scholarly journals Growth, cycles and convergence in US regional time series

2005 ◽  
Vol 21 (4) ◽  
pp. 667-686 ◽  
Author(s):  
Vasco M. Carvalho ◽  
Andrew C. Harvey
Keyword(s):  
Time Series ◽  
Growth Cycles

scholarly journals Assessing Landsat Fractional Ground-Cover Time Series across Australia's Arid Rangelands: Separating Grazing Impacts from Climate Variability

2017 ◽  
Author(s):  
Jason Barnetson ◽  
Stuart Phinn ◽  
Peter Scarth ◽  
Robert Denham
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Ground Cover ◽  
Field Measurements ◽  
Change Point Detection ◽  
Grazing Impact ◽  
Growth Cycles ◽  
Grazing Impacts ◽  
Arid Rangelands

Suitable measures of grazing impacts on ground cover, that enable separation of the effects of climatic variations, are needed to inform land managers and policy makers across the arid rangelands of the Northern Territory of Australia. This work developed and tested a time-series, change-point detection method for application to time series of vegetation fractional cover derived from Landsat data to identify irregular and episodic ground-cover growth cycles. These cycles were classified to distinguish grazing impacts from that of climate variability. A measure of grazing impact was developed using a multivariate technique to quantify the rate and degree of ground cover change. The method was successful in detecting both long term (> 3 years) and short term (< 3 years) growth cycles. Growth cycle detection was assessed against rainfall surplus measures indicating a relationship with high rainfall periods. Ground cover change associated with grazing impacts was also assessed against field measurements of ground cover indicating a relationship between both field and remotely sensed ground cover. Cause and effects between grazing practices and ground cover resilience can now be explored in isolation to climatic drivers. This is important to the long term balance between ground cover utilisation and overall landscape function and resilience.

scholarly journals Forecasting Cycles in the Transportation Sector

2010 ◽  
Author(s):  
Vincent W. Yao ◽  
Brian W. Sloboda
Keyword(s):  
Time Series ◽  
Evaluation Criteria ◽  
Time Series Models ◽  
Leading Indicators ◽  
Modern Time ◽  
General State ◽  
Growth Cycles ◽  
Screening Techniques ◽  
Transportation Sector ◽  
Timely Fashion

This paper predicted fluctuations in the transportation sector using leading indicators. From 25 initial candidates, we selected seven leading indicators, using various screening techniques and modern time series models. A composite leading index was constructed and found to perform well in predicting transportation reference cycles. The leading index signals downturns in the transportation sector 10 months ahead and upturns six months ahead on average. The index predicted the latest recession in transportation with a lead of 20 months. The analysis also confirms the predictive contents of the composite leading index (CLI) in relation to transportation growth cycles. These evaluation criteria ensure accurate forecasts of the general state of the transportation sector in a timely fashion.

scholarly journals ASSESSING LANDSAT FRACTIONAL GROUND-COVER TIME SERIES ACROSS AUSTRALIA’S ARID RANGELANDS: SEPARATING GRAZING IMPACTS FROM CLIMATE VARIABILITY

2017 ◽  
Vol XLII-3/W2 ◽  
pp. 15-26 ◽  
Author(s):  
J. Barnetson ◽  
S. Phinn ◽  
P. Scarth ◽  
R. Denham
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
High Performance ◽  
Ground Cover ◽  
Field Measurements ◽  
Grazing Impact ◽  
Growth Cycles ◽  
Grazing Impacts ◽  
Arid Rangelands

