abundances could be a powerful tool to elucidate differences in ecosystem functioning and driving mechanisms of element cycling in organic and conventional management systems. Here, we studied the δ(15)N and δ(13)C isotopic composition of soil and hay samples of 21 organic and 34 conventional grasslands in two German regions. We also used Δδ(15)N (δ(15)N plant - δ(15)N soil) to characterize nitrogen dynamics. In order to detect temporal trends, isotopic abundances in organic grasslands were related to the time since certification. Furthermore, discriminant analysis was used to test whether the respective management type can be deduced from observed isotopic abundances. Isotopic analyses revealed no significant differences in δ(13)C in hay and δ(15)N in both soil and hay between management types, but showed that δ(13)C abundances were significantly lower in soil of organic compared to conventional grasslands. Δδ(15)N values implied that management types did not substantially differ in nitrogen cycling. Only δ(13)C in soil and hay showed significant negative relationships with the time since certification. Thus, our result suggest that organic grasslands suffered less from drought stress compared to conventional grasslands most likely due to a benefit of higher plant species richness, as previously shown by manipulative biodiversity experiments. Finally, it was possible to correctly classify about two third of the samples according to their management using isotopic abundances in soil and hay. However, as more than half of the organic samples were incorrectly classified, we infer that more research is needed to improve this approach before it can be efficiently

Organic vs. Conventional Grassland Management: Do 15N and 13C Isotopic Signatures of Hay and Soil Samples Differ?

PubMed Central

Klaus, Valentin H.; Hölzel, Norbert; Prati, Daniel; Schmitt, Barbara; Schöning, Ingo; Schrumpf, Marion; Fischer, Markus; Kleinebecker, Till

2013-01-01

Distinguishing organic and conventional products is a major issue of food security and authenticity. Previous studies successfully used stable isotopes to separate organic and conventional products, but up to now, this approach was not tested for organic grassland hay and soil. Moreover, isotopic abundances could be a powerful tool to elucidate differences in ecosystem functioning and driving mechanisms of element cycling in organic and conventional management systems. Here, we studied the δ15N and δ13C isotopic composition of soil and hay samples of 21 organic and 34 conventional grasslands in two German regions. We also used Δδ15N (δ15N plant - δ15N soil) to characterize nitrogen dynamics. In order to detect temporal trends, isotopic abundances in organic grasslands were related to the time since certification. Furthermore, discriminant analysis was used to test whether the respective management type can be deduced from observed isotopic abundances. Isotopic analyses revealed no significant differences in δ13C in hay and δ15N in both soil and hay between management types, but showed that δ13C abundances were significantly lower in soil of organic compared to conventional grasslands. Δδ15N values implied that management types did not substantially differ in nitrogen cycling. Only δ13C in soil and hay showed significant negative relationships with the time since certification. Thus, our result suggest that organic grasslands suffered less from drought stress compared to conventional grasslands most likely due to a benefit of higher plant species richness, as previously shown by manipulative biodiversity experiments. Finally, it was possible to correctly classify about two third of the samples according to their management using isotopic abundances in soil and hay. However, as more than half of the organic samples were incorrectly classified, we infer that more research is needed to improve this approach before it can be efficiently used in practice

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Quantification of LiDAR measurement uncertainty through propagation of errors due to sensor sub-systems and terrain morphology

NASA Astrophysics Data System (ADS)

Goulden, T.; Hopkinson, C.

2013-12-01

The quantification of LiDAR sensor measurement uncertainty is important for evaluating the quality of derived DEM products, compiling risk assessment of management decisions based from LiDAR information, and enhancing LiDAR mission planning capabilities. Current quality assurance estimates of LiDAR measurement uncertainty are limited to post-survey empirical assessments or vendor estimates from commercial literature. Empirical evidence can provide valuable information for the performance of the sensor in validated areas; however, it cannot characterize the spatial distribution of measurement uncertainty throughout the extensive coverage of typical LiDAR surveys. Vendor advertised error estimates are often restricted to strict and optimal survey conditions, resulting in idealized values. Numerical modeling of individual pulse uncertainty provides an alternative method for estimating LiDAR measurement uncertainty. LiDAR measurement uncertainty is theoretically assumed to fall into three distinct categories, 1) sensor sub-system errors, 2) terrain influences, and 3) vegetative influences. This research details the procedures for numerical modeling of measurement uncertainty from the sensor sub-system (GPS, IMU, laser scanner, laser ranger) and terrain influences. Results show that errors tend to increase as the laser scan angle, altitude or laser beam incidence angle increase. An experimental survey over a flat and paved runway site, performed with an Optech ALTM 3100 sensor, showed an increase in modeled vertical errors of 5 cm, at a nadir scan orientation, to 8 cm at scan edges; for an aircraft altitude of 1200 m and half scan angle of 15°. In a survey with the same sensor, at a highly sloped glacial basin site absent of vegetation, modeled vertical errors reached over 2 m. Validation of error models within the glacial environment, over three separate flight lines, respectively showed 100%, 85%, and 75% of elevation residuals fell below error predictions. Future

Mental health associations with eczema, asthma and hay fever in children: a cross-sectional survey

PubMed Central

Hammer-Helmich, Lene; Linneberg, Allan; Obel, Carsten; Thomsen, Simon Francis; Tang Møllehave, Line; Glümer, Charlotte

2016-01-01

Objective This study aimed to examine the association of eczema, asthma and hay fever with mental health in a general child population and to assess the influence of parental socioeconomic position on these associations. Methods We conducted a cross-sectional health survey of children aged 3, 6, 11 and 15 years in the City of Copenhagen, Denmark. Individual questionnaire data on eczema, asthma, and hay fever and mental health problems assessed using the Strengths and Difficulties Questionnaire (SDQ) was linked to register data on demographics and parental socioeconomic position. 9215 (47.9%) children were included in the analyses. Results Linear regression analyses showed that children with current eczema symptoms had higher SDQ scores (mean difference, 95% CI) of emotional problems (0.26, 0.12 to 0.39), conduct problems (0.19, 0.09 to 0.29) and hyperactivity problems (0.32, 0.16 to 0.48); children with current asthma symptoms had higher SDQ scores of emotional problems (0.45, 0.32 to 0.58), conduct problems (0.28, 0.18 to 0.38) and hyperactivity problems (0.52, 0.35 to 0.69); and children with current hay fever symptoms had higher SDQ scores of emotional problems (0.57, 0.42 to 0.72), conduct problems (0.22, 0.11 to 0.33), hyperactivity problems (0.44, 0.26 to 0.61) and peer problems (0.14, 0.01 to 0.26), compared with children without current symptoms of the relevant disease. For most associations, parental socioeconomic position did not modify the effect. Conclusions Children with eczema, asthma or hay fever had more emotional, conduct and hyperactivity problems, but not peer problems, compared with children without these diseases. Atopic diseases added equally to the burden of mental health problems independent of socioeconomic position. PMID:27742629

Supplementation of Farta sheep fed hay with graded levels of concentrate mix consisting of noug seed meal and rice bran.

PubMed

Asmare, Bimrew; Melaku, Solomon; Peters, Kurt J

2010-10-01

The study was carried out at Woreta, Ethiopia, to determine feed intake, digestibility, body weight (BW) change, and profitability of Farta sheep fed pasture hay alone or supplemented with graded levels of concentrate mix (CM) consisting of noug seed meal (NSM) and rice bran in 2:1 ratio. Twenty yearling intact male Farta sheep with BW of 16.9 +/- 1.68 kg (mean +/- SD) were used in randomized complete block design arranged into five blocks of four animals. The dietary treatments consisting of sole natural pasture hay (T1, control), hay +200 g of CM dry matter (DM) (T2, low), hay +300 g of CM DM (T3, medium), and hay +400 g of CM DM (T4, high) were randomly assigned to sheep within each block. Common salt and water were available to animals all the time. The supplements were offered twice daily in equal portions at 0800 and 1600 h. Supplementation with the CM increased (P < 0.001) DM, organic matter, crude protein, neutral detergent fiber, and acid detergent fiber intake and digestibility. The final BW and daily BW gains were higher (P < 0.001) for the supplemented compared to the control treatment. The study also revealed supplementation improved feed conversion efficiency and profitability. Among the supplemented treatments, the high level of supplementation resulted in better (P < 0.001) nutrient utilization, animal performance, and profitability. Thus, the high level of supplementation is recommended based on biological performance and profitability under conditions of this study.

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

Treesearch

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

2012-01-01

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

Validation of the high-throughput marker technology DArT using the model plant Arabidopsis thaliana.

PubMed

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.

Performance testing of LiDAR exploitation software

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

NASA Astrophysics Data System (ADS)

Griesbach, Christopher

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

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

NASA Astrophysics Data System (ADS)

Zhu, Junfeng; Pierskalla, William P.

2016-02-01

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

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

USGS Publications Warehouse

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

2010-01-01

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

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

PubMed Central

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

2013-01-01

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. PMID:24336112

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

PubMed

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

2013-12-11

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

A LiDAR data-based camera self-calibration method

NASA Astrophysics Data System (ADS)

Xu, Lijun; Feng, Jing; Li, Xiaolu; Chen, Jianjun

2018-07-01

To find the intrinsic parameters of a camera, a LiDAR data-based camera self-calibration method is presented here. Parameters have been estimated using particle swarm optimization (PSO), enhancing the optimal solution of a multivariate cost function. The main procedure of camera intrinsic parameter estimation has three parts, which include extraction and fine matching of interest points in the images, establishment of cost function, based on Kruppa equations and optimization of PSO using LiDAR data as the initialization input. To improve the precision of matching pairs, a new method of maximal information coefficient (MIC) and maximum asymmetry score (MAS) was used to remove false matching pairs based on the RANSAC algorithm. Highly precise matching pairs were used to calculate the fundamental matrix so that the new cost function (deduced from Kruppa equations in terms of the fundamental matrix) was more accurate. The cost function involving four intrinsic parameters was minimized by PSO for the optimal solution. To overcome the issue of optimization pushed to a local optimum, LiDAR data was used to determine the scope of initialization, based on the solution to the P4P problem for camera focal length. To verify the accuracy and robustness of the proposed method, simulations and experiments were implemented and compared with two typical methods. Simulation results indicated that the intrinsic parameters estimated by the proposed method had absolute errors less than 1.0 pixel and relative errors smaller than 0.01%. Based on ground truth obtained from a meter ruler, the distance inversion accuracy in the experiments was smaller than 1.0 cm. Experimental and simulated results demonstrated that the proposed method was highly accurate and robust.

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

DTIC Science & Technology

2014-03-01

investigator’s objective. For example, if the sole objective is to identify geomorphic breaks in slope associated with the OHWM, points representing vegetation... geomorphic position. During the data-gathering stage of wetland delinea- tions, measurements made using LiDAR data should be considered esti- mates...field. Field validation of LiDAR topographic data is essential before using them as evidence of a secondary hydrology indicator, such as geomorphic

Airborne LiDAR : a new source of traffic flow data.

DOT National Transportation Integrated Search

2005-10-01

LiDAR (or airborne laser scanning) systems became a dominant player in high-precision spatial data acquisition : to efficiently create DEM/DSM in the late 90's. With increasing point density, new systems are now able to : support object extraction, s...

Airborne LiDAR : a new source of traffic flow data.

DOT National Transportation Integrated Search

2005-10-01

LiDAR (or airborne laser scanning) systems became a dominant player in high-precision spatial data acquisition : to efficiently create DEM/DSM in the late 90s. With increasing point density, new systems are now able to : support object extraction, ...

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

The HayWired earthquake scenario—Engineering implications

USGS Publications Warehouse

Detweiler, Shane T.; Wein, Anne M.

2018-04-18

The HayWired Earthquake Scenario—Engineering Implications is the second volume of U.S. Geological Survey (USGS) Scientific Investigations Report 2017–5013, which describes the HayWired scenario, developed by USGS and its partners. The scenario is a hypothetical yet scientifically realistic earthquake sequence that is being used to better understand hazards for the San Francisco Bay region during and after a magnitude-7 earthquake (mainshock) on the Hayward Fault and its aftershocks.Analyses in this volume suggest that (1) 800 deaths and 16,000 nonfatal injuries result from shaking alone, plus property and direct business interruption losses of more than $82 billion from shaking, liquefaction, and landslides; (2) the building code is designed to protect lives, but even if all buildings in the region complied with current building codes, 0.4 percent could collapse, 5 percent could be unsafe to occupy, and 19 percent could have restricted use; (3) people expect, prefer, and would be willing to pay for greater resilience of buildings; (4) more than 22,000 people could require extrication from stalled elevators, and more than 2,400 people could require rescue from collapsed buildings; (5) the average east-bay resident could lose water service for 6 weeks, some for as long as 6 months; (6) older steel-frame high-rise office buildings and new reinforced-concrete residential buildings in downtown San Francisco and Oakland could be unusable for as long as 10 months; (7) about 450 large fires could result in a loss of residential and commercial building floor area equivalent to more than 52,000 single-family homes and cause property (building and content) losses approaching $30 billion; and (8) combining earthquake early warning (ShakeAlert) with “drop, cover, and hold on” actions could prevent as many as 1,500 nonfatal injuries out of 18,000 total estimated nonfatal injuries from shaking and liquefaction hazards.

Characterization and comparison of the temporal dynamics of ruminal bacterial microbiota colonizing rice straw and alfalfa hay within ruminants.

PubMed

Liu, Junhua; Zhang, Mengling; Xue, Chunxu; Zhu, Weiyun; Mao, Shengyong

2016-12-01

Three ruminally cannulated Holstein cows were used to characterize the dynamics of bacterial colonization of rice straw and alfalfa hay and to assess the differences in the composition and inferred gene function of the colonized microbiota between these 2 forages. Nonincubated (0h) rice straw and alfalfa hay samples and residues in nylon bags incubated for 0.5, 2, 6, 16, and 48h were analyzed for dry matter and were used for DNA extraction and MiSeq (Illumina Inc., San Diego, CA) sequencing of the 16S rRNA gene. The microbial communities that colonized the air-dried and nonincubated (0h) rice straw and alfalfa hay were both dominated by members of the Proteobacteria (contributing toward 70.47% of the 16S RNA reads generated). In situ incubation of the 2 forages revealed major shifts in the community composition: Proteobacteria were replaced within 30min by members belonging to the Bacteroidetes and Firmicutes, contributing toward 51.9 and 36.6% of the 16S rRNA reads generated, respectively. A second significant shift was observed after 6h of rumen incubation, when members of the Spirochaetes and Fibrobacteria phyla became abundant in the forage-adherent community. During the first 30min of rumen incubation, ~20.7 and 36.1% of the rice straw and alfalfa hay, respectively, were degraded, whereas little biomass degradation occurred between 30min and 2h after the rice straw or alfalfa hay was placed in the rumen. Significant differences were noted in attached bacterial community structure between the 2 forage groups, and the abundances of dominant genera Anaeroplasma, Butyrivibrio, Fibrobacter, and Prevotella were affected by the forage types. Real-time PCR results showed that the 16S rRNA copies of total bacteria attached to these 2 forages were affected by the forage types and incubation time, and higher numbers of attached bacterial 16S rRNA were observed in the alfalfa hay samples than in the rice straw from 0.5 to 16h of incubation. The metagenomes predicted by

Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology.

PubMed

Ferreira, Manuel A; Vonk, Judith M; Baurecht, Hansjörg; Marenholz, Ingo; Tian, Chao; Hoffman, Joshua D; Helmer, Quinta; Tillander, Annika; Ullemar, Vilhelmina; van Dongen, Jenny; Lu, Yi; Rüschendorf, Franz; Esparza-Gordillo, Jorge; Medway, Chris W; Mountjoy, Edward; Burrows, Kimberley; Hummel, Oliver; Grosche, Sarah; Brumpton, Ben M; Witte, John S; Hottenga, Jouke-Jan; Willemsen, Gonneke; Zheng, Jie; Rodríguez, Elke; Hotze, Melanie; Franke, Andre; Revez, Joana A; Beesley, Jonathan; Matheson, Melanie C; Dharmage, Shyamali C; Bain, Lisa M; Fritsche, Lars G; Gabrielsen, Maiken E; Balliu, Brunilda; Nielsen, Jonas B; Zhou, Wei; Hveem, Kristian; Langhammer, Arnulf; Holmen, Oddgeir L; Løset, Mari; Abecasis, Gonçalo R; Willer, Cristen J; Arnold, Andreas; Homuth, Georg; Schmidt, Carsten O; Thompson, Philip J; Martin, Nicholas G; Duffy, David L; Novak, Natalija; Schulz, Holger; Karrasch, Stefan; Gieger, Christian; Strauch, Konstantin; Melles, Ronald B; Hinds, David A; Hübner, Norbert; Weidinger, Stephan; Magnusson, Patrik K E; Jansen, Rick; Jorgenson, Eric; Lee, Young-Ae; Boomsma, Dorret I; Almqvist, Catarina; Karlsson, Robert; Koppelman, Gerard H; Paternoster, Lavinia

2017-12-01

Asthma, hay fever (or allergic rhinitis) and eczema (or atopic dermatitis) often coexist in the same individuals, partly because of a shared genetic origin. To identify shared risk variants, we performed a genome-wide association study (GWAS; n = 360,838) of a broad allergic disease phenotype that considers the presence of any one of these three diseases. We identified 136 independent risk variants (P < 3 × 10 -8 ), including 73 not previously reported, which implicate 132 nearby genes in allergic disease pathophysiology. Disease-specific effects were detected for only six variants, confirming that most represent shared risk factors. Tissue-specific heritability and biological process enrichment analyses suggest that shared risk variants influence lymphocyte-mediated immunity. Six target genes provide an opportunity for drug repositioning, while for 36 genes CpG methylation was found to influence transcription independently of genetic effects. Asthma, hay fever and eczema partly coexist because they share many genetic risk variants that dysregulate the expression of immune-related genes.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.

PubMed

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.

Ron Hays: A Story of Art as Self Treatment for Alzheimer's Disease

ERIC Educational Resources Information Center

Jones, Robin M. N.; Hays, Nancy Scheller

2016-01-01

Ronald E. Hays is the former Director of the Hahnemann Creative Arts in Therapy Department at Drexel University in Philadelphia, Pennsylvania, and the cofounder of the graduate art therapy program at Eastern Virginia Medical School in Norfolk, Virginia. At the age of 62 he was diagnosed with early onset Alzheimer's disease, a form of dementia. In…

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

USGS Publications Warehouse

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models

PubMed Central

2018-01-01

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the ‘Internet of Things’ (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds. PMID:29748521

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.

PubMed

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

2018-05-10

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

Automated object detection and tracking with a flash LiDAR system

NASA Astrophysics Data System (ADS)

Hammer, Marcus; Hebel, Marcus; Arens, Michael

2016-10-01

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

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

PubMed

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

In the last years, airborne Light Detection and Ranging (LiDAR) data proved to be a valuable information resource for a vast number of applications ranging from land cover mapping to individual surface feature extraction from complex urban environments. To extract information from LiDAR data, users apply prior knowledge. Unfortunately, there is no consistent initiative for structuring this knowledge into data models that can be shared and reused across different applications and domains. The absence of such models poses great challenges to data interpretation, data fusion and integration as well as information transferability. The intention of this work is to describe the design, development and deployment of an ontology-based system to classify buildings from airborne LiDAR data. The novelty of this approach consists of the development of a domain ontology that specifies explicitly the knowledge used to extract features from airborne LiDAR data. The overall goal of this approach is to investigate the possibility for classification of features of interest from LiDAR data by means of domain ontology. The proposed workflow is applied to the building extraction process for the region of "Biberach an der Riss" in South Germany. Strip-adjusted and georeferenced airborne LiDAR data is processed based on geometrical and radiometric signatures stored within the point cloud. Region-growing segmentation algorithms are applied and segmented regions are exported to the GeoJSON format. Subsequently, the data is imported into the ontology-based reasoning process used to automatically classify exported features of interest. Based on the ontology it becomes possible to define domain concepts, associated properties and relations. As a consequence, the resulting specific body of knowledge restricts possible interpretation variants. Moreover, ontologies are machinable and thus it is possible to run reasoning on top of them. Available reasoners (FACT++, JESS, Pellet) are used to check

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Asthma, hay fever, and food allergy are associated with caregiver-reported speech disorders in US children

PubMed Central

Strom, Mark A.; Silverberg, Jonathan I.

2016-01-01

Background Children with asthma, hay fever, and food allergy may have several factors that increase their risk of speech disorder, including allergic inflammation, ADD/ADHD, and sleep disturbance. However, few studies have examined a relationship between asthma, allergic disease, and speech disorder. We sought to determine whether asthma, hay fever, and food allergy are associated with speech disorder in children and whether disease severity, sleep disturbance, or ADD/ADHD modified such associations. Methods We analyzed cross-sectional data on 337,285 children aged 2–17 years from 19 US population-based studies, including the 1997–2013 National Health Interview Survey and the 2003/4 and 2007/8 National Survey of Children’s Health. Results In multivariate models, controlling for age, demographic factors, healthcare utilization, and history of eczema, lifetime history of asthma (odds ratio [95% confidence interval]: 1.18 [1.04–1.34], p = 0.01), and one-year history of hay fever (1.44 [1.28–1.62], p < 0.0001) and food allergy (1.35 [1.13–1.62], p = 0.001) were associated with increased odds of speech disorder. Children with current (1.37 [1.15–1.59] p = 0.0003) but not past (p = 0.06) asthma had increased risk of speech disorder. In one study that assessed caregiver-reported asthma severity, mild (1.58 [1.20–2.08], p = 0.001) and moderate (2.99 [1.54–3.41], p < 0.0001) asthma were associated with increased odds of speech disorder; however, severe asthma was associated with the highest odds of speech disorder (5.70 [2.36–13.78], p = 0.0001). Conclusion Childhood asthma, hay fever, and food allergy are associated with increased risk of speech disorder. Future prospective studies are needed to characterize the associations. PMID:27091599

Asthma, hay fever, and food allergy are associated with caregiver-reported speech disorders in US children.

PubMed

Strom, Mark A; Silverberg, Jonathan I

2016-09-01

Children with asthma, hay fever, and food allergy may have several factors that increase their risk of speech disorder, including allergic inflammation, ADD/ADHD, and sleep disturbance. However, few studies have examined a relationship between asthma, allergic disease, and speech disorder. We sought to determine whether asthma, hay fever, and food allergy are associated with speech disorder in children and whether disease severity, sleep disturbance, or ADD/ADHD modified such associations. We analyzed cross-sectional data on 337,285 children aged 2-17 years from 19 US population-based studies, including the 1997-2013 National Health Interview Survey and the 2003/4 and 2007/8 National Survey of Children's Health. In multivariate models, controlling for age, demographic factors, healthcare utilization, and history of eczema, lifetime history of asthma (odds ratio [95% confidence interval]: 1.18 [1.04-1.34], p = 0.01), and one-year history of hay fever (1.44 [1.28-1.62], p < 0.0001) and food allergy (1.35 [1.13-1.62], p = 0.001) were associated with increased odds of speech disorder. Children with current (1.37 [1.15-1.59] p = 0.0003) but not past (p = 0.06) asthma had increased risk of speech disorder. In one study that assessed caregiver-reported asthma severity, mild (1.58 [1.20-2.08], p = 0.001) and moderate (2.99 [1.54-3.41], p < 0.0001) asthma were associated with increased odds of speech disorder; however, severe asthma was associated with the highest odds of speech disorder (5.70 [2.36-13.78], p = 0.0001). Childhood asthma, hay fever, and food allergy are associated with increased risk of speech disorder. Future prospective studies are needed to characterize the associations. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Effect of Feeding Selenium-Fertilized Alfalfa Hay on Performance of Weaned Beef Calves

PubMed Central

Hall, Jean A.; Bobe, Gerd; Hunter, Janice K.; Vorachek, William R.; Stewart, Whitney C.; Vanegas, Jorge A.; Estill, Charles T.; Mosher, Wayne D.; Pirelli, Gene J.

2013-01-01

Selenium (Se) is an essential micronutrient in cattle, and Se-deficiency can affect morbidity and mortality. Calves may have greater Se requirements during periods of stress, such as during the transitional period between weaning and movement to a feedlot. Previously, we showed that feeding Se-fertilized forage increases whole-blood (WB) Se concentrations in mature beef cows. Our current objective was to test whether feeding Se-fertilized forage increases WB-Se concentrations and performance in weaned beef calves. Recently weaned beef calves (n = 60) were blocked by body weight, randomly assigned to 4 groups, and fed an alfalfa hay based diet for 7 wk, which was harvested from fields fertilized with sodium-selenate at a rate of 0, 22.5, 45.0, or 89.9 g Se/ha. Blood samples were collected weekly and analyzed for WB-Se concentrations. Body weight and health status of calves were monitored during the 7-wk feeding trial. Increasing application rates of Se fertilizer resulted in increased alfalfa hay Se content for that cutting of alfalfa (0.07, 0.95, 1.55, 3.26 mg Se/kg dry matter for Se application rates of 0, 22.5, 45.0, or 89.9 g Se/ha, respectively). Feeding Se-fertilized alfalfa hay during the 7-wk preconditioning period increased WB-Se concentrations (P Linear<0.001) and body weights (P Linear = 0.002) depending upon the Se-application rate. Based upon our results we suggest that soil-Se fertilization is a potential management tool to improve Se-status and performance in weaned calves in areas with low soil-Se concentrations. PMID:23536788

Comparison of hay and haylage from permanent Alpine meadows in winter dairy cow diets.

