Ground-based LIDAR: a novel approach to quantify fine-scale fuelbed characteristics

2009 ◽  
Vol 18 (6) ◽  
pp. 676 ◽  
Author(s):  
E. Louise Loudermilk ◽  
J. Kevin Hiers ◽  
Joseph J. O'Brien ◽  
Robert J. Mitchell ◽  
Abhinav Singhania ◽  
...  
Keyword(s):  
Leaf Area ◽  
Fire Behavior ◽  
Complex Surface ◽  
Individual Plant ◽  
Terrestrial Lidar ◽  
Novel Approach ◽  
Area Distribution ◽  
Ground Based Lidar ◽  
The Individual ◽  
Volume Estimates

Ground-based LIDAR (also known as laser ranging) is a novel technique that may precisely quantify fuelbed characteristics important in determining fire behavior. We measured fuel properties within a south-eastern US longleaf pine woodland at the individual plant and fuelbed scale. Data were collected using a mobile terrestrial LIDAR unit at sub-cm scale for individual fuel types (shrubs) and heterogeneous fuelbed plots. Spatially explicit point-intercept fuel sampling also measured fuelbed heights and volume, while leaf area and biomass measurements of whole and sectioned shrubs were determined from destructive sampling. Volumes obtained by LIDAR and traditional methods showed significant discrepancies. We found that traditional means overestimated volume for shrub fuel types because of variation in leaf area distribution within shrub canopies. LIDAR volume estimates were correlated with biomass and leaf area for individual shrubs when factored by species, size, and plant section. Fuelbed heights were found to be highly variable among the fuel plots, and ground LIDAR was more sensitive to capturing the height variation than traditional point intercept sampling. Ground LIDAR is a promising technology capable of measuring complex surface fuels and fuel characteristics, such as fuel volume.

scholarly journals A Novel Approach for Retrieving Tree Leaf Area from Ground-Based LiDAR

2016 ◽  
Vol 8 (11) ◽  
pp. 942 ◽  
Author(s):  
Ting Yun ◽  
Feng An ◽  
Weizheng Li ◽  
Yuan Sun ◽  
Lin Cao ◽  
...  
Keyword(s):  
Leaf Area ◽  
Novel Approach ◽  
Ground Based Lidar ◽  
Tree Leaf

scholarly journals Vertical Distribution of Leaf Area of European Larch (Larix decidua Mill.) and Norway Spruce (Picea abies (L.) Karst.) in Pure and Mixed Stands

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 570 ◽  
Author(s):  
Sterba ◽  
Dirnberger ◽  
Ritter
Keyword(s):  
Picea Abies ◽  
Leaf Area ◽  
Norway Spruce ◽  
Larix Decidua ◽  
European Larch ◽  
Beta Distributions ◽  
Area Distribution ◽  
The Individual ◽  
Individual Trees ◽  
Leaf Area Distribution

The growth effects of mixtures are generally assumed to be a result of canopy structure and crown plasticity. Thus, the distribution of leaf area at tree and stand level helps to explain these mixing effects. Therefore, we investigated the leaf area distribution in 12 stands with a continuum of proportions of European larch (Larix decidua Mill.) and Norway spruce (Picea abies (L.) Karst.). The stands were between 40 and 170 years old and located in the northern part of the Eastern Intermediate Alps in Austria at elevations between 900 and 1300 m a. s. l. A total of 200 sample trees were felled and the leaf area distribution within their crowns was evaluated. Fitting beta distributions to the individual empirical leaf area distributions, the parameters of the beta distributions were shown to depend on the leaf area of the individual trees and, for spruce, on the proportion of spruce in the stands. With the equations determined, the leaf area distribution of all trees in the stand, and thus its distribution in the stands, was calculated by species and in 2 m height classes. For the individual trees, we found that the leaf area distribution of larch is more symmetric, and its peak is located higher in the crown than it is the case for spruce. Furthermore, the leaf area distribution of both species becomes more peaked and skewed when the leaf area of the trees increases. The mixture only influences the leaf area distribution of spruce in such a way that the higher the spruce proportion of the stand, the higher the leaf area is located within the crown. At the stand level, a strong relationship was found between the proportion of spruce and the distance between the peaks of the leaf area distributions of larch and spruce.