Suitable measures of grazing impacts on ground cover, that enable separation of the effects of climatic variations, are needed to inform land managers and policy makers across the arid rangelands of Australia. This work developed and tested a time-series, changepoint detection method for application to time series of vegetation fractional cover derived from Landsat data to identify irregular and episodic ground-cover growth cycles. Utilising the High Performance Computing power of the Google Cloud Compute Engine these cycles were segmented to distinguish grazing impacts from that of climate variability. A measure of grazing impact was developed using a multivariate technique to quantify the rate and degree of ground cover change. The method was successful in detecting both long term and short term growth cycles. Growth cycle detection was assessed against rainfall surplus measures indicating a relationship with high rainfall periods. During periods of ground cover decline, grazing utilisation was observed across four major grasslands. Ground cover change associated with grazing impacts was also assessed against field measurements of ground cover indicating a relationship between both field and remotely sensed ground cover. Cause and effects between grazing practices and ground cover resilience can now be explored in isolation to climatic drivers. This is important to the long term balance between ground cover utilisation and overall landscape function and resilience.

Growth, cycles, and convergence in US regional time series: A personal point of view

2005 ◽  
Vol 21 (4) ◽  
pp. 687-689
Author(s):  
Miguel Jerez ◽  
José Casals ◽  
Sonia Sotoca
Keyword(s):  
Time Series ◽  
Point Of View ◽  
Growth Cycles

scholarly journals Economic sensor for Misiones province from 2005 to 2018

2019 ◽  
pp. 195-213
Author(s):  
Nicolás Álvarez ◽  
Juan Luis Heredia ◽  
María Natalia León
Keyword(s):  
Time Series ◽  
Economic Activity ◽  
Cross Correlation ◽  
Composite Indicator ◽  
Sources Of Information ◽  
Growth Cycles ◽  
First Approximation ◽  
Misiones Province

This paper presents the construction of a composite indicator of economic activity for the province of Misiones for the period 2005 – 2018, in order to measure fluctuations of economic and growth cycles. The methodologies proposed by The Conference Board (2001) and Jorrat (2003), that are referents at international and national levels respectively, are used. This methodology gives less weight to time series which variations have more volatility. After selecting eleven component series from public sources of information and representatives from different sectors of the provincial economic activity, seasonally adjusted using X-13 ARIMA and aggregating them, it is obtained a composite indicator representative for the economic activity, named Misiones Economic Sensor (MisES). This indicator is a first approximation of provincial economic activity’s fluctuations, and given that cross correlation with EMAE (Mensual Estimator of Economic Activity) is 0.93 when t=0, it is presumed that it is represents fluctuations observed in the provincial economy.

The LDE-Type Flare Occurrence (1969-1993)

1994 ◽  
Vol 144 ◽  
pp. 279-282
Author(s):  
A. Antalová
Keyword(s):  
Time Series ◽  
Fourier Analysis ◽  
Sunspot Cycle ◽  
List Type ◽  
Type Number ◽  
Solar Cycles ◽  
Type Iv ◽  
Long Duration ◽  
Cycle Maximum ◽  
Flare Index

AbstractThe occurrence of LDE-type flares in the last three cycles has been investigated. The Fourier analysis spectrum was calculated for the time series of the LDE-type flare occurrence during the 20-th, the 21-st and the rising part of the 22-nd cycle. LDE-type flares (Long Duration Events in SXR) are associated with the interplanetary protons (SEP and STIP as well), energized coronal archs and radio type IV emission. Generally, in all the cycles considered, LDE-type flares mainly originated during a 6-year interval of the respective cycle (2 years before and 4 years after the sunspot cycle maximum). The following significant periodicities were found:• in the 20-th cycle: 1.4, 2.1, 2.9, 4.0, 10.7 and 54.2 of month,• in the 21-st cycle: 1.2, 1.6, 2.8, 4.9, 7.8 and 44.5 of month,• in the 22-nd cycle, till March 1992: 1.4, 1.8, 2.4, 7.2, 8.7, 11.8 and 29.1 of month,• in all interval (1969-1992):a)the longer periodicities: 232.1, 121.1 (the dominant at 10.1 of year), 80.7, 61.9 and 25.6 of month,b)the shorter periodicities: 4.7, 5.0, 6.8, 7.9, 9.1, 15.8 and 20.4 of month.Fourier analysis of the LDE-type flare index (FI) yields significant peