scholarly journals Geographical distribution and volume of Antarctic icebergs derived from ship observation data

2017 ◽  
Vol 58 (74) ◽  
pp. 28-40 ◽  
Author(s):  
Yury A. Romanov ◽  
Nina A. Romanova ◽  
Peter Romanov
Keyword(s):  
Spatial Distribution ◽  
Standard Deviation ◽  
Southern Ocean ◽  
Geographical Distribution ◽  
Observation Data ◽  
Morphometric Characteristics ◽  
Concentration Data ◽  
Shape Distribution ◽  
Freshwater Balance ◽  
Area And Volume

ABSTRACTInformation on the occurrence, spatial distribution and morphometric characteristics of Antarctic icebergs is needed in a large number of applications including navigation, heat and freshwater balance calculations, biochemistry of the ocean and climatology. Using over 60 000 ship observations of icebergs in the Southern Ocean collected since the end of the 1940s we have produced a detailed map of the distribution of Antarctic icebergs as well as maps of related statistics including the standard deviation, minimum and maximum values of the iceberg concentration and the probability of iceberg-free observations. The study incorporated small and medium-sized icebergs with a length of <10 nautical miles. Most observations were taken during the warm period of the year, from December to April. It is shown that the iceberg distribution across the Southern Ocean is determined by the location of calving regions and peculiarities of the atmospheric circulation and ocean currents. Iceberg concentration data combined with information on the iceberg size and shape distribution have been used to evaluate the area-integrated characteristics of Antarctic icebergs. The instantaneous number of icebergs in the Southern Ocean was estimated as 132 269 with an uncertainty of 7%. The area and volume of icebergs were equal correspondingly to 55 805 km2 and 16 893 km3 with uncertainties of 32–33%.

scholarly journals Identifying the best spatial interpolation method for estimating spatial distribution of PM2.5 in Jakarta

2021 ◽  
Vol 893 (1) ◽  
pp. 012043
Author(s):  
K I Solihah ◽  
D N Martono ◽  
B Haryanto
Keyword(s):  
Spatial Distribution ◽  
Human Health ◽  
Model Evaluation ◽  
Interpolation Method ◽  
Health Effect ◽  
Air Pollutant ◽  
Observation Data ◽  
Concentration Data ◽  
Measurement Results ◽  
Spatial Interpolation Method

Abstract Nowadays, many researchers are focused on analyzing the association between PM2.5 concentration and respiratory diseases. PM2.5 is one of the most threatening air pollutant for human health in cities and causes an increasing number of deaths. However, obtaining detailed PM2.5 concentration data constitutes one of the problems in analyzing its relationship with the human health effect. This study aims to select the best model for predicting PM2.5, spatially explicit in Jakarta, and estimate its spatial distribution in this region over the 2019-2020 period. The observation data of PM2.5 measurement results were in eight points spread across Jakarta. Furthermore, the data is a two-year daily time series from 2019-2020, which was then be processed into annual average data. Seven spatial interpolations of different methods were selected to identify which is most realistic in generating the estimated concentration value of PM2.5. From the results, we conclude that the Spline with Tension was the best interpolation method based on 2D visualization and model evaluation. Based on the model evaluation, the Spline with Tension method generated the best model with minimum error, where RMSE, MSE, MAE, and MAP had values of 0.0533,0.0028, 0.0400, 0.0008, respectively. Meanwhile, Ordinary Kriging with spherical had the most significant.

scholarly journals Drivers of abundance and spatial distribution in Southern Ocean peracarid crustacea

2021 ◽  
Vol 128 ◽  
pp. 107832
Author(s):  
Davide Di Franco ◽  
Katrin Linse ◽  
Huw J. Griffiths ◽  
Angelika Brandt
Keyword(s):  
Spatial Distribution ◽  
Southern Ocean

scholarly journals Analisis Total Electron Content (TEC) Menggunakan Continous Wavelet Transform Sebagai Indikator Prekursor Gempa Bumi Di Wilayah Provinsi Bengkulu

2019 ◽  
Vol 9 (2) ◽  
pp. 27-33
Author(s):  
Laksamana Agung Aprillo ◽  
Hendy Santosa ◽  
Faisal Hadi
Keyword(s):  
Wavelet Transform ◽  
Standard Deviation ◽  
Total Electron Content ◽  
Electromagnetic Waves ◽  
Electron Content ◽  
Observation Data ◽  
Dual Frequency ◽  
Total Electron ◽  
Gps Observation ◽  
Large Earthquakes

ABSTRACT Bengkulu is one of 34 provinces in Indonesia which is a megathrust region. So Bengkulu province is often hit by many large earthquakes with shallow depth. TEC anomaly was analyzed based on three electromagnetic waves radiated by an earthquake. The total electron content (TEC) anomaly is seen through the global positioning system (GPS) dual-frequency radio signal data. The continuous wavelet transform (CWT) method is used to divide the signal analysis into several sections according to the electromagnetic wave frequency range of acoustic (2.5 mHz) -3 mHz), gravity waves (1 mHz-2.8 mHz) and rayleigh waves (5 mHz-33 mHz). GPS observation data for 9 days is calculated using the Standard deviation (2?) method to see trends in data changes. The analysis shows anomalies in the September 12 2007 earthquake (7.9 Mw), the March 5 2010 earthquake (6.3 Mw) and the August 4 2011 earthquake (6.0 Mw). Anomalies are detected 1 to 5 hours before an earthquake occurs. TEC anomalies that occur may be related to the process of preseismic before the earthquake and may be an early sign of an earthquake.Keyword: earthquake, total electron content, continous wavelet transform, standard deviation

Large discrepancies on nitrate loading estimates from sparse measurements by SWAT and statistical models at catchment scale

2021 ◽  
Author(s):  
Kang Liang ◽  
Yefang Jiang ◽  
Fan-Rui Meng
Keyword(s):  
Water Quality ◽  
Agricultural Watershed ◽  
Data Availability ◽  
Accurate Estimation ◽  
Observation Data ◽  
Load Estimation ◽  
Concentration Data ◽  
Regression Methods ◽  
Nitrate Load ◽  
Sparse Measurements

&lt;p&gt;Nitrogen (N) is one of the major pollutants to aquatic ecosystems. One of the key steps for efficient N reduction management at watershed scale is accurate quantification of N load. High frequency monitoring of stream water N concentration has not been common, and this has largely been the limiting factor for accurate estimation of N loading worldwide. N loads have often been estimated from sparse measurements. The objective of this study was to investigate the performance of the physical-based SWAT (Soil and Water Assessment Tool) model and three commonly used regression methods, namely LI (linear interpolation), WRTDS (Weighted Regression on Time, Discharge, and Season), and the LOADEST (LOAD ESTimator) on estimating nitrate load from sparse measurements through a case study in an agricultural watershed in eastern Canada. The range of daily nitrate load of SWAT and LOADEST was 0.05-1.29 and 0.14 - 1.35 t day&lt;sup&gt;-1&lt;/sup&gt;, compared with 0.13 - 13.08 t day&lt;sup&gt;-1&amp;#160; &lt;/sup&gt;and 0.15 - 16.75 t day&lt;sup&gt;-1 &lt;/sup&gt;for LI and WRTDS, respectively. Mean daily nitrate load estimated by the four methods followed the order: WRTDS &gt; LI &gt; LOADEST &gt; SWAT. The large discrepancies were mainly occurred during the non-growing season during which there was observation data available. As regression methods use concentration data from dry seasons to estimate the concentrations of wet seasons, there is a strong likelihood of overestimation of nitrate load for wet seasons. The results of this study shed new light on nitrate load estimation under conditions of different data availability. Under situations of limited water quality measurement, policy makers or researchers are likely to benefit from using hydrological models such as SWAT for constituent load estimation. However, the selection of the most appropriate method for load estimation should be seen as a dynamic process, and case by case evaluation is required especially when only sparsely measured data is available. As agri-environmental water quality issues become more pressing, it is critical that data collection strategies that encompass seasonal variation in streamflow and nitrate concentration be employed in regions like Atlantic Canada in the future.&lt;/p&gt;

Using betweenness metrics to investigate the geographical distribution of retailers

2020 ◽  
pp. 239980832097130
Author(s):  
Luigi Buzzacchi ◽  
Philippe Leveque ◽  
Roberta Taramino ◽  
Giulio Zotteri
Keyword(s):  
Spatial Distribution ◽  
Geographical Distribution ◽  
Differentiated Goods ◽  
Shopping Trips ◽  
The Impact

In retailing, a location’s accessibility and attractiveness depends on the spatial distribution of other stores and consumers. In particular, the literature shows that a place is more attractive for retailers if the generic routes taken by consumers often cross it. However, previous studies failed to consider that there are at least two possible consumer routes: job commutes from residential to workplaces and shopping trips among stores. In this paper, we analyze the impact of both consumer routes on the commercial patterns in Turin. The paper demonstrates that daily commutes to workplaces do not benefit a retailer along the trip, as much as journeys for shopping purposes do. In particular, we show that the benefits that a store can have when localized on the routes depend on the kind of goods it sells. Finally, the paper shows that stores selling homogeneous products and stores selling differentiated goods subject to comparison can differently benefit from being located in population hotspots and in commercial areas.

scholarly journals Spatial distribution of top soil water content in an experimental catchment of Southeast Brazil

2011 ◽  
Vol 68 (3) ◽  
pp. 285-294 ◽  
Author(s):  
Carlos Rogério de Mello ◽  
Léo Fernandes Ávila ◽  
Lloyd Darrell Norton ◽  
Antônio Marciano da Silva ◽  
José Márcio de Mello ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Standard Deviation ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Time Domain Reflectometry ◽  
Water Infiltration ◽  
Local Factor ◽  
Top Soil ◽  
Over Time

Soil water content is essential to understand the hydrological cycle. It controls the surface runoff generation, water infiltration, soil evaporation and plant transpiration. This work aims to analyze the spatial distribution of top soil water content and to characterize the spatial mean and standard deviation of top soil water content over time in an experimental catchment located in the Mantiqueira Range region, state of Minas Gerais, Brazil. Measurements of top soil water content were carried out every 15 days, between May/2007 and May/2008. Using time-domain reflectometry (TDR) equipment, 69 points were sampled in the top 0.2 m of the soil profile. Geostatistical procedures were applied in all steps of the study. First, the spatial continuity was evaluated, and the experimental semi-variogram was modeled. For the development of top soil water content maps over time a co-kriging procedure was used having the slope as a secondary variable. Rainfall regime controlled the top soil water content during the wet season. Land use was also another fundamental local factor. The spatial standard deviation had low values under dry conditions, and high values under wet conditions. Thus, more variability occurs under wet conditions.

The geographical distribution of passenger railway hubs in Russia

2020 ◽  
pp. 121-130
Author(s):  
K. V. Samburov
Keyword(s):  
Spatial Distribution ◽  
Population Size ◽  
Geographical Distribution ◽  
Saint Petersburg ◽  
Economic Regions

The geographical distribution of 550 passenger railway nodes that are serving longer distance trains were studied. It’s containing 622 stations, which encompass more than 97% of passenger departures total number on the railway in 2016 were selected and grouped according to its size and the main nodes’characteristics were analyzed. Studying dependence of node’s rank and size from number of people, which live in its area, revealed that the less population size center is, the more other factors influence. The factual and ideal Zipf’s curve for the hierarchy of railway nodes were analyzed and its discrepancy was identified. An excessive role of Moscow as a main node and of Saint Petersburg as the second center is a feature in the hierarchy of nodes. This research also represents the analysis of nodes’ upper groups (more than 250 000 passenger departures per year). Spatial distribution of passenger railway nodes on the territory of Russia is descripted and the similarity of it with area of main resettlement was found. However, the density of relatively large nodes increases in Central and Central Black Earth economic regions and in Circum-Pontic region

Statistical Analysis Relating to Recent Federal Standard 209 (Cleanrooms) Revisions

1988 ◽  
Vol 31 (5) ◽  
pp. 48-52
Author(s):  
Douglas Cooper
Keyword(s):  
Standard Deviation ◽  
Statistical Tests ◽  
Average Concentration ◽  
Airborne Particles ◽  
Simulation Methods ◽  
Concentration Data ◽  
Normal Distributions ◽  
Good Practices ◽  
Federal Standard ◽  
Poisson Data

The recent revisions of Federal Standard 209 regarding clean-rooms include two statistical tests for the concentration data obtained from sampling airborne particles: a) that none of the location averages exceeds the Class Limit (CL) and b) that there be 95 percent confidence that the true mean of the location averages does not exceed the CL, based on the data making up the grand mean of averages. For sampling from a constant and uniform concentration (Poisson data) or from a concentration giving data that are normally distributed, we show the statistical implications of choosing a certain level of confidence that no location average exceed CL. Similarly, we show the statistical implications of the 95 percent confidence requirement on the grand mean. For any situation where each location has approximately the same standard deviation in its readings, the Poisson and normal distributions included, if one has 95 percent confidence that none of the locations exceeds the CL, the requirement for the grand mean is also likely to be met if five or more locations are sampled. Simulation methods can assist prediction, and several methods are summarized. The likelihood of meeting the standard can usually be improved by: reducing the average concentration and the variability of the concentration (through design and good practices), increasing the number of samples per location and the volume sampled for each, and keeping the number of locations sampled to the minimum allowed.