Estimating leaf area distribution in savanna trees from terrestrial LiDAR measurements

2011 ◽  
Vol 151 (9) ◽  
pp. 1252-1266 ◽  
Author(s):  
Martin Béland ◽  
Jean-Luc Widlowski ◽  
Richard A. Fournier ◽  
Jean-François Côté ◽  
Michel M. Verstraete
Keyword(s):  
Leaf Area ◽  
Terrestrial Lidar ◽  
Area Distribution ◽  
Lidar Measurements ◽  
Leaf Area Distribution

Linking complex forest fuel structure and fire behaviour at fine scales

2012 ◽  
Vol 21 (7) ◽  
pp. 882 ◽  
Author(s):  
E. Louise Loudermilk ◽  
Joseph J. O'Brien ◽  
Robert J. Mitchell ◽  
Wendell P. Cropper ◽  
J. Kevin Hiers ◽  
...  
Keyword(s):  
Spatial Configuration ◽  
Bare Soil ◽  
Ensemble Classification ◽  
Fire Intensity ◽  
Fire Behaviour ◽  
Novel Approach ◽  
Fuel Heterogeneity ◽  
Ground Based Lidar ◽  
The Individual ◽  
In Fire

Improved fire management of savannas and open woodlands requires better understanding of the fundamental connection between fuel heterogeneity, variation in fire behaviour and the influence of fire variation on vegetation feedbacks. In this study, we introduce a novel approach to predicting fire behaviour at the submetre scale, including measurements of forest understorey fuels using ground-based LIDAR (light detection and ranging) coupled with infrared thermography for recording precise fire temperatures. We used ensemble classification and regression trees to examine the relationships between fuel characteristics and fire temperature dynamics. Fire behaviour was best predicted by characterising fuelbed heterogeneity and continuity across multiple plots of similar fire intensity, where impacts from plot-to-plot variation in fuel, fire and weather did not overwhelm the effects of fuels. The individual plot-level results revealed the significance of specific fuel types (e.g. bare soil, pine leaf litter) as well as the spatial configuration of fire. This was the first known study to link the importance of fuelbed continuity and the heterogeneity associated with fuel types to fire behaviour at metre to submetre scales and provides the next step in understanding the complex responses of vegetation to fire behaviour.

Physiological studies of competition in Zea mays L: I. Vegetative growth and ear development in maize

1969 ◽  
Vol 72 (2) ◽  
pp. 185-193 ◽  
Author(s):  
Maurice Eddowes
Keyword(s):  
Leaf Area ◽  
Dry Matter ◽  
Rapid Development ◽  
Total Yield ◽  
Field Studies ◽  
High Yield ◽  
Individual Plant ◽  
Dry Matter Accumulation ◽  
Net Assimilation ◽  
The Individual

SUMMARYPreliminary field studies were carried out to obtain an understanding of the progress of dry-matter accumulation in maize and its end-point at harvest. Dry-matter accumulation and its partition between morphological parts was affected, at various stages of growth, by competition. For maximum total yield per unit area of land, early and rapid development of leaf area was needed to exploit the relatively high net assimilation rate early in the season. This leaf area should persist as long as possibleto maximize leaf area duration. A high total plant yield, and high yield of the important ear component, by the individual plant, was obtained at a plant population of about 40000 per acre. The photosynthetic area of the ear made no significant contribution to cob weight.

scholarly journals On seeing the wood from the leaves and the role of voxel size in determining leaf area distribution of forests with terrestrial LiDAR

2014 ◽  
Vol 184 ◽  
pp. 82-97 ◽  
Author(s):  
Martin Béland ◽  
Dennis D. Baldocchi ◽  
Jean-Luc Widlowski ◽  
Richard A. Fournier ◽  
Michel M. Verstraete
Keyword(s):  
Leaf Area ◽  
Voxel Size ◽  
Terrestrial Lidar ◽  
Area Distribution ◽  
Leaf Area Distribution

Effect of location and year on some agronomical characters of maize hybrids

2005 ◽  
Vol 53 (3) ◽  
pp. 251-259 ◽  
Author(s):  
Z. Hegyi ◽  
T. Spitkó ◽  
J. Pintér
Keyword(s):  
Leaf Area ◽  
Plant Production ◽  
Individual Plant ◽  
Single Plant ◽  
Average Yield ◽  
Maize Hybrids ◽  
Year Effect ◽  
Single Cross ◽  
The Individual ◽  
Agronomical Characters

Some agronomical characters of twelve single-cross maize hybrids were investigated at five different locations in Hungary over a three-year period. The characters examined were individual plant production (total mass of the ears on a single plant), thousand-kernel mass, number of kernel rows, ear length, number of kernels per row, shelling % and the assimilating leaf area above the main ear. Among these yield components, the individual plant production, the ear length, the number of kernels per row and the grain-cob ratio (shelling %) were influenced to the greatest extent by the year, followed by the variety and the location. The greatest average yield was achieved by the tested hybrids at all five locations in 1997 (263 g/plant). The average yields in 1998 and 1999 were significantly lower (221 and 203 g/plant, respectively). The outstanding yields achieved in 1997 could be attributed to the favourable ecological conditions, which led to the development of secondary ears in Keszthely and Sopronhorpács. At the other three locations there was only one ear per plant, but these ears were longer than in the following years. The greatest year effect was recorded in Sopronhorpács, where the individual plant production amounted to 305 g/plant in 1997 and 238 g/plant in the worst year, 1999. In Gyöngyös conditions were very dry in all three years, so the year effect was least pronounced at this location (grand mean of 195 g/plant in 1997 and 201 g/plant in 1999). Stability analysis was carried out using the coefficient of variance for individual plant production. Hybrids Mv 3, Mv 5, Mv 9 and Mv 12 were found to have the best adaptability. The shelling % was not significantly influenced by the location; the grain-cob ratio is relatively stable for maize hybrids. A correlation was found between the individual plant production and the leaf area above the main ear (R2=0.658). Hybrids with the largest leaf area above the main ear also had the greatest ear mass.