PubMed

Borreani, G; Giaccone, D; Mimosi, A; Tabacco, E

2007-12-01

In an Alpine environment, diets based on local forage resources are needed to maintain the link with the territory and confer special characteristics to typical cheeses. Harvesting at a late stage of maturity, high mechanical losses, and frequent rainfall often make the hay that is harvested of a poor quality. The aim of this study was to evaluate the effects of 2 different conservation methods (late hay, LH, vs. early haylage, ES) of natural permanent meadows on milk production in dairy cows, on the chemical and microbiological characteristics of the milk, and on the quality of the cheese over the winter period. Haylage and hay were harvested from the same permanent meadow at the Vittorino Vezzani experimental farm in Sauze d'Oulx (45 degrees 02'N, 6 degrees 53'E, Italy). The ES forage was cut 4 wk earlier than traditional hay, wilted for 30 h, baled at a dry matter (DM) content of about 50%, wrapped with 6 layers of stretch film, and stored in a protected area. The LH forage was harvested later, when the weather conditions were favorable and, after a 3-d wilting, it was baled and stored indoors. After an 8-mo storage period, the ES had a greater crude protein concentration, organic matter digestibility, and net energy for lactation than LH and a lower neutral detergent fiber and acid detergent fiber. Forty multiparous lactating Aosta Red Pied cows were used in a 19-d period crossover design to assess the nutritional value of the stored forages. The diets included ES fed ad libitum and 3.5 kg of DM per cow of concentrate or LH fed ad libitum and 5.1 kg of DM per cow of concentrate. The dietary DM was 90.1% for the LH and 59.9% for the ES. The diets contained 12.6 and 13.0% crude protein and 48.6 and 48.0% neutral detergent fiber, for the LH and ES, respectively. The forage intake was greater in the ES treatment than in the LH treatment. The ES treatment produced more milk (1.7 kg/d) and more 3.5% fat-corrected milk (1.5 kg/d) than the cows on the LH treatment. The

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

PubMed Central

Bartholomeus, Harm M.; Kooistra, Lammert

2017-01-01

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 Models (DTMs), Digital Surface Models (DSMs) and finally Canopy Height Models (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 cm 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 cm. 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). PMID:29039755

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

PubMed

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).

Mental health associations with eczema, asthma and hay fever in children: a cross-sectional survey.

PubMed

Hammer-Helmich, Lene; Linneberg, Allan; Obel, Carsten; Thomsen, Simon Francis; Tang Møllehave, Line; Glümer, Charlotte

2016-10-14

This study aimed to examine the association of eczema, asthma and hay fever with mental health in a general child population and to assess the influence of parental socioeconomic position on these associations. We conducted a cross-sectional health survey of children aged 3, 6, 11 and 15 years in the City of Copenhagen, Denmark. Individual questionnaire data on eczema, asthma, and hay fever and mental health problems assessed using the Strengths and Difficulties Questionnaire (SDQ) was linked to register data on demographics and parental socioeconomic position. 9215 (47.9%) children were included in the analyses. Linear regression analyses showed that children with current eczema symptoms had higher SDQ scores (mean difference, 95% CI) of emotional problems (0.26, 0.12 to 0.39), conduct problems (0.19, 0.09 to 0.29) and hyperactivity problems (0.32, 0.16 to 0.48); children with current asthma symptoms had higher SDQ scores of emotional problems (0.45, 0.32 to 0.58), conduct problems (0.28, 0.18 to 0.38) and hyperactivity problems (0.52, 0.35 to 0.69); and children with current hay fever symptoms had higher SDQ scores of emotional problems (0.57, 0.42 to 0.72), conduct problems (0.22, 0.11 to 0.33), hyperactivity problems (0.44, 0.26 to 0.61) and peer problems (0.14, 0.01 to 0.26), compared with children without current symptoms of the relevant disease. For most associations, parental socioeconomic position did not modify the effect. Children with eczema, asthma or hay fever had more emotional, conduct and hyperactivity problems, but not peer problems, compared with children without these diseases. Atopic diseases added equally to the burden of mental health problems independent of socioeconomic position. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

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

PubMed

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

2011-05-01

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

Investigating the causal effect of smoking on hay fever and asthma: a Mendelian randomization meta-analysis in the CARTA consortium.

PubMed

Skaaby, Tea; Taylor, Amy E; Jacobsen, Rikke K; Paternoster, Lavinia; Thuesen, Betina H; Ahluwalia, Tarunveer S; Larsen, Sofus C; Zhou, Ang; Wong, Andrew; Gabrielsen, Maiken E; Bjørngaard, Johan H; Flexeder, Claudia; Männistö, Satu; Hardy, Rebecca; Kuh, Diana; Barry, Sarah J; Tang Møllehave, Line; Cerqueira, Charlotte; Friedrich, Nele; Bonten, Tobias N; Noordam, Raymond; Mook-Kanamori, Dennis O; Taube, Christian; Jessen, Leon E; McConnachie, Alex; Sattar, Naveed; Upton, Mark N; McSharry, Charles; Bønnelykke, Klaus; Bisgaard, Hans; Schulz, Holger; Strauch, Konstantin; Meitinger, Thomas; Peters, Annette; Grallert, Harald; Nohr, Ellen A; Kivimaki, Mika; Kumari, Meena; Völker, Uwe; Nauck, Matthias; Völzke, Henry; Power, Chris; Hyppönen, Elina; Hansen, Torben; Jørgensen, Torben; Pedersen, Oluf; Salomaa, Veikko; Grarup, Niels; Langhammer, Arnulf; Romundstad, Pål R; Skorpen, Frank; Kaprio, Jaakko; R Munafò, Marcus; Linneberg, Allan

2017-05-22

Observational studies on smoking and risk of hay fever and asthma have shown inconsistent results. However, observational studies may be biased by confounding and reverse causation. Mendelian randomization uses genetic variants as markers of exposures to examine causal effects. We examined the causal effect of smoking on hay fever and asthma by using the smoking-associated single nucleotide polymorphism (SNP) rs16969968/rs1051730. We included 231,020 participants from 22 population-based studies. Observational analyses showed that current vs never smokers had lower risk of hay fever (odds ratio (OR) = 0·68, 95% confidence interval (CI): 0·61, 0·76; P < 0·001) and allergic sensitization (OR = 0·74, 95% CI: 0·64, 0·86; P < 0·001), but similar asthma risk (OR = 1·00, 95% CI: 0·91, 1·09; P = 0·967). Mendelian randomization analyses in current smokers showed a slightly lower risk of hay fever (OR = 0·958, 95% CI: 0·920, 0·998; P = 0·041), a lower risk of allergic sensitization (OR = 0·92, 95% CI: 0·84, 1·02; P = 0·117), but higher risk of asthma (OR = 1·06, 95% CI: 1·01, 1·11; P = 0·020) per smoking-increasing allele. Our results suggest that smoking may be causally related to a higher risk of asthma and a slightly lower risk of hay fever. However, the adverse events associated with smoking limit its clinical significance.

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

USGS Publications Warehouse

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

2011-01-01

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

China: Tradition and Transformation Curriculum Projects. 1994 Fulbright-Hays Summer Seminars Abroad Program.

ERIC Educational Resources Information Center

National Committee on United States-China Relations, New York, NY.

These lessons were developed by teacher participants in the 1994 Fulbright-Hays Summer Seminars Abroad program in China. The 15 lessons include: (1) "Global Studies 1" (Robert H. Berry); (2) "Dao Beijing" (Thomas G. Buckingham, Jr.); (3) "Letters to the Past: An Integrated Curriculum on China, Hong Kong, and Macau"…

The HayWired Scenario - How Can the San Francisco Bay Region Bounce Back Better?

NASA Astrophysics Data System (ADS)

Hudnut, K. W.; Wein, A. M.; Cox, D. A.; Perry, S. C.; Porter, K.; Johnson, L. A.; Strauss, J. A.

2017-12-01

The HayWired scenario is a hypothetical yet scientifically realistic and quantitative depiction of a moment magnitude (Mw) 7.0 earthquake occurring on April 18, 2018, at 4:18 p.m. on the Hayward Fault in the east bay part of the San Francisco Bay area, California. The hypothetical earthquake has its epicenter in Oakland, and strong ground shaking from the scenario causes a wide range of severe impacts throughout the greater bay region. In the scenario, the Hayward Fault is ruptured along its length for 83 kilometers (about 52 miles). Building on a decades-long series of efforts to reduce earthquake risk in the SF Bay area, the hypothetical HayWired earthquake is used to examine the well-known earthquake hazard of the Hayward Fault, with a focus on newly emerging vulnerabilities. After a major earthquake disaster, reestablishing water services and food-supply chains are, of course, top priorities. However, problems associated with telecommunication outages or "network congestion" will increase and become more urgent as the bay region deepens its reliance on the "Internet of Things." Communications at all levels are crucial during incident response following an earthquake. Damage to critical facilities (such as power plants) from earthquake shaking and to electrical and telecommunications wires and fiber-optic cables that are severed where they cross a fault rupture can trigger cascading Internet and telecommunications outages, and restoring these services is crucially important for emergency-response coordination. Without good communications, emergency-response efficiency is reduced, and as a result, life-saving response functions can be compromised. For these reasons, the name HayWired was chosen for this scenario to emphasize the need to examine our interconnectedness and reliance on telecommunications and other lifelines (such as water and electricity). Earthquake risk in the SF Bay area has been greatly reduced as a result of previous concerted efforts; for

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

Treesearch

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

2013-01-01

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

Using Landsat Time-Series and LiDAR to Inform Aboveground Forest Biomass Baselines in Northern Minnesota, USA

Treesearch

Ram K. Deo; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall; Michael J. Falkowski; Warren B. Cohen

2017-01-01

The publicly accessible archive of Landsat imagery and increasing regional-scale LiDAR acquisitions offer an opportunity to periodically estimate aboveground forest biomass (AGB) from 1990 to the present to alignwith the reporting needs ofNationalGreenhouseGas Inventories (NGHGIs). This study integrated Landsat time-series data, a state-wide LiDAR dataset, and a recent...

High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR

PubMed Central

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

2018-01-01

Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR (r2 of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association (r2 = 0.92 and slope = 1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass (r2 = 0.93 and r2 = 0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new opportunities to

Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR.

PubMed

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

High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR.

PubMed

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

2018-01-01

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

Interaction of bale size and preservative rate for large-round bales of alfalfa hay

USDA-ARS?s Scientific Manuscript database

Recently, two studies conducted at the US Dairy Forage Research Center have reported inconsistent storage responses following the application of propionic-acid-based preservatives to alfalfa or alfalfa-orchardgrass hays. One of these studies utilized 5-foot-diameter round bales, and produced disappo...

Evaluation of physical structure value in spring-harvested grass/clover silage and hay fed to heifers.

PubMed

Schulze, A K S; Nørgaard, P; Byskov, M V; Weisbjerg, M R

2015-02-01

The physical structure value of conserved grass/clover forages of spring harvest was evaluated by assessing effects of harvest time, conservation method, iNDF/NDF ratio and NDF intake (NDFI) per kg BW on chewing activity and fecal particle size in dairy heifers. A mixed sward consisting of ryegrass (Lolium perenne), red clover (Trifolium pratense) and white clover (Trifolium repens) was harvested in 2009 on May 9 (early) and 25 (late), and both cuts were conserved as silage and hay. The early silage, early hay, late silage and late hay contained dry matter (DM) of 454, 842, 250 and 828 g/kg, and NDF of 315, 436, 414 and 503 g/kg DM, respectively. Forages were fed as sole feed to four Jersey heifers of 435±30 kg BW in a 4×4 Latin square experiment. Feeding level was 90% of individual ad libitum intake, divided equally across two daily meals offered at 0800 and 1530 h. Chewing activity was estimated from recorded jaw movements (JM) oscillations continuously logged for 96 h and summarized per 24 h as mean effective rumination time and eating time. Eating behavior was further observed during four 20-min test meals. Weight proportion of large feces particles (>1.0 mm) and geometric mean fecal particle size (GPS) were calculated. Potentially indigestible NDF (iNDF) was estimated by incubation for 288 h in situ. The daily DM intake (DMI) decreased with progressing maturity at harvest (P<0.001) while daily NDFI was unaffected by harvest time (P>0.05). Earlier harvest led to less rumination per kg NDFI (P<0.01), similar eating time per kg NDFI (P>0.05) and similar proportion of large particles (P>0.01) compared with later harvest. Rumination time per kg NDFI decreased with higher NDFI per kg BW (P<0.001) and with lower iNDF/NDF ratio (P<0.01). Content and potential digestibility of NDF was greater in hay than in silage from the same harvest probably due to field loss and therefore confounded effects of conservation method. This study of high digestibility grass

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

The effect of a hay grid feeder on feed consumption and measurement of the gastric pH using an intragastric electrode device in horses: a preliminary report.

PubMed

Aristizabal, F; Nieto, J; Yamout, S; Snyder, J

2014-07-01

Obesity and gastric ulceration are highly prevalent in horses. Management modifications for preventing squamous gastric ulceration include frequent feeding and free access to pasture; however, these practices may predispose horses to obesity. To compare the percentage of hay consumed, intragastric pH and horse activity between feeding from the ground and a hay grid feeder. Crossover experimental study. A pH electrode was inserted into the stomach to record the intragastric pH for 48 h. Horses received 1% of their body weight in grass hay twice a day. Horses were assigned to be fed from the ground or a commercial hay grid feeder for 24 h and then switched to the opposite protocol for an additional 24 h. Horses were continuously video-recorded and the percentage of time spent eating or drinking, walking or standing, and lying down were calculated. Two point data were compared by paired t test and pH over time was compared by repeated measures ANOVA. Horses consumed significantly greater amounts of grass hay when fed on the ground compared with a hay grid feeder (n = 9; P<0.001). There were no significant differences between the groups for mean intragastric pH values (n = 6; P = 0.97), mean intragastric pH over time (n = 6; P = 0.45) the length of time the pH was below 4.0 (n = 6; P = 0.54), and the percentage of time horses spent eating or drinking (n = 9; P = 0.52), walking or standing (n = 9; P = 0.3), or lying down (n = 9; P = 0.4). Within each group horses spent more time eating during the day compared with the night (n = 9; hay grid feeder P = 0.003; ground feeding P = 0.007). The hay grid feeder studied may be used to reduce the amount of hay ingested by horses without reducing the time horses spend eating. © 2013 EVJ Ltd.

Prioritizing treatment of second-growth forests using LiDAR

Treesearch

Lathrop P. Leonard; Daryl Van Dyke

2012-01-01

We used multi-return light detecting and ranging (LiDAR) to develop a costeffective method for describing forest conditions and prioritizing stands for treatment in over 14,000 ha of second-growth forests (11 to 85 years old) in Del Norte Coast Redwoods State Park (DNCRSP). DNCRSP consists primarily of redwood and Douglas-fir dominated forests with scattered tanoak...

Quantifying Ladder Fuels: A New Approach Using LiDAR

Treesearch

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...

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

NASA Astrophysics Data System (ADS)

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.

Clay Shrines by 75 Fifth Graders. Fulbright-Hays Summer Seminars Abroad, 1999 (Mexico).

ERIC Educational Resources Information Center

Conn, Marsha

This curriculum unit, incorporating an art specialist's experience and knowledge gained in Mexico as a participant in the Fulbright-Hays Summer Seminars Abroad Program, focuses on the creation of a ceramic shrine by 75 fifth graders. The ceramic shrine described in the unit uses clay, paint, varnish, collage materials, and tin for…

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Effects of a propionic acid-based preservative on storage characteristics, nutritive value, and energy content for alfalfa hays packaged in large, round bales

USDA-ARS?s Scientific Manuscript database

During 2009 and 2010, alfalfa (Medicago sativa L.) hays from two cuttings that were harvested from the same field site were used to evaluate the effects of a propionic acid-based preservative on the storage characteristics and nutritive value of hays stored as large, round bales. A total of 87 large...

Post-construction monitoring of a Core-Loc™ breakwater using tripod-based LiDAR

USGS Publications Warehouse

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

NASA Astrophysics Data System (ADS)

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).

Quantitative analysis of woodpecker habitat using high-resolution airborne LiDAR estimates of forest structure and composition

Treesearch

James E. Garabedian; Robert J. McGaughey; Stephen E. Reutebuch; Bernard R. Parresol; John C. Kilgo; Christopher E. Moorman; M. Nils. Peterson

2014-01-01

Light detection and ranging (LiDAR) technology has the potential to radically alter the way researchers and managers collect data on wildlife–habitat relationships. To date, the technology has fostered several novel approaches to characterizing avian habitat, but has been limited by the lack of detailed LiDAR-habitat attributes relevant to species across a continuum of...

Shift work and sleep disorder among textile mill workers in Bahir Dar, northwest Ethiopia.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

Rao, M.; Vuong, H.

2013-12-01

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

Fulbright-Hays Summer Seminars Abroad Program 1989. Egypt: Transition to the Modern World.

ERIC Educational Resources Information Center

Office of International Education (ED), Washington, DC.

This document consists of four papers on various aspects of development in Egypt prepared by participants in the Fulbright-Hays Seminars Abroad Program in Egypt in 1989. Four of the papers are descriptive, one is a lesson plan. The papers included are: (1) "Egypt: Transition to Modern Times" (Katherine Jensen) focuses on the role of…

Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology

PubMed Central

Esparza-Gordillo, Jorge; Medway, Chris W; Mountjoy, Edward; Burrows, Kimberley; Hummel, Oliver; Grosche, Sarah; Brumpton, Ben M; Witte, John S; Hottenga, Jouke-Jan; Willemsen, Gonneke; Zheng, Jie; Rodríguez, Elke; Hotze, Melanie; Franke, Andre; Revez, Joana A; Beesley, Jonathan; Matheson, Melanie C; Dharmage, Shyamali C; Bain, Lisa M; Fritsche, Lars G; Gabrielsen, Maiken E; Balliu, Brunilda; Nielsen, Jonas B; Zhou, Wei; Hveem, Kristian; Langhammer, Arnulf; Holmen, Oddgeir L; Løset, Mari; Abecasis, Gonçalo R; Willer, Cristen J; Arnold, Andreas; Homuth, Georg; Schmidt, Carsten O; Thompson, Philip J; Martin, Nicholas G; Duffy, David L; Novak, Natalija; Schulz, Holger; Karrasch, Stefan; Gieger, Christian; Strauch, Konstantin; Melles, Ronald B; Hinds, David A; Hübner, Norbert; Weidinger, Stephan; Magnusson, Patrik KE; Jansen, Rick; Jorgenson, Eric; Lee, Young-Ae; Boomsma, Dorret I; Almqvist, Catarina; Karlsson, Robert; Koppelman, Gerard H; Paternoster, Lavinia

2017-01-01

Asthma, hay fever (or allergic rhinitis) and eczema (or atopic dermatitis) often coexist in the same individuals1, partly because of a shared genetic origin2–4. To identify shared risk variants, we performed a genome-wide association study (GWAS, n=360,838) of a broad allergic disease phenotype that considers the presence of any one of these three diseases. We identified 136 independent risk variants (P<3x10-8), including 73 not previously reported, which implicate 132 nearby genes in allergic disease pathophysiology. Disease-specific effects were detected for only six variants, confirming that most represent shared risk factors. Tissue-specific heritability and biological process enrichment analyses suggest that shared risk variants influence lymphocyte-mediated immunity. Six target genes provide an opportunity for drug repositioning, while for 36 genes CpG methylation was found to influence transcription independently of genetic effects. Asthma, hay fever and eczema partly coexist because they share many genetic risk variants that dysregulate the expression of immune-related genes. PMID:29083406

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

USGS Publications Warehouse

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

Bahr, Thomas

2014-05-01

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

QTL mapping for fruit quality in Citrus using DArTseq markers.

PubMed

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

2017-04-12

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

Mixing and photoreactivity of dissolved organic matter in the Nelson/Hayes estuarine system (Hudson Bay, Canada)

NASA Astrophysics Data System (ADS)

Guéguen, C.; Mokhtar, M.; Perroud, A.; McCullough, G.; Papakyriakou, T.

2016-09-01

This work presents the results of a 4-year study (2009-2012) investigating the mixing and photoreactivity of dissolved organic matter (DOM) in the Nelson/Hayes estuary (Hudson Bay). Dissolved organic carbon (DOC), colored DOM, and humic-like DOM decreased with increasing salinity (r2 = 0.70-0.84). Removal of DOM was noticeable at low to mid salinity range, likely due to degradation and/or adsorption to particles. DOM photobleaching rates (i.e., decrease in DOM signal resulting from exposure to solar radiation) ranged from 0.005 to 0.030 h- 1, corresponding to half-lives of 4.9-9.9 days. Dissolved organic matter from the Nelson and Hayes Rivers was more photoreactive than from the estuary where the photodegradation of terrestrial DOM decreased with increasing salinity. Coincident with the loss of CDOM absorption was an increase in spectral slope S, suggesting a decrease in DOM molecular weight. Marked differences in photoreactivity of protein- and humic-like DOM were observed with highly humidified material being the most photosensitive. Information generated by our study will provide a valuable data set for better understanding the impacts of future hydroelectric development and climate change on DOM biogeochemical dynamics in the Nelson/Hayes estuary and coastal domain. This study will constitute a reference on terrestrial DOM fate prior to building additional generating capacity on the Nelson River.

Near-Field Deformation Associated with the South Napa Earthquake (M 6.0) Using Differential Airborne LiDAR

NASA Astrophysics Data System (ADS)

Hudnut, K. W.; Glennie, C. L.; Brooks, B. A.; Hauser, D. L.; Ericksen, T.; Boatwright, J.; Rosinski, A.; Dawson, T. E.; Mccrink, T. P.; Mardock, D. K.; Hoirup, D. F., Jr.; Bray, J.

2014-12-01

Pre-earthquake airborne LiDAR coverage exists for the area impacted by the M 6.0 South Napa earthquake. The Napa watershed data set was acquired in 2003, and data sets were acquired in other portions of the impacted area in 2007, 2010 and 2014. The pre-earthquake data are being assessed and are of variable quality and point density. Following the earthquake, a coalition was formed to enable rapid acquisition of post-earthquake LiDAR. Coordination of this coalition took place through the California Earthquake Clearinghouse; consequently, a commercial contract was organized by Department of Water Resources that allowed for the main fault rupture and damaged Browns Valley area to be covered 16 days after the earthquake at a density of 20 points per square meter over a 20 square kilometer area. Along with the airborne LiDAR, aerial imagery was acquired and will be processed to form an orthomosaic using the LiDAR-derived DEM. The 'Phase I' airborne data were acquired using an Optech Orion M300 scanner, an Applanix 200 GPS-IMU, and a DiMac ultralight medium format camera by Towill. These new data, once delivered, will be differenced against the pre-earthquake data sets using a newly developed algorithm for point cloud matching, which is improved over prior methods by accounting for scan geometry error sources. Proposed additional 'Phase II' coverage would allow repeat-pass, post-earthquake coverage of the same area of interest as in Phase I, as well as an addition of up to 4,150 square kilometers that would potentially allow for differential LiDAR assessment of levee and bridge impacts at a greater distance from the earthquake source. Levee damage was reported up to 30 km away from the epicenter, and proposed LiDAR coverage would extend up to 50 km away and cover important critical lifeline infrastructure in the western Sacramento River delta, as well as providing full post-earthquake repeat-pass coverage of the Napa watershed to study transient deformation.

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

PubMed

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

2018-02-21

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

Unsupervised building detection from irregularly spaced LiDAR and aerial imagery

NASA Astrophysics Data System (ADS)

Shorter, Nicholas Sven

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

Influence of supplementation with corn dried distillers grains plus solubles to growing calves fed medium-quality hay on growth performance and feeding behavior.

PubMed

Islas, A; Gilbery, T C; Goulart, R S; Dahlen, C R; Bauer, M L; Swanson, K C

2014-02-01

To determine the effect of increasing supplementation of corn dried distillers grains plus solubles (DDGS) on growth performance and feeding behavior, 70 steer calves (287 ± 10 kg of BW) were blocked by BW to 3 pens equipped with Insentec feeders. For 84 d, calves were fed medium-quality grass/legume hay offered for ad libitum intake and provided 1 of 3 dietary supplemental treatments (n = 7 or 8 steers per treatment within each pen; n = 23 or 24 per treatment): 1) nothing, 2) DDGS at 0.5% of BW daily (DM basis), and 3) DDGS at 1% of BW daily (DM basis). Hay intake (kg/d and % of BW daily) decreased linearly (P < 0.001) as DDGS supplementation increased. Total DMI (kg/d and % of BW) increased linearly (P < 0.001) with DDGS supplementation. Average daily gain and gain efficiency (G:F) responded quadratically (P ≤ 0.006) as G:F increased to a lesser extent when DDGS supplementation increased from 0.5 to 1% than from 0 to 0.5%. Meals (number per day) and time eating per meal for hay and total diet decreased linearly (P ≤ 0.006) with increasing DDGS supplementation. Time eating per day for hay responded quadratically (P < 0.001) and decreased to a greater extent when increasing from 0 to 0.5% DDGS supplementation than from 0.5 to 1% DDGS. Feed intake per minute (eating rate) for hay and total diet increased linearly (P ≤ 0.05) with increasing DDGS supplementation. On d 84, LM area, back fat thickness, and rump fat thickness increased linearly (P ≤ 0.006) with increasing DDGS supplementation. There were significant day × treatment interactions (P < 0.001) for plasma glucose and urea-N concentrations. Glucose did not change over the feeding period in control steers but increased in both supplemented groups. Urea-N decreased for control steers over the feeding period whereas urea-N increased in supplemented steers. In conclusion, supplementation of DDGS in amounts of 0.5 or 1% of BW daily can be used to reduce hay intake and improve ADG and G:F in growing steers

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Economic consequences of earthquakes: bridging research and practice with HayWired

NASA Astrophysics Data System (ADS)

Wein, A. M.; Kroll, C.

2016-12-01

The U.S. Geological Survey partners with organizations and experts to develop multiple hazard scenarios. The HayWired earthquake scenario refers to a rupture of the Hayward fault in the Bay Area of California and addresses the potential chaos related to interconnectedness at many levels: the fault afterslip and aftershocks, interdependencies of lifelines, wired/wireless technology, communities at risk, and ripple effects throughout today's digital economy. The scenario is intended for diverse audiences. HayWired analyses translate earthquake hazards (surface rupture, ground shaking, liquefaction, landslides) into physical engineering and environmental health impacts, and into societal consequences. Damages to life and property and lifeline service disruptions are direct causes of business interruption. Economic models are used to estimate the economic impacts and resilience in the regional economy. The objective of the economic analysis is to inform policy discourse about economic resilience at all three levels of the economy: macro, meso, and micro. Stakeholders include businesses, economic development, and community leaders. Previous scenario analyses indicate the size of an event: large earthquakes and large winter storms are both "big ones" for California. They motivate actions to reduce the losses from fire following earthquake and water supply outages. They show the effect that resilience can have on reducing economic losses. Evaluators find that stakeholders learned the most about the economic consequences.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

The use of LiDAR-derived high-resolution DSM and intensity data to support modelling of urban flooding

NASA Astrophysics Data System (ADS)

Aktaruzzaman, Md.; Schmitt, Theo G.

2011-11-01

This paper addresses the issue of a detailed representation of an urban catchment in terms of hydraulic and hydrologic attributes. Modelling of urban flooding requires a detailed knowledge of urban surface characteristics. The advancement in spatial data acquisition technology such as airborne LiDAR (Light Detection and Ranging) has greatly facilitated the collection of high-resolution topographic information. While the use of the LiDAR-derived Digital Surface Model (DSM) has gained popularity over the last few years as input data for a flood simulation model, the use of LiDAR intensity data has remained largely unexplored in this regard. LiDAR intensity data are acquired along with elevation data during the data collection mission by an aircraft. The practice of using of just aerial images with RGB (Red, Green and Blue) wavebands is often incapable of identifying types of surface under the shadow. On the other hand, LiDAR intensity data can provide surface information independent of sunlight conditions. The focus of this study is the use of intensity data in combination with aerial images to accurately map pervious and impervious urban areas. This study presents an Object-Based Image Analysis (OBIA) framework for detecting urban land cover types, mainly pervious and impervious surfaces in order to improve the rainfall-runoff modelling. Finally, this study shows the application of highresolution DSM and land cover maps to flood simulation software in order to visualize the depth and extent of urban flooding phenomena.

A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits

PubMed Central

Wenzl, Peter; Li, Haobing; Carling, Jason; Zhou, Meixue; Raman, Harsh; Paul, Edie; Hearnden, Phillippa; Maier, Christina; Xia, Ling; Caig, Vanessa; Ovesná, Jaroslava; Cakir, Mehmet; Poulsen, David; Wang, Junping; Raman, Rosy; Smith, Kevin P; Muehlbauer, Gary J; Chalmers, Ken J; Kleinhofs, Andris; Huttner, Eric; Kilian, Andrzej

2006-01-01

Background Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding

UAV-LiDAR accuracy and comparison to Structure from Motion photogrammetry

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

A single dose desensitization for summer hay fever. Results of a double blind study-1988.

PubMed

Fell, P; Brostoff, J

1990-01-01

A new type of desensitising vaccine, enzyme potentiated was subjected to a double-blind randomised study during the hay fever season. The vaccine is a convenient single injection given in March and the results show good protection throughout the grass pollen season.

China: Tradition and Transformation Curriculum Projects. Fulbright-Hays Summer Seminars Abroad Program, 2001 (China).

ERIC Educational Resources Information Center

National Committee on United States-China Relations, New York, NY.

The curriculum projects in this collection represent the culmination of a Fulbright-Hays summer seminar for educators which took place in China in 2001. The collection contains 16 curriculum projects: "Notes on Giving a Presentation to a Parents Group, School Board or Other Public Audience Regarding Modern China" (David Bilka);…

China: Tradition and Transformation. Curriculum Projects. Fulbright-Hays Summer Seminars Abroad Program 1996 (China).

ERIC Educational Resources Information Center

National Committee on United States-China Relations, New York, NY.

These projects were completed by participants in the Fulbright-Hays summer seminar in China in 1996. The participants represented various regions of the U.S. and different grade levels and subject areas. The 15 curriculum projects in the collection are: (1) "Slide Narrative" (Debra Alexander); (2) "Peking Opera Painted Faces"…

Ground-Truthing of Airborne LiDAR Using RTK-GPS Surveyed Data in Coastal Louisiana's Wetlands

NASA Astrophysics Data System (ADS)

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

Canopy wake measurements using multiple scanning wind LiDARs

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Canopy wake measurements using multiple scanning wind LiDARs

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

A novel DARS2 mutation in a Japanese patient with leukoencephalopathy with brainstem and spinal cord involvement but no lactate elevation

PubMed Central

Shimojima, Keiko; Higashiguchi, Takafumi; Kishimoto, Kanako; Miyatake, Satoko; Miyake, Noriko; Takanashi, Jun-ichi; Matsumoto, Naomichi; Yamamoto, Toshiyuki

2017-01-01

The mitochondrial aspartyl-tRNA synthetase 2 gene (DARS2) is responsible for leukoencephalopathy with brainstem and spinal cord involvement and lactate elevation (LBSL). A Japanese patient with LBSL showed compound heterozygous DARS2 mutations c.358_359delinsTC (p.Gly120Ser) and c.228-15C>G (splicing error). This provides further evidence that most patients with LBSL show compound heterozygous mutations in DARS2 in association with a common splicing mutation in the splicing acceptor site of intron 2. PMID:29138691

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

Multiple quarantine treatment using bale compression and a three-day fumigation to control Hessian fly (Diptera: Cecidomyiidae) in exported hay.

PubMed

Yokoyama, Victoria Y

2014-06-01

A multiple quarantine treatment was developed to control Hessian fly puparia, Mayetiola destructor (Say), the stage of regulatory concern in exported hay. In a commercial test using 51.589 puparia, no insects survived to the adult stage after exposure to bale compression at 137 kg/cm2 and fumigation with 61 g/28.3 m3 hydrogen phosphide for 3d. The puparia were fumigated in infested wheat seedlings in cloth bags inside compressed timothy bales placed in different locations in three replicate freight containers in a heated building. Fumigant concentrations were 345-522 ppm on day 1; 580-824 ppm on day 2; and 680-861 ppm on day 3. Monitored temperatures were < 20 degrees C in all locations allowing the fumigation temperature to be established at > or = 20 degrees C. Copper detection plate corrosion values were severe inside the freight container doors, and moderate in the middle of bales in all locations, providing visual confirmation of exposure to hydrogen phosphide. Hydrogen phosphide residues in exposed hay bales were found in trace amounts, below the U.S. Environmental Protection Agency tolerance of 0.1 ppm for animal feeds. Timothy hay used in the commercial test is the representative species for all previously exported hay and straw species. The new multiple quarantine treatment is proposed for use with all previously tested bale sizes and wrapper styles for which 3-d fumigation data has been reported, and for bales and wrappers derived from those tested.

Effect of different potassium levels in hay on acid-base status and mineral balance in periparturient dairy cows.

PubMed

Rérat, M; Philipp, A; Hess, H D; Liesegang, A

2009-12-01

Forages commonly used in dry cow rations contain high K concentrations. This results in a high dietary cation-anion difference (DCAD), which can compromise the calcium homeostasis of periparturient cows. The aim of this study was to determine the effect of 2 types of hay, fed during the prepartum period and differing in their K concentrations, on the peripartum acid-base status and mineral balance of dairy cows. During the prepartum period, the cows of group K(33) (n = 6) received a diet based on hay with a high K concentration (33 g/kg of DM), whereas the cows of group K(13) (n = 6) received a diet based on hay with a low K concentration (13 g/kg of DM). Both experimental diets were formulated to be isoenergetic and isonitrogenous. After calving, all cows received the same diet based on hay K(33). Blood and urine samples were taken on d 14, 7, and 3 before parturition, at parturition, and then daily during the first 8 d after calving. Concentrations of minerals were analyzed in both blood and urine. Creatinine was also measured in urine for the calculation of the mineral:creatinine ratio. The acid-base parameters in blood (pH and HCO(3)(-) concentration) and urine (pH, net acid-base excretion, and base-acid quotient) were determined on d 14, 7, and 3 before parturition, at parturition, and on d 1 after parturition. The use of hay K(13) reduced the DCAD value of the prepartum diet by half (195 vs. 514 mEq/kg of DM). No significant differences between the 2 groups were observed for blood acid-base indicators or plasma minerals except for the Mg plasma concentration, which tended to be higher in group K(13) from d 3 prepartum to d 2 after calving. In group K(13), urinary Ca excretion tended to be higher from d 3 prepartum to d 1 after parturition than that in group K(33). On d 3 before parturition, urinary pH and net acid-base excretion were significantly lower in group K(13) than in group K(33). On d 14, 7, and 3 before parturition, base-acid quotient was

Development in Mexico and Central America. Fulbright-Hays Summer Seminars Abroad Program. Summer 1991.

ERIC Educational Resources Information Center

Institute of International Education, New York, NY.

This document features writings and curriculum projects by teachers who traveled to Mexico and Central America in the summer of 1991 as members of a Fulbright-Hays Summer Seminar. The following items are among the 20 included: Curriculum Project: "'Escritoras Mexicanas Contemporaneas': A Survey of Mexican Women Fiction Writers" (Laura J.…

A comparison of two open source LiDAR surface classification algorithms

USDA-ARS?s Scientific Manuscript database

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 Point Cloud and Stereo Image Point Cloud Fusion

DTIC Science & Technology

2013-09-01

LiDAR point cloud (right) highlighting linear edge features ideal for automatic registration...point cloud (right) highlighting linear edge features ideal for automatic registration. Areas where topography is being derived, unfortunately, do...with the least amount of automatic correlation errors was used. The following graphic (Figure 12) shows the coverage of the WV1 stereo triplet as

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

PubMed

Kahesa, Crispin; Kjaer, Susanne; Mwaiselage, Julius; Ngoma, Twalib; Tersbol, Britt; Dartell, Myassa; Rasch, Vibeke

2012-12-19

To describe how demographic characteristics and knowledge of cervical cancer influence screening acceptance among women living in Dar es Salaam, Tanzania. Multistage cluster sampling was carried out in 45 randomly selected streets in Dar es Salaam. Women between the ages of 25-59 who lived in the sampled streets were invited to a cervical cancer screening; 804 women accepted and 313 rejected the invitation. Information on demographic characteristics and knowledge of cervical cancer were obtained through structured questionnaire interviews. Women aged 35-44 and women aged 45-59 had increased ORs of 3.52 and 7.09, respectively, for accepting screening. Increased accepting rates were also found among single women (OR 2.43) and among women who had attended primary or secondary school (ORs of 1.81 and 1.94). Women who had 0-2 children were also more prone to accept screening in comparison with women who had five or more children (OR 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). 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 uptake of cervical cancer screening.

Identification of a new fault and associated lineament features in Oregon's Summer Lake Valley using high-resolution LiDAR data

NASA Astrophysics Data System (ADS)

Bennett, L.; Madin, I.

2012-12-01

In 2012, the Oregon Department of Geology and Mineral Industries (DOGAMI) contracted WSI to co-acquire airborne Light Detecting and Ranging (LiDAR) and Thermal Infrared Imagery (TIR) data within the region surrounding Summer Lake, Oregon. The objective of this project was to detect surficial expressions of geothermal activity and associated geologic features. An analysis of the LiDAR data revealed one newly identified fault and several accompanying lineaments that strike northwest, similar to the trend of the Ana River, Brothers, and Eugene-Denio Fault Zones in Central Oregon. The age of the Ana River Fault Zone and Summer Lake bed is known to be within the Holocene epoch. Apparent scarp height observed from the LiDAR is up to 8 meters. While detailed analysis is ongoing, the data illustrated the effectiveness of using high resolution remote sensing data for surficial analysis of geologic displacement. This presentation will focus on direct visual detection of features in the Summer Lake, Oregon landscape using LiDAR data.

Airborne LiDAR : a new source of traffic flow data : executive summary.

DOT National Transportation Integrated Search

2005-10-01

LiDAR (or airborne laser scanning) systems became a : dominant player in high-precision spatial data : acquisition in the late 90s. This new technology : quickly established itself as the main source of surface : information in commercial mapping,...

Tropical pasture hay utilization with slaframine and cottonseed meal: ruminal characteristics and digesta passage in wethers.

PubMed

Bird, A R; Croom, W J; Bailey, J V; O'Sullivan, B M; Hagler, W M; Gordon, G L; Martin, P R

1993-06-01

Sixteen mature, ruminally cannulated wethers (average BW = 41 +/- 1 kg) were fed a low-quality hay diet with or without a cottonseed meal (CSM) supplement and the parasympathomimetic agonist slaframine (SF). Treatments were basal diet (Mitchell grass hay, 4.8% CP, 46.8% ADF) available on an ad libitum basis, basal diet plus SF (8 micrograms/kg BW, 2 x daily i.m. injection), basal diet plus CSM (41.0% CP; 100 g/d), or basal diet plus SF and CSM. Treatments were arranged as a 2 x 2 factorial within a replicated 4 x 4 Latin square with 20-d periods followed by a 10-d adjustment during which only the basal diet was fed. All measurements were performed within the final 10 d of each period. Slaframine increased salivary flow by 10 to 35% (P < .07), ruminal fluid dilution rate by 8 to 11% (P < .10), and pH by 3 to 4% (P < .001). A twofold increase (P < .05) in ruminal cellulolytic bacteria numbers occurred in SF-treated wethers. Despite these SF-induced changes in the ruminal environment, whole-tract apparent nutrient digestibility, N and mineral balance, and ruminal VFA concentrations were not changed. Cottonseed meal increased forage intake by 34 to 54% (P < .001) and DM digestibility by 30% (P < .001). Cottonseed meal supplementation of a Mitchell grass hay diet improved nutritional status and attenuated live weight loss.

San Clemente Island Baseline LiDAR Mapping Final Report

DTIC Science & Technology

2016-12-01

automatically detect individual shrubs , though this method was more successful in some places than others. Finally, the hyperspectral data cubes, with...for California coastal shrub land, likely because the LiDAR tends not to penetrate the dense shrub , resulting in nearly identical first and last...subclasses of these structures. Using the aerial photographs in conjunction with the ground truth data, we automated the identification of the shrub Rhus

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Geo-referenced digital data acquisition and processing system using LiDAR technology.

DOT National Transportation Integrated Search

2006-02-01

LiDAR technology, introduced in the late 90s, has received wide acceptance in airborne surveying as a leading : tool for obtaining high-quality surface data at decimeter-level vertical accuracy in an unprecedentedly short : turnaround time. State-of-...