scholarly journals Influence of the Spatial Distribution Pattern of Buildings on the Distribution of PM2.5 Concentration

2021 ◽  
Author(s):  
Zhixuan Zhang ◽  
Baoyan Shan ◽  
Qikai Lin ◽  
Yanqiu Chen ◽  
Xinwei Yu
Keyword(s):  
Spatial Distribution ◽  
Standard Deviation ◽  
Spatial Structure ◽  
Distribution Pattern ◽  
Distribution Patterns ◽  
Spatial Distribution Pattern ◽  
Urban Spatial Structure ◽  
Coverage Ratio ◽  
The Mean ◽  
Pm2.5 Concentration

Abstract The spatial distribution pattern of buildings is an entry point for controlling the diffusion of pollution particles at an urban spatial structure scale. In this study, we adopted ordinary kriging interpolation and other methods to study the spatial distribution pattern of PM2.5 and constructed urban spatial structure indexes based on building distribution patterns to reveal the influence of building spatial distribution patterns on PM2.5 concentration across the study area and at different elevations. The present study suggests that: (1) Topographic elevation is an important factor influencing the distribution of PM2.5; the correlation coefficient reaches −0.761 and exceeds the 0.001 confidence level. As the elevation increases, the urban spatial structure indexes show significant correlations with PM2.5, and the regularity becomes stronger. (2) The PM2.5 concentration is negatively correlated with the mean and standard deviation of the DEM, the mean and maximum absolute building height, the outdoor activity area, and the average distance between adjacent buildings; and is positively correlated with the sum of the building base area, the building coverage ratio, the space area, the building coverage ratio, the space occupation ratio, and the sum of the building volume. These urban spatial structure indexes are important factors affecting PM2.5 concentration and distribution and should be considered in urban planning. (3) Spatio-temporal differences in PM2.5 concentration and distribution were found at different elevation and time ranges. Indexes, such as the average building height, the average building base area, the sum of the building volume, and the standard deviation of building volume experienced significant changes. Higher PM2.5 concentration yielded a more significant influence of urban spatial structure indexes on PM2.5 distribution. More discrete spatial distributions of PM2.5 yielded weaker correlations between PM2.5 concentrations and the urban spatial structure indexes.

scholarly journals Cost of territorial maintenance by Parodon nasus (Osteichthyes: Parodontidae) in a Neotropical stream

2009 ◽  
Vol 7 (4) ◽  
pp. 677-682 ◽  
Author(s):  
Samuel Elias Silva ◽  
Wilhan R. C. Assunção ◽  
Charles Duca ◽  
Jerry Penha
Keyword(s):  
Spatial Distribution ◽  
Standard Deviation ◽  
Territorial Behavior ◽  
Maintenance Cost ◽  
Behavioral Patterns ◽  
Mato Grosso ◽  
Neotropical Stream ◽  
The Relationship

The combined demand over a certain resource may exceed its immediate supply, which can then lead to competition between individuals. This competition may result in territorial behavior. In this study we determine the density and spatial distribution, describe the interactions arising from territorial behavior and evaluate the costs of keeping the territories defended by adults of Parodon nasus. The study was conducted in Camarinha Stream located in the Serra das Araras Ecological Station, Porto Estrela, State of Mato Grosso, Brazil. The density was constant throughout the length of the stream, with a mean (± standard deviation) of 1.01 ind./m² (± 0.14). Our results show that the spatial distribution of individuals in the area ranged between uniform and random. The territories were defended more often against intraspecific than interspecific intruders. The time that the owners of the territories devoted to defending them was not influenced by the size of the territories. However, owners of larger territories spent more time foraging than owners of smaller territories. As a result, owners of larger territories had less time to rest than owners of smaller territories. The results of this study show behavioral patterns relevant to understanding the relationship between size and territorial maintenance cost of P. nasus and other species of fish with territorial behavior.

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