Volumetric measurement of fossil charcoal: Principles, applications and potential

The Holocene ◽  
2020 ◽  
Vol 30 (10) ◽  
pp. 1481-1487
Author(s):  
Alastair J Crawford ◽  
Claire M Belcher
Keyword(s):  
Fire History ◽  
Particle Morphology ◽  
Power Transformation ◽  
Two Dimensional ◽  
Sedimentary Sequence ◽  
Volumetric Measurement ◽  
Data Set ◽  
Shape Coefficient ◽  
Volume Estimates ◽  
Area Data

Quantifying sedimentary charcoal content by estimation of volume from two-dimensional images is a relatively new and little-used method, but has the potential to improve the accuracy of fire histories. It requires a power transformation of area data, and multiplication by a coefficient to account for particle shape. The latter step has been routinely overlooked, or considered unnecessary, with volume estimates made simply by power transformation of the area data. Some researchers have used the method on the basis of the power transformation only, and others have rejected it as unnecessary on the same basis. However, the assumption that the shape coefficient can be ignored is likely to introduce very large errors, resulting in overestimation of charcoal volume. The magnitude of the error is indicated by a limited amount of empirical data obtained from volumetric measurement of individual charcoal particles, and accurate use of the method would require considerable further work to extend this data set. In a sedimentary sequence where particle morphology varies with depth, the errors identified could seriously distort the fire history produced. However, as such variation is easily identified, the method can still improve charcoal quantification where morphology is stationary.

scholarly journals Prediction of Wide Range Two-Dimensional Refractivity Using an IDW Interpolation Method from High-Altitude Refractivity Data of Multiple Meteorological Observatories

2021 ◽  
Vol 11 (4) ◽  
pp. 1431
Author(s):  
Sungsik Wang ◽  
Tae Heung Lim ◽  
Kyoungsoo Oh ◽  
Chulhun Seo ◽  
Hosung Choo
Keyword(s):  
High Altitude ◽  
Korean Peninsula ◽  
Interpolation Method ◽  
Atmospheric Condition ◽  
Propagation Path ◽  
Two Dimensional ◽  
Data Set ◽  
Wide Range ◽  
Atmospheric Data ◽  
Terrain Surface

This article proposes a method for the prediction of wide range two-dimensional refractivity for synthetic aperture radar (SAR) applications, using an inverse distance weighted (IDW) interpolation of high-altitude radio refractivity data from multiple meteorological observatories. The radio refractivity is extracted from an atmospheric data set of twenty meteorological observatories around the Korean Peninsula along a given altitude. Then, from the sparse refractive data, the two-dimensional regional radio refractivity of the entire Korean Peninsula is derived using the IDW interpolation, in consideration of the curvature of the Earth. The refractivities of the four seasons in 2019 are derived at the locations of seven meteorological observatories within the Korean Peninsula, using the refractivity data from the other nineteen observatories. The atmospheric refractivities on 15 February 2019 are then evaluated across the entire Korean Peninsula, using the atmospheric data collected from the twenty meteorological observatories. We found that the proposed IDW interpolation has the lowest average, the lowest average root-mean-square error (RMSE) of ∇M (gradient of M), and more continuous results than other methods. To compare the resulting IDW refractivity interpolation for airborne SAR applications, all the propagation path losses across Pohang and Heuksando are obtained using the standard atmospheric condition of ∇M = 118 and the observation-based interpolated atmospheric conditions on 15 February 2019. On the terrain surface ranging from 90 km to 190 km, the average path losses in the standard and derived conditions are 179.7 dB and 182.1 dB, respectively. Finally, based on the air-to-ground scenario in the SAR application, two-dimensional illuminated field intensities on the terrain surface are illustrated.

A Constrained Delaunay Triangulation Algorithm Based on Incremental Points

2011 ◽  
Vol 90-93 ◽  
pp. 3277-3282 ◽  
Author(s):  
Bai Chao Wu ◽  
Ai Ping Tang ◽  
Lian Fa Wang
Keyword(s):  
Information System ◽  
Data Structures ◽  
Delaunay Triangulation ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Three Dimensional ◽  
Geographical Information ◽  
Two Dimensional ◽  
Data Set ◽  
Constrained Delaunay Triangulation

The foundation ofdelaunay triangulationandconstrained delaunay triangulationis the basis of three dimensional geographical information system which is one of hot issues of the contemporary era; moreover it is widely applied in finite element methods, terrain modeling and object reconstruction, euclidean minimum spanning tree and other applications. An algorithm for generatingconstrained delaunay triangulationin two dimensional planes is presented. The algorithm permits constrained edges and polygons (possibly with holes) to be specified in the triangulations, and describes some data structures related to constrained edges and polygons. In order to maintain the delaunay criterion largely，some new incremental points are added onto the constrained ones. After the data set is preprocessed, the foundation ofconstrained delaunay triangulationis showed as follows: firstly, the constrained edges and polygons generate initial triangulations，then the remained points completes the triangulation . Some pseudo-codes involved in the algorithm are provided. Finally, some conclusions and further studies are given.