scholarly journals The OsERF115/AP2EREBP110 Transcription Factor Is Involved in the Multiple Stress Tolerance to Heat and Drought in Rice Plants

2021 ◽  
Vol 22 (13) ◽  
pp. 7181
Author(s):  
Seong-Im Park ◽  
Hyeok Jin Kwon ◽  
Mi Hyeon Cho ◽  
Ji Sun Song ◽  
Beom-Gi Kim ◽  
...  
Keyword(s):  
Stress Tolerance ◽  
Transcriptional Activation ◽  
Individual Plant ◽  
Hormone Signaling ◽  
Combined Stress ◽  
Drought Treatment ◽  
Wide Range ◽  
The Individual ◽  
Potential Use ◽  
Multiple Stress Tolerance

The AP2/EREBP family transcription factors play important roles in a wide range of stress tolerance and hormone signaling. In this study, a heat-inducible rice ERF gene was isolated and functionally characterized. The OsERF115/AP2EREBP110 was categorized to Group-IIIc of the rice AP2/EREBP family and strongly induced by heat and drought treatment. The OsERF115/AP2EREBP110 protein targeted to nuclei and suppressed the ABA-induced transcriptional activation of Rab16A promoter in rice protoplasts. Overexpression of OsERF115/AP2EREBP110 enhanced thermotolerance of seeds and vegetative growth stage plants. The OsERF115/AP2EREBP110 overexpressing (OE) plants exhibited higher proline level and increased expression of a proline biosynthesis P5CS1 gene. Phenotyping of water use dynamics of the individual plant indicates that the OsERF115/AP2EREBP110-OE plant exhibited better water saving traits under heat and drought combined stress. Our combined results suggest the potential use of OsERF115/AP2EREBP110 as a candidate gene for genetic engineering approaches to develop heat and drought stress-tolerant crops.

Using hidden Markov models to find discrete targets in continuous sociophonetic data

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Daniel Duncan
Keyword(s):  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Abstract Representation ◽  
Language Variation And Change ◽  
Novel Approach ◽  
Single Target ◽  
The Individual ◽  
Individual Speaker

Abstract Advances in sociophonetic research resulted in features once sorted into discrete bins now being measured continuously. This has implied a shift in what sociolinguists view as the abstract representation of the sociolinguistic variable. When measured discretely, variation is variation in selection: one variant is selected for production, and factors influencing language variation and change are influencing the frequency at which variants are selected. Measured continuously, variation is variation in execution: speakers have a single target for production, which they approximate with varying success. This paper suggests that both approaches can and should be considered in sociophonetic analysis. To that end, I offer the use of hidden Markov models (HMMs) as a novel approach to find speakers’ multiple targets within continuous data. Using the lot vowel among whites in Greater St. Louis as a case study, I compare 2-state and 1-state HMMs constructed at the individual speaker level. Ten of fifty-two speakers’ production is shown to involve the regular use of distinct fronted and backed variants of the vowel. This finding illustrates HMMs’ capacity to allow us to consider variation as both variant selection and execution, making them a useful tool in the analysis of sociophonetic data.

scholarly journals HPM: A Hybrid Model for User’s Behavior Prediction Based on N-Gram Parsing and Access Logs

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Sonia Setia ◽  
Verma Jyoti ◽  
Neelam Duhan
Keyword(s):  
Web Mining ◽  
Contextual Information ◽  
Hybrid Approach ◽  
Web Pages ◽  
Continuous Growth ◽  
Novel Approach ◽  
Content Mining ◽  
Long Access ◽  
N Gram ◽  
The Individual

The continuous growth of the World Wide Web has led to the problem of long access delays. To reduce this delay, prefetching techniques have been used to predict the users’ browsing behavior to fetch the web pages before the user explicitly demands that web page. To make near accurate predictions for users’ search behavior is a complex task faced by researchers for many years. For this, various web mining techniques have been used. However, it is observed that either of the methods has its own set of drawbacks. In this paper, a novel approach has been proposed to make a hybrid prediction model that integrates usage mining and content mining techniques to tackle the individual challenges of both these approaches. The proposed method uses N-gram parsing along with the click count of the queries to capture more contextual information as an effort to improve the prediction of web pages. Evaluation of the proposed hybrid approach has been done by using AOL search logs, which shows a 26% increase in precision of prediction and a 10% increase in hit ratio on average as compared to other mining techniques.

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