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

Treesearch

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

2008-01-01

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

34 CFR 662.20 - How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected?

Code of Federal Regulations, 2012 CFR

2012-07-01

... Abroad Fellow selected? 662.20 Section 662.20 Education Regulations of the Offices of the Department of... DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 662.20 How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected? (a) The Secretary considers applications for fellowships under...

34 CFR 662.20 - How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected?

Code of Federal Regulations, 2013 CFR

2013-07-01

... Abroad Fellow selected? 662.20 Section 662.20 Education Regulations of the Offices of the Department of... DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 662.20 How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected? (a) The Secretary considers applications for fellowships under...

34 CFR 662.20 - How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected?

Code of Federal Regulations, 2014 CFR

2014-07-01

... Abroad Fellow selected? 662.20 Section 662.20 Education Regulations of the Offices of the Department of... DISSERTATION RESEARCH ABROAD FELLOWSHIP PROGRAM Selection of Fellows § 662.20 How is a Fulbright-Hays Doctoral Dissertation Research Abroad Fellow selected? (a) The Secretary considers applications for fellowships under...

Replacing cottonseed meal with ground Prosopis juliflora pods; effect on intake, weight gain and carcass parameters of Afar sheep fed pasture hay basal diet.

PubMed

Yasin, Mohammed; Animut, Getachew

2014-08-01

The experiment was conducted to determine the supplementary feeding value of ground Prosopis juliflora pod (Pjp) and cottonseed meal (CSM) and their mixtures on feed intake, body weight gain and carcass parameters of Afar sheep fed a basal diet of pasture hay. Twenty-five yearling fat-tailed Afar rams with mean initial live weight 17.24 ± 1.76 kg (mean ± SD) were used in a randomized complete block design. Animals were blocked on their initial body weight. The experiment was conducted for 12 weeks and carcass evaluation followed. Treatments were hay alone ad libitum (T 1) or with 300 g CSM (T 2), 300 g Pjp (T 5), 2:1 ratio (T 3) and 1:2 ratio of CSM : Pjp (T 4). The CP contents of the hay, CSM and Pjp were 10.5, 44.5 and 16.7 %, respectively. Hay DM intake was higher (P < 0.05) for non-supplemented and total DM intake was lower in non-supplemented. Average daily weight gain (ADG) was lower (P < 0.05) for T 1 compared to all supplemented treatments except T 5. Hot carcass weight and rib-eye muscle area also followed the same trend like that of ADG. Compared with feeding hay alone, supplementing with CSM or a mixture of CSM and Pjp appeared to be a better feeding strategy, biologically, for yearling Afar rams.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Electro-microscopic observations of liver lesions after intravenous inoculation of mouldy hay extracts.

PubMed

Shadmi, A; Griffel, B

1985-01-01

With the aid of the electron microscope, a number of histopathological changes in the liver of mice caused by mycotoxins from mouldy hay were examined and studied. These changes were observed in the mitochondria, the cell nucleus, and the cell membranes, and included fatty and parenchymal degeneration, plasma granulation, vacuolisation and vesiculation, glycogen secretion, incorporation into RNA, karyolysis and karyolaxis, and space of Disse constriction.

Horizontal geometrical reaction time model for two-beam nacelle LiDARs

NASA Astrophysics Data System (ADS)

Beuth, Thorsten; Fox, Maik; Stork, Wilhelm

2015-06-01

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

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

DOT National Transportation Integrated Search

2016-01-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-09-09

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

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

Coastal and tidal landform detection from high resolution topobathymetric LiDAR data

NASA Astrophysics Data System (ADS)

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

2016-04-01

Coastal and tidal environments are valuable ecosystems, which, however, are under pressure in many areas around the world due to globalisation and/or climate change. Detailed mapping of these environments is required in order to manage the coastal zone in a sustainable way. However, historically these transition zones between land and water are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. The new generation of airborne topobathymetric light detection and ranging (LiDAR) potentially enables full-coverage and high-resolution mapping of these land-water transition zones. We have carried out topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the LiDAR point cloud with a mean point density in the order of 20 points/m2. The DEM was analysed morphometrically using a modification of the tool Benthic Terrain Modeler (BTM) developed by Wright et al. (2005). Initially, stage (the elevation in relation to tidal range) was used to divide the area of investigation into the different tidal zones, i.e. subtidal, intertidal and supratidal. Subsequently, morphometric units were identified and characterised by a combination of statistical neighbourhood analysis with varying window sizes (using the Bathymetric Positioning Index (BPI) from the BTM, moving average and standard deviation), slope parameters and area/perimeter ratios. Finally, these morphometric units were classified into six different types of landforms based on their stage and morphometric characteristics, i.e. either subtidal channel, intertidal flat, intertidal creek, linear bar, swash bar or beach dune. We hereby demonstrate the potential of using airborne topobathymetric LiDAR for seamless mapping of land

Wallace Creek Virtual Field Trip: Teaching Geoscience Concepts with LiDAR

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

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

NASA Technical Reports Server (NTRS)

Nelson, Ross; Ratnaswamy, Mary; Keller, Cherry

2004-01-01

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

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

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-06-17

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

A Systems Biology Approach Reveals Differences in the Dynamics of Colonization and Degradation of Grass vs. Hay by Rumen Microbes with Minor Effects of Vitamin E Supplementation

PubMed Central

Belanche, Alejandro; Newbold, Charles J.; Lin, Wanchang; Rees Stevens, Pauline; Kingston-Smith, Alison H.

2017-01-01

Increasing the efficiency of utilization of fresh and preserved forage is a key target for ruminant science. Vitamin E is often used as additive to improve product quality but its impact of the rumen function is unknown. This study investigated the successional microbial colonization of ryegrass (GRA) vs. ryegrass hay (HAY) in presence of zero or 50 IU/d supplementary vitamin E, using a rumen simulation technique. A holistic approach was used to link the dynamics of feed degradation with the structure of the liquid-associated (LAB) and solid-associated bacteria (SAB). Results showed that forage colonization by SAB was a tri-phasic process highly affected by the forage conservation method: Early colonization (0–2 h after feeding) by rumen microbes was 2× faster for GRA than HAY diets and dominated by Lactobacillus and Prevotella which promoted increased levels of lactate (+56%) and ammonia (+18%). HAY diets had lower DM degradation (-72%) during this interval being Streptococcus particularly abundant. During secondary colonization (4–8 h) the SAB community increased in size and decreased in diversity as the secondary colonizers took over (Pseudobutyrivibrio) promoting the biggest differences in the metabolomics profile between diets. Secondary colonization was 3× slower for HAY vs. GRA diets, but this delay was compensated by a greater bacterial diversity (+197 OTUs) and network complexity resulting in similar feed degradations. Tertiary colonization (>8 h) consisted of a slowdown in the colonization process and simplification of the bacterial network. This slowdown was less evident for HAY diets which had higher levels of tertiary colonizers (Butyrivibrio and Ruminococcus) and may explain the higher DM degradation (+52%) during this interval. The LAB community was particularly active during the early fermentation of GRA and during the late fermentation for HAY diets indicating that the availability of nutrients in the liquid phase reflects the dynamics of

Effect of lactic acid-lactobacillus preservative and moisture concentration at baling on intake and digestibility of crabgrass hay by lambs and in-situ digestibility by heifers

USDA-ARS?s Scientific Manuscript database

Crabgrass is a warm-season annual forage that has greater nutritive value than most other warm-season grasses and is highly palatable, but curing time for crabgrass hay is typically longer than for bermudagrass. Crabgrass hay was either not treated or treated with a lactic acid-lactobacillus preserv...

Computational modeling of river flow using bathymetry collected with an experimental, water-penetrating, green LiDAR

NASA Astrophysics Data System (ADS)

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

Processing and utilization of LiDAR data as a support for a good management of DDBR

NASA Astrophysics Data System (ADS)

Nichersu, I.; Grigoras, I.; Constantinescu, A.; Mierla, M.; Tifanov, C.

2012-04-01

Danube Delta Biosphere Reserve (DDBR) has 5,800 km2 as surface and it is situated in the South-East of Europe, in the East of Romania. The paper is taking into account the data related to the elevation surfaces of the DDBR (Digital Terrain Model DTM and Digital Surface Model DSM). To produce such kind of models of elevation for the entire area of DDBR it was used the most modern method that utilizes the Light Detection And Ranging (LiDAR). The raw LiDAR data (x, y, z) for each point were transformed into grid formats for DTM and DSM. Based on these data multiple GIS analyses can be done for management purposes : hydraulic modeling 1D2D scenarios, flooding regime and protection, biomass volume estimation, GIS biodiversity processing. These analyses are very useful in the management planning process. The hydraulic modeling 1D2D scenarios are used by the administrative authority to predict the sense of the fluvial water flow and also to predict the places where the flooding could occur. Also it can be predicted the surface of the terrain that will be occupied by the water from floods. Flooding regime gives information about the frequency of the floods and also the intensity of these. In the same time it could be predicted the time of water remanence period. The protection face of the flooding regime is in direct relation with the socio-cultural communities and all their annexes those that are in risk of being flooded. This raises the problem of building dykes and other flooding protection systems. The biomass volume contains information derived from the LiDAR cloud points that describes only the vegetation. The volume of biomass is an important item in the management of a Biosphere Reserve. Also the LiDAR cloud points that refer to vegetation could help in identifying the groups of vegetal association. All these information corroborated with other information build good premises for a good management. Keywords: Danube Delta Biosphere Reserve, LiDAR data, DTM, DSM

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

PubMed

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

2017-12-01

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

Using LiDAR to Estimate Surface Erosion Volumes within the Post-storm 2012 Bagley Fire

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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

Intake, digestibility, and passage rate of three warm-season grass hays consumed by beef steers

USDA-ARS?s Scientific Manuscript database

Florida-44 bermudagrass [Cynodon dactylon (L.) Pers.] is a fine-stemmed forage selected from a Tifton-44 field near Brooksville, FL that had drifted from the original and is highly desired for horses. The objective here was to assess quality of warm-season grass hays at different maturities in stall...

Brazilian History and Culture Program, June 27 - August 2, 1992. Fulbright Hays Seminars Abroad Program.

ERIC Educational Resources Information Center

1992

Sixteen participants in the Fulbright-Hays Seminar on the history and culture of Brazil traveled throughout Brazil from June 27 through August 2, 1992. At the end of the seminar 14 participants developed curriculum projects. Presented alphabetically by author, the 14 curricular projects cover aspects of Brazilian life and culture. Riva…

Environmental Issues in Brazilian Society. Fulbright-Hays Seminars Abroad Program. June 26-July 31, 1994.

ERIC Educational Resources Information Center

Commission for Educational Exchange between the United States and Brazil, Brasilia.

This book contains a review of the 1994 Fulbright-Hays Seminars Abroad Program along with lesson plans from 13 of the participants. The curriculum projects contained in this book include: (1) "The Brazilian Cinema: A Critical Appreciation of An Industry in Turmoil" (Aaron Braun); (2) "Reflections on the Relationship between…

Evaluation of hay and silage in receiving diets of newly weaned calves over two years

USDA-ARS?s Scientific Manuscript database

Silages are often viewed as less desirable feedstuffs in receiving diets offered to newly weaned calves. A two-year experiment was performed to determine the effects of oat forage harvested as either hay or silage from the same crop in receiving diets on cattle performance and diet mixing and integr...

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates.

PubMed

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.

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates

PubMed Central

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 (H2> 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 (H2> 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. PMID:29230229

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

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

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

Kumar, Jitendra; HargroveJr., William Walter; Norman, Steven P

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 andmore » 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.« less

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

NASA Astrophysics Data System (ADS)

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

75 FR 50777 - Final Comprehensive Conservation Plan; John Hay National Wildlife Refuge, Merrimack County, NH

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-17

.... We completed a thorough analysis of impacts on the human environment, which we included in the draft.... We would construct an alternate route for the John Hay II Forest Ecology Trail to allow visitors to... spur trail to the fen and back with informational signage on the ecology of fens, and install a...

Fulbright-Hays Seminars Abroad Program June 23-July 26, 1993. Brazilian History and Culture Program.

ERIC Educational Resources Information Center

Department of Education, Washington, DC. Div. of International Education.