scholarly journals Pedestrian detection algorithm in traffic scene based on weakly supervised hierarchical deep model

2016 ◽  
Vol 14 (1) ◽  
pp. 172988141769231 ◽  
Author(s):  
Yingfeng Cai ◽  
Youguo He ◽  
Hai Wang ◽  
Xiaoqiang Sun ◽  
Long Chen ◽  
...  
Keyword(s):  
Deep Learning ◽  
Pedestrian Detection ◽  
Recognition Rate ◽  
Detection Algorithm ◽  
Training Methods ◽  
Two Dimensional ◽  
Data Set ◽  
Deep Model ◽  
Unsupervised Training ◽  
Weakly Supervised

The emergence and development of deep learning theory in machine learning field provide new method for visual-based pedestrian recognition technology. To achieve better performance in this application, an improved weakly supervised hierarchical deep learning pedestrian recognition algorithm with two-dimensional deep belief networks is proposed. The improvements are made by taking into consideration the weaknesses of structure and training methods of existing classifiers. First, traditional one-dimensional deep belief network is expanded to two-dimensional that allows image matrix to be loaded directly to preserve more information of a sample space. Then, a determination regularization term with small weight is added to the traditional unsupervised training objective function. By this modification, original unsupervised training is transformed to weakly supervised training. Subsequently, that gives the extracted features discrimination ability. Multiple sets of comparative experiments show that the performance of the proposed algorithm is better than other deep learning algorithms in recognition rate and outperforms most of the existing state-of-the-art methods in non-occlusion pedestrian data set while performs fair in weakly and heavily occlusion data set.

scholarly journals Global estimation of burned area using MODIS active fire observations

2006 ◽  
Vol 6 (4) ◽  
pp. 957-974 ◽  
Author(s):  
L. Giglio ◽  
G. R. van der Werf ◽  
J. T. Randerson ◽  
G. J. Collatz ◽  
P. Kasibhatla
Keyword(s):  
Vegetation Cover ◽  
Regression Trees ◽  
The United States ◽  
Tree Cover ◽  
Burned Area ◽  
Data Set ◽  
Active Fire ◽  
Terra Modis ◽  
Good Agreement ◽  
Area Data

Abstract. We present a method for estimating monthly burned area globally at 1° spatial resolution using Terra MODIS data and ancillary vegetation cover information. Using regression trees constructed for 14 different global regions, MODIS active fire observations were calibrated to burned area estimates derived from 500-m MODIS imagery based on the assumption that burned area is proportional to counts of fire pixels. Unlike earlier methods, we allow the constant of proportionality to vary as a function of tree and herbaceous vegetation cover, and the mean size of monthly cumulative fire-pixel clusters. In areas undergoing active deforestation, we implemented a subsequent correction based on tree cover information and a simple measure of fire persistence. Regions showing good agreement between predicted and observed burned area included Boreal Asia, Central Asia, Europe, and Temperate North America, where the estimates produced by the regression trees were relatively accurate and precise. Poorest agreement was found for southern-hemisphere South America, where predicted values of burned area are both inaccurate and imprecise; this is most likely a consequence of multiple factors that include extremely persistent cloud cover, and lower quality of the 500-m burned area maps used for calibration. Application of our approach to the nine remaining regions yielded comparatively accurate, but less precise, estimates of monthly burned area. We applied the regional regression trees to the entire archive of Terra MODIS fire data to produce a monthly global burned area data set spanning late 2000 through mid-2005. Annual totals derived from this approach showed good agreement with independent annual estimates available for nine Canadian provinces, the United States, and Russia. With our data set we estimate the global annual burned area for the years 2001-2004 to vary between 2.97 million and 3.74 million km2, with the maximum occurring in 2001. These coarse-resolution burned area estimates may serve as a useful interim product until long-term burned area data sets from multiple sensors and retrieval approaches become available.

scholarly journals Two-dimensional stochastic modeling for predicting bankruptcy for manufacturing companies

2021 ◽  
Vol 54 (2) ◽  
pp. 123-129
Author(s):  
James C. Fu ◽  
Winnie H. W. Fu
Keyword(s):  
Brownian Motion ◽  
Real Data ◽  
Bankruptcy Prediction ◽  
Boundary Crossing ◽  
Time Interval ◽  
Two Dimensional ◽  
Manufacturing Companies ◽  
Boundary Crossing Probability ◽  
Data Set ◽  
Crossing Probability

Increasing accuracy of the model prediction on business bankruptcy helps reduce substantial losses for owners, creditors, investors and workers, and, further, minimize an economic and social problem frequently. In this study, we propose a stochastic model of financial working capital and cashflow as a two-dimensional Brownian motion X(t) = (X1(t),X2(t)) on the business bankruptcy prediction. The probability of bankruptcy occurring in a time interval [0,T] is defined by the boundary crossing probability of the two-dimensional Brownian motion entering a predetermined threshold domain. Mathematically, we extend the result in Fu and Wu (2016) on the boundary crossing probability of a high dimensional Brownian motion to an unbounded convex hull. The proposed model is applied to a real data set of companies in US and the numerical results show the proposed method performs well.

scholarly journals COMPATIBILITY BETWEEN THE STEM VOLUME AND TAPER EQUATIONS VOLUME FOR BLACK WATTLE TREES

FLORESTA ◽  
2020 ◽  
Vol 50 (3) ◽  
pp. 1518
Author(s):  
Marcos Behling ◽  
Henrique Soares Koehler ◽  
Alexandre Behling
Keyword(s):  
Traditional Approach ◽  
Stem Volume ◽  
System Of Equations ◽  
Data Set ◽  
Taper Function ◽  
Black Wattle ◽  
Taper Equations ◽  
Volume Estimates ◽  
Forest Engineering

A system of equations widely used in Forest Engineering by the international community of researchers consists of a combination of a volumetric function and a taper function, with the purpose of making volume estimates compatible. When using the volume function and the taper function in a system, the result of the volume estimated by the two functions should be compatible, meaning that the volume estimated by the volumetric function should not differ from the volume obtained by integrating the taper function. Thus, the purpose of this paper was to develop and present the procedures of a system of equations to make volume estimates from both volume and taper equations compatible, and then compare it to the traditional approach, which is used in forestry companies. The procedures proposed were applied to a data set on the Acacia mearnsii De Wild. (black wattle) at sites where the plantation of this species is concentrated in the state of Rio Grande do Sul. The data set included 343 trees ranging from 5 to 10.75 years of age. It was noted that the lack of volume compatibility, in absolute terms, grows exponentially with the size of the tree. The quality of the estimates using the system of compatible equations did not differ from those obtained from the traditional model, therefore, the former is preferable. Furthermore, it was noted that the residuals from the volume and taper equations are correlated, which suggests that the system of equations be fitted simultaneously.

scholarly journals Individual Tree Volume Equations for Red Pine in Michigan

1997 ◽  
Vol 14 (2) ◽  
pp. 53-58 ◽  
Author(s):  
Gary W. Fowler
Keyword(s):  
Red Pine ◽  
Data Sets ◽  
Regression Equations ◽  
Independent Data ◽  
Data Set ◽  
Individual Tree ◽  
Standing Trees ◽  
Pine Stands ◽  
Volume Estimates ◽  
Volume Equations

Abstract New total, pulpwood, sawtimber, and residual pulpwood cubic foot individual tree volume equations were developed for red pine in Michigan using nonlinear and multiple linear regression. Equations were also developed for Doyle, International 1/4 in., and Scribner bd ft volume, and a procedure for estimating pulpwood and residual pulpwood rough cord volumes from the appropriate cubic foot equations was described. Average ratios of residual pulpwood (i.e., topwood, cubic foot or cords) to mbf were developed for 7.6 and 9.6 in. sawtimber. Data used to develop these equations were collected during May-August 1983-1985 from 3,507 felled and/or standing trees from 27 stands in Michigan. Sixteen and 11 stands were located in the Upper and Lower Peninsulas, respectively. All equations were validated on an independent data set. Rough cord volume estimates based on the new pulpwood equation were compared with contemporary tables for 2 small cruise data sets. The new equations can be used to more accurately estimate total volume and volume per acre when cruising red pine stands. North. J. Appl. For. 14(2):53-58.

Comparisons of Environmental Ordinations with Principal Component Vegetational Ordinations for Sets of Data Having Different Degrees of Complexity

1971 ◽  
Vol 1 (2) ◽  
pp. 99-112 ◽  
Author(s):  
J. K. Jeglum ◽  
C. F. Wehrhahn ◽  
J. M. A. Swan
Keyword(s):  
Principal Component Analysis ◽  
Water Level ◽  
Principal Component ◽  
Low Complexity ◽  
Component Analysis ◽  
Two Dimensional ◽  
High Complexity ◽  
Water Conductivity ◽  
Data Set ◽  
Total Data

Data from a survey of lowland, mainly peatland, vegetation were subjected to environmental ordination based on measurements of water level and water conductivity, and to vegetational ordination derived from principal component analysis (P.C.A.). Analyzed were the total set of the data ("all types"), half sets ("nonwoody" and "woody types") and quarter sets (stands of "marshes", "meadows", "shrub fens", and "other woody types"); the number of distinct physiognomic groups in a set of data, and presumably the amount of contained heterogeneity, decreased at each segmentation.The effectiveness of the ordination models was tested by correlating measured distances in two-dimensional ordination models with 2W/(A + B) indices of vegetational similarity for randomly selected pairs of types or stands. As the physiognomic complexity decreased, the effectiveness of the P.C.A. vegetational ordination increased whereas that of the environmental ordination decreased. The environmental ordination seemed most appropriate to the data encompassing high complexity (total data set), while the P.C.A. vegetational ordination seemed most appropriate to data with low complexity (quarter sets of the data).

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