This document consists of 16 papers on aspects of Brazilian culture, history, and geography prepared by participants in the Fulbright Hays Seminars Abroad Program in Brazil in 1993. The papers are: (1) "Cordel Literature: A Window on the History and Culture of Brazil" (Juan Barroso VIII); (2) "Connections: Public Images of Indians…

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

NASA Astrophysics Data System (ADS)

Koulas, Christos

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

Influence of Waveform Characteristics on LiDAR Ranging Accuracy and Precision

PubMed Central

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

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Large off-nadir scan angle of airborne LiDAR can severely affect the estimates of forest structure metrics

NASA Astrophysics Data System (ADS)

Liu, Jing; Skidmore, Andrew K.; Jones, Simon; Wang, Tiejun; Heurich, Marco; Zhu, Xi; Shi, Yifang

2018-02-01

Gap fraction (Pgap) and vertical gap fraction profile (vertical Pgap profile) are important forest structural metrics. Accurate estimation of Pgap and vertical Pgap profile is therefore critical for many ecological applications, including leaf area index (LAI) mapping, LAI profile estimation and wildlife habitat modelling. Although many studies estimated Pgap and vertical Pgap profile from airborne LiDAR data, the scan angle was often overlooked and a nadir view assumed. However, the scan angle can be off-nadir and highly variable in the same flight strip or across different flight strips. In this research, the impact of off-nadir scan angle on Pgap and vertical Pgap profile was evaluated, for several forest types. Airborne LiDAR data from nadir (0°∼7°), small off-nadir (7°∼23°), and large off-nadir (23°∼38°) directions were used to calculate both Pgap and vertical Pgap profile. Digital hemispherical photographs (DHP) acquired during fieldwork were used as references for validation. Our results show that angular Pgap from airborne LiDAR correlates well with angular Pgap from DHP (R2 = 0.74, 0.87, and 0.67 for nadir, small off-nadir and large off-nadir direction). But underestimation of Pgap from LiDAR amplifies at large off-nadir scan angle. By comparing Pgap and vertical Pgap profiles retrieved from different directions, it is shown that scan angle impact on Pgap and vertical Pgap profile differs amongst different forest types. The difference is likely to be caused by different leaf angle distribution and canopy architecture in these forest types. Statistical results demonstrate that the scan angle impact is more severe for plots with discontinuous or sparse canopies. These include coniferous plots, and deciduous or mixed plots with between-crown gaps. In these discontinuous plots, Pgap and vertical Pgap profiles are maximum when observed from nadir direction, and then rapidly decrease with increasing scan angle. The results of this research have many

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

PubMed

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

2017-02-01

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

Effect of cowpea hay, groundnut hay, cotton seed meal and maize meal supplementation to maize stover on intake, digestibility, microbial protein supply and acetate kinetics in weaner lambs.

PubMed

Chakeredza, S; ter Meulen, U; Ndlovu, L R

2002-02-01

Ten weaner lambs were used in a double 5 x 5 Latin square design to evaluate the effect of supplementing maize stover (MS) with cowpea hay (CW), groundnut hay (GN), cotton seed meal (CSM) or maize meal (MM) on the intake, digestion kinetics and acetate clearance rate. CW and GN were offered at 30% w/w to MS, while CSM and MM were given at 15 g/kg0.75 per day. Supplementation reduced (p < 0.01) MS intake but enhanced (p < 0.01) total dry matter intake. There were no significant differences (p > 0.05) in digestibility. However, the estimated ME intake was significantly (p < 0.05) improved by supplementation. The estimated microbial protein supply was almost significantly (p < 0.06) improved by 22.68%, 5.35%, 17.58% and 47.90% on the CW-, GN-, CSM- and MM-supplemented diets, compared to the control (7.85 g/day). Microbial protein synthesis efficiency was not significantly affected (p > 0.05) by diet, and nor were the acetate clearance rates (p > 0.05), which averaged 0.0475 +/- 0.0078/min. The improvement in ME intake may have been due to a faster flow rate of digesta and a better balance of nutrients in the end-products of digestion. These results demonstrate that small amounts of forage supplements can improve nutrient intake when animals consume low-quality forages and provide a basis for comparing such supplements with bought-in protein and energy supplements.

Analyzing Hydro-Geomorphic Responses in Post-Fire Stream Channels with Terrestrial LiDAR

NASA Astrophysics Data System (ADS)

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.

Hay fever, a post industrial revolution epidemic: a history of its growth during the 19th century.

PubMed

Emanuel, M B

1988-05-01

Although other forms of allergic disease were described in antiquity, hay fever is surprisingly modern. Very rare descriptions can be traced back to Islamic texts of the 9th century and European texts of the 16th century. It was only in the early 19th century that the disease was carefully described and at that time was regarded as most unusual. By the end of the 19th century it had become commonplace in both Europe and North America. This paper attempts to chart the growth of hay fever through the medical literature of the 19th century. It is hoped that an understanding of the increase in prevalence between 1820 and 1900 may provide an insight for modern researchers and give some clues into possible reasons for the epidemic nature of the disease today.

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

ERIC Educational Resources Information Center

Haslam, Nick

2011-01-01

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

Airborne LiDAR : a new source of traffic flow data, executive summary report.

DOT National Transportation Integrated Search

2005-10-01

LiDAR (or airborne laser scanning) systems became a : dominant player in high-precision spatial data : acquisition in the late 90s. This new technology : quickly established itself as the main source of surface : information in commercial mapping,...

TScan : stationary LiDAR for traffic and safety studies : object detection and tracking.

DOT National Transportation Integrated Search

2016-08-01

The ability to accurately measure and cost-effectively collect traffic data at road intersections is needed to improve their safety and operations. This study investigates the feasibility of using laser ranging technology (LiDAR) for this purpose. Th...

The eczema risk variant on chromosome 11q13 (rs7927894) in the population-based ALSPAC cohort: a novel susceptibility factor for asthma and hay fever.

PubMed

Marenholz, Ingo; Bauerfeind, Anja; Esparza-Gordillo, Jorge; Kerscher, Tamara; Granell, Raquel; Nickel, Renate; Lau, Susanne; Henderson, John; Lee, Young-Ae

2011-06-15

In a genome-wide association study, a common variant on chromosome 11q13.5 (rs7927894[T]) has been identified as a susceptibility locus for eczema. We aimed to analyze the effect of this risk variant on asthma and hay fever and to determine its impact on the general population level in over 9300 individuals of the prospectively evaluated Avon Longitudinal Study of Parents and Children birth cohort. We demonstrate an association of rs7927894[T] with atopic asthma and with hay fever. The largest effect sizes were found in patients with the combined phenotype atopic asthma plus eczema [odds ratio (OR) = 1.50; 95% confidence interval (CI) 1.20-1.88; P = 3.7 × 10(-4)] and hay fever plus eczema (OR = 1.37; 95% CI 1.15-1.62; P = 3.8 × 10(-4)). We replicated the effects of rs7927894[T] on eczema-associated asthma and hay fever independently in the German GENUFAD (GEnetic studies in NUclear Families with Atopic Dermatitis) study and show that they are significantly larger than the effect observed in eczema. The estimated population attributable risk fractions for eczema, eczema-associated atopic asthma or hay fever were 9.3, 24.9 and 23.5%, respectively. Finally in eczema, we found a synergistic interaction of rs7927894[T] with filaggrin gene (FLG) mutations, which are a major cause of epidermal barrier dysfunction, and replicated the interaction in the German Multicenter Allergy Study birth cohort. The synergistic effect of rs7927894[T] and FLG mutations on eczema risk as well as the association of both variants with eczema-associated atopic asthma and hay fever point to an involvement of rs7927894[T] in a functional pathway that is linked to the barrier defect.

Comparative study of building footprint estimation methods from LiDAR point clouds

NASA Astrophysics Data System (ADS)

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.

Do glyphosate resistant feral plants and hay fields spread the transgene to conventional alfalfa seed fields?

USDA-ARS?s Scientific Manuscript database

In addition to meeting domestic needs, large amounts of alfalfa seed and hay produced in the US are being exported overseas. Because alfalfa is an insect pollinated crop, gene flow is a concern. Adding to this alfalfa readily naturalizes along roadsides, irrigation ditches, and unmanaged habitats; a...

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

Treesearch

Demetrios Gatziolis

2012-01-01

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

Linking LiDAR with streamwater biogeochemistry in coastal temperate rainforest watersheds

Treesearch

Jason B. Fellman; Brian Buma; Eran Hood; Richard T. Edwards; David V. D’Amore

2017-01-01

The goal of this study was to use watershed characteristics derived from light detection and ranging (LiDAR) data to predict stream biogeochemistry in Perhumid Coastal Temperate Rainforest (PCTR) watersheds. Over a 2-day period, we sampled 37 streams for concentrations of dissolved C, N, P, major cations, and measures of dissolved organic matter quality (specific...

Statistical rigor in LiDAR-assisted estimation of aboveground forest biomass

Treesearch

Timothy G. Gregoire; Erik Næsset; Ronald E. McRoberts; Göran Ståhl; Hans Andersen; Terje Gobakken; Liviu Ene; Ross Nelson

2016-01-01

For many decades remotely sensed data have been used as a source of auxiliary information when conducting regional or national surveys of forest resources. In the past decade, airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool for sample surveys aimed at improving estimation of aboveground forest biomass. This technology is now...

A comparison of two open source LiDAR surface classification algorithms

Treesearch

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....

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

ERIC Educational Resources Information Center

Turkheimer, Eric

2011-01-01

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

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

Treesearch

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

2011-01-01

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

Airborne LiDAR : a new source of traffic flow data, research implementation plan.

DOT National Transportation Integrated Search

2005-10-01

LiDAR (or airborne laser scanning) systems became a dominant player in high-precision spatial data acquisition in the late 90's. This new technology quickly established itself as the main source of surface information in commercial mapping, deliverin...

Preliminary Results of Double-Sample Forest Inventory of Pine and Mixed Stands with High- and Low-Density LiDAR

Treesearch

Robert C. Parker; Patrick A. Glass

2004-01-01

LiDAR data (0.5 and 1 m postings) were used in a double-sample forest inventory on the Lee Experimental Forest, Louisiana. Phase 2 plots were established with DGPS. Tree d.b.h. (> 4.5 inches) and two sample heights were measured on every 10 th plot of the Phase 1 sample. Volume was computed for natural and planted pine and mixed hardwood species. LiDAR trees were...

Reauthorizing the Higher Education Act: Opportunities to Improve Student Success. Testimony of Lashawn Richburg-Hayes, MDRC [before the] U.S. Senate Health, Education, Labor, and Pensions Committee

ERIC Educational Resources Information Center

Richburg-Hayes, Lashawn

2015-01-01

This document presents the testimony of MDRC's Lashawn Richburg-Hayes before the U.S. Senate Health, Education, Labor, and Pensions Committee regarding evidence-based ways to improve the academic success of low-income college students. Richburg-Hayes makes four primary points based on existing research: (1) Comprehensive and integrated programs…

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

NASA Astrophysics Data System (ADS)

Feng, Dengchao; Yuan, Xiaohui

2016-05-01

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

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Effects on the equine colon ecosystem of grass silage and haylage diets after an abrupt change from hay.

PubMed

Muhonen, S; Julliand, V; Lindberg, J E; Bertilsson, J; Jansson, A

2009-07-01

The objective of this study was to investigate the effect of an abrupt change from grass hay (81% DM) to grass silage (36% DM) or grass haylage (55% DM), fed at similar DM intakes, and to compare the effects of silage and haylage on the composition and activities of the colon microflora. The forages were from the same swath harvested on the same day. Four adult colon-fistulated geldings were randomly assigned to diets in a crossover design. The study started with a preperiod when all 4 horses received the hay diet, followed by an abrupt feed change to the haylage diet for 2 horses and the silage diet for 2 horses. All 4 horses then had a new second preperiod of hay, followed by an abrupt feed change to the opposite haylage and silage diet. The periods were 21 d long, and the forage-only diets were supplemented with minerals and salt. The abrupt feed changes were made at 0800 h. Colon samples were taken before the abrupt feed change, 4 and 28 h after the feed change, and 8, 15, and 21 d after the feed change, all at 1200 h. Colon bacterial counts, VFA, pH, and DM concentrations were unchanged throughout the first 28 h after the abrupt feed change from hay to haylage and silage. Also, fecal pH and DM concentrations were unchanged during the first 28 h. During the weekly observations, colon lactobacilli counts increased (P = 0.023) in horses receiving the silage diet and were greater than on the haylage diet at 21 d. Streptococci counts decreased (P = 0.046) in horses receiving the haylage diet and were less than on the silage diet at 15 and 21 d. Total VFA concentrations and colon and fecal pH did not differ between diets and were unchanged throughout the weekly observations. The DM concentration of colon digesta and feces decreased (P = 0.030 and 0.049, respectively) on both diets during the weekly observations. The results suggest that in horses fed at the maintenance level of energy intake, an abrupt feed change from grass hay to grass silage or grass haylage from

A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification

PubMed Central

Kumar, G. Ajay; Patil, Ashok Kumar; Patil, Rekha; Park, Seong Sill; Chai, Young Ho

2017-01-01

Mapping the environment of a vehicle and localizing a vehicle within that unknown environment are complex issues. Although many approaches based on various types of sensory inputs and computational concepts have been successfully utilized for ground robot localization, there is difficulty in localizing an unmanned aerial vehicle (UAV) due to variation in altitude and motion dynamics. This paper proposes a robust and efficient indoor mapping and localization solution for a UAV integrated with low-cost Light Detection and Ranging (LiDAR) and Inertial Measurement Unit (IMU) sensors. Considering the advantage of the typical geometric structure of indoor environments, the planar position of UAVs can be efficiently calculated from a point-to-point scan matching algorithm using measurements from a horizontally scanning primary LiDAR. The altitude of the UAV with respect to the floor can be estimated accurately using a vertically scanning secondary LiDAR scanner, which is mounted orthogonally to the primary LiDAR. Furthermore, a Kalman filter is used to derive the 3D position by fusing primary and secondary LiDAR data. Additionally, this work presents a novel method for its application in the real-time classification of a pipeline in an indoor map by integrating the proposed navigation approach. Classification of the pipeline is based on the pipe radius estimation considering the region of interest (ROI) and the typical angle. The ROI is selected by finding the nearest neighbors of the selected seed point in the pipeline point cloud, and the typical angle is estimated with the directional histogram. Experimental results are provided to determine the feasibility of the proposed navigation system and its integration with real-time application in industrial plant engineering. PMID:28574474

Characterization of the horizontal structure of the tropical forest canopy using object-based LiDAR and multispectral image analysis

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

Effect of increasing the level of alfalfa hay in finishing beef heifer diets on intake, sorting, and feeding behavior.

PubMed

Madruga, A; González, L A; Mainau, E; Ruíz de la Torre, J L; Rodríguez-Prado, M; Manteca, X; Ferret, A

2018-02-15

Eight rumen cannulated Simmental heifers (BW = 281.4 ± 7.28 kg) were randomly assigned to one of four experimental treatments in a 4 × 4 replicated Latin square design to ascertain the effects of increasing levels of alfalfa hay on intake, sorting, and feeding behavior in comparison to barley straw as forage source. Treatments tested were four total mixed rations with: 1) 10% barley straw (10BS) with 7.0% NDF from forage, 2) 13% alfalfa hay (13AH) and less NDF from forage (5.7%) than 10BS, 3) 16% alfalfa hay (16AH) and the same NDF from forage (7.0%) as 10BS, and 4) 19% alfalfa hay (19AH) and more NDF from forage (8.3%) than 10BS. Each experimental period consisted of 3 wk for adaptation and 1 wk for sampling. Increasing the proportion of alfalfa hay in the diet linearly increased (P < 0.05) total DMI, CP intake, water consumption, intake of long, medium and fine particle size, extent of sorting of fine particle size, and time spent rumination, but linearly decreased (P < 0.05) extent of sorting of short particle size. Intake of DM was higher in heifers fed 16AH and 19AH than in heifers fed 10BS (P < 0.001). Intake of NDF and physically effective NDF (peNDF) was greater in 13AH, 16AH, and 19AH than in 10BS (P < 0.01). The DMI of medium and short particle size was greater in 13AH, 16AH, and 19AH than in 10BS (P < 0.05), whereas DMI of long particle size was greater in 16AH and 19AH compared to 10BS (P < 0.001). Heifers fed 13AH, 16AH, and 19AH diets sorted against fine particle size and sorted for or tended to sort for short, medium, and long particle sizes. Meal length was greater in heifers fed 16AH and 19AH than 10BS (P < 0.05). Time spent eating was not affected by diet but time spent ruminating was greater in heifers fed 19AH than in 10BS (P < 0.05). Results indicate that the inclusion of alfalfa hay at 19% of incorporation caused an increase in DM, NDF, and peNDF intake, in comparison to the 10BS diet. In the same way, intake of long, medium, and short

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed

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

Molecular genetic characterization of lasquerella new industrial crop using DArTseq markers

USDA-ARS?s Scientific Manuscript database

DArTseq, a new SNP-based marker platform, was developed and used to analyze the genetic diversity of the US germplasm collection of lesquerella. Lesquerella is a new oilseed crop in the Brassica family found native in the American Southwest. The potential of the species as a domestic source of indu...

Implementing DRGs at Silas B. Hays Army Community Hospital: Enhancement of Utilization Review

DTIC Science & Technology

1990-12-01

valuable assistance in creating this wordperfect document from both ASCII and ENABLE files. I thank them for their patience. Lastly, I wish to thank COL Jack...34error" predicate is called from a trap. A longmenu should eventually be used to assist in locating the RCMAS file. rcrnas-file:-not(existfile...B. Hays U.S. Army Community Hospital, Fort Ord, California has the potential to lose over $900 thousand in the supply budget category starting in

Automatic detection of zebra crossings from mobile LiDAR data

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

Effects of different fresh-cut forages and their hays on feed intake, digestibility, heat production, and ruminal methane emission by Boer x Spanish goats.

PubMed

Puchala, R; Animut, G; Patra, A K; Detweiler, G D; Wells, J E; Varel, V H; Sahlu, T; Goetsch, A L

2012-08-01

Twenty-four yearling Boer × Spanish wethers were used to assess effects of different forages, either fresh (Exp. 1) or as hay (Exp. 2), on feed intake, digestibilities, heat production, and ruminal methane emission. Treatments were: 1) Sericea lespedeza (SER; Lespedeza cuneata), a legume high in condensed tannins (CT; 20% and 15% in fresh forage and hay, respectively), 2) SER supplemented with polyethylene glycol (SER-PEG; 25 g/d), 3) alfalfa (Medicago sativa), a legume low in CT (ALF), and 4) sorghum-sudangrass (Sorghum bicolor), a grass low in CT (GRASS). Experiments were 22 d, which included 16 d for acclimatization followed by a 6-d period for fecal and urine collection, and gas exchange measurement (last 2 d). Intake of OM was 867, 823, 694, and 691 g/d (SEM = 20.1) with fresh forage, and 806, 887, 681, and 607 g/d with hay for SER, SER-PEG, ALF, and GRASS, respectively (SEM = 46.6). Apparent total tract N digestion was greater for SER-PEG vs. SER (P < 0.001) with fresh forage (46.3%, 66.5%, 81.7%, and 73.2%; SEM = 1.71) and hay (49.7%, 71.4%, 65.4%, and 54.8% for SER, SER-PEG, ALF, and GRASS, respectively; SEM = 1.57). Intake of ME was similar among treatments with fresh forage (8.24, 8.06, 7.42, and 7.70 MJ/d; SEM = 0.434) and with hay was greater for SER-PEG than ALF (P < 0.03) and GRASS (P < 0.001) (8.63, 10.40, 8.15, and 6.74 MJ/d for SER, SER-PEG, ALF, and GRASS, respectively; SEM = 0.655). The number of ciliate protozoa in ruminal fluid was least for SER with fresh forage (P < 0.01) (9.8, 20.1, 21.0, and 33.6 × 10(5)/ml; SEM = 2.76) and hay (P < 0.02) (6.3, 11.4, 13.6, and 12.5 × 10(5)/ml for SER, SER-PEG, ALF, and GRASS, respectively; SEM = 1.43). Methane emission as a percentage of DE intake was lower (P < 0.01) for SER vs. ALF and GRASS with fresh forage (6.6, 8.3, 9.4, and 9.2%; SEM = 0.64) and hay (4.3, 4.9, 6.4, and 6.7% for SER, SER-PEG, ALF, and GRASS, respectively; SEM = 0.38). In summary, methane emission in this short-term experiment was

Three-dimensional feature extraction and geometric mappings for improved parameter estimation in forested terrain using airborne LiDAR data

NASA Astrophysics Data System (ADS)

Lee, Heezin

Scanning laser ranging technology is well suited for measuring point-to-point distances because of its ability to generate small beam divergences. As a result, many of the laser pulses emitted from airborne light detection and ranging (LiDAR) systems are able to reach the ground underneath tree canopies through small (10 cm scale) gaps in the foliage. Using high pulse rate lasers and fast optical scanners, airborne LiDAR systems can provide both high spatial resolution and canopy penetration, and these data have become more widely available in recent years for use in environmental and forestry applications. The small-footprint, discrete-return Airborne Laser Swath Mapping (ALSM) system at the University of Florida (UF) is used to directly measure ground surface elevations and the three-dimensional (3D) distribution of the vegetative material above the soil surface. Field of view geometric mappings are explored to find optical gaps inside forests. First, a method is developed to detect walking trails in natural forests that are obscured from above by the canopy. Several features are derived from the ALSM data and used to constrain the search space and infer the location of trails. Second, a robust and simple procedure for estimating intercepted photosynthetically active radiation (IPAR), which is an important measure of forest timber productivity and of daylight visibility in forested terrain, is presented. Simple scope functions that isolate the relevant LiDAR reflections between observer locations and the sun are defined and shown to give good agreement between the LiDAR-derived estimates and values of IPAR measured in situ. A conical scope function with an angular divergence from the centerline of +/-7° provided the best agreement with the in situ measurements. This scope function yielded remarkably consistent IPAR estimates for different pine species and growing conditions. The developed idea could be extended, through potential future work, to characterize the

Remote measurement of surface roughness, surface reflectance, and body reflectance with LiDAR.

PubMed

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 (R_a), which can be used to validate the feasibility of the BRDF model in surface characterizations and performance evaluations.

An Integrated Multi-Omics Approach Reveals the Effects of Supplementing Grass or Grass Hay with Vitamin E on the Rumen Microbiome and Its Function

PubMed Central

Belanche, Alejandro; Kingston-Smith, Alison H.; Newbold, Charles J.

2016-01-01

Rumen function is generally suboptimal leading to losses in methane and nitrogen. Analysis of the rumen microbiome is thus important to understanding the underlying microbial activity under different feeding strategies. This study investigated the effect of forage conservation method and vitamin E supplementation on rumen function using a rumen simulation technique. Ryegrass (GRA) or ryegrass hay (HAY) was supplemented with 20% concentrate containing zero or 50 IU/d vitamin E, as α-tocopheryl acetate, according to a 2 × 2 factorial design. The forage conservation method did not substantially change the nutrient composition but had a profound impact on the structure and diversity of the rumen microbiome. HAY diets promoted a more complex bacterial community (+38 OTUs) dominated by Firmicutes. This bacterial adaptation, together with increased rumen protozoa levels and methanogen diversity, was associated with greater fiber disappearance (+12%) in HAY diets, but also with greater rumen true N degradability (+7%) than GRA diets. HAY diets also had a higher metabolic H recovery and methane production (+35%) suggesting more efficient inter-species H transfer between bacteria, protozoa and methanogens. Contrarily, GRA diets promoted more simplified methanogen and bacterial communities, which were dominated by Bacteroidetes and Lactobacillus, thus lactate formation may have acted as an alternative H sink in GRA diets. Moreover the structure of the bacterial community with GRA diets was highly correlated with N utilization, and GRA diets promoted greater bacterial growth and microbial protein synthesis (+16%), as well as a more efficient microbial protein synthesis (+22%). A dose-response experiment using batch cultures revealed that vitamin E supplementation increased rumen fermentation in terms of total VFA and gas production, with protozoal activity higher when supplying α-tocopheryl acetate vs. α-tocopherol. Moreover, α-tocopheryl acetate promoted a small increase

Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation.

PubMed

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

2018-01-01

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

Modeling plant composition as community continua in a forest landscape with LiDAR and hyperspectral remote sensing.

PubMed

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.

Optimizing the Use of LiDAR for Hydraulic and Sediment Transport Model Development: Case Studies from Marin and Sonoma Counties, CA

NASA Astrophysics Data System (ADS)

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

Nitrogen digestion and urea recycling in Hokkaido native horses fed hay-based diets.

PubMed

Obitsu, Taketo; Hata, Hiroshi; Taniguchi, Kohzo

2015-02-01

Nitrogen (N) digestion and urea-N metabolism in Hokkaido native horses fed roughage-based diets containing different types and levels of protein sources were studied. Horses (173 ± 4.8 kg) fitted with an ileum cannula were fed four diets consisting of 100% timothy hay (TH), 88% TH and 12% soybean meal (SBM), 79% TH and 21% SBM, and 51% TH and 49% alfalfa hay at 2.2% of body weight. Dietary protein content varied from 5% to 15% of dry matter. Apparent N digestibilities in the pre-cecum and total tract for the TH diet were lower than those for other diets. However, the proportion of post-ileum N digestion to N intake was not affected by the diets. Urea-N production was linearly related to N intake, but gut urea-N entry was not affected by the diets. The proportion of gut urea-N entry to urea-N production tended to be higher for the TH diet (57%) than the two SBM diets (39%). Anabolic use of urea-N entering the gut was not affected by the diets (20-36% of gut urea-N entry). These results indicate that urea-N recycling provides additional N sources for microbial fermentation in the hindgut of Hokkaido native horses fed low-quality roughages. © 2014 Japanese Society of Animal Science.

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

Treesearch

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

2014-01-01

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

Projects Submitted by Participants of the Fulbright-Hays Summer Seminars Abroad Program, 2000 (Poland and Hungary).

ERIC Educational Resources Information Center

2000

These curriculum projects were developed by participants of the Fulbright-Hays Seminars Abroad Program in Poland and Hungary during the summer of 2000. The following 11 projects are in the collection: "A Thematic Multicultural Interactive School Event on Poland and Hungary: Exploration and Learning for 6-to-9-Year-Olds" (Ruth Albert);…

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

USGS Publications Warehouse

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

2011-01-01

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

Influence of Time-Pickoff Circuit Parameters on LiDAR Range Precision

PubMed Central

Wang, Hongming; Yang, Bingwei; Huyan, Jiayue; Xu, Lijun

2017-01-01

A pulsed time-of-flight (TOF) measurement-based Light Detection and Ranging (LiDAR) system is more effective for medium-long range distances. As a key ranging unit, a time-pickoff circuit based on automatic gain control (AGC) and constant fraction discriminator (CFD) is designed to reduce the walk error and the timing jitter for obtaining the accurate time interval. Compared with Cramer–Rao lower bound (CRLB) and the estimation of the timing jitter, four parameters-based Monte Carlo simulations are established to show how the range precision is influenced by the parameters, including pulse amplitude, pulse width, attenuation fraction and delay time of the CFD. Experiments were carried out to verify the relationship between the range precision and three of the parameters, exclusing pulse width. It can be concluded that two parameters of the ranging circuit (attenuation fraction and delay time) were selected according to the ranging performance of the minimum pulse amplitude. The attenuation fraction should be selected in the range from 0.2 to 0.6 to achieve high range precision. The selection criterion of the time-pickoff circuit parameters is helpful for the ranging circuit design of TOF LiDAR system. PMID:29039772

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Road traffic sign detection and classification from mobile LiDAR point clouds

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure.

PubMed

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.

Leaf Movements of Indoor Plants Monitored by Terrestrial LiDAR

PubMed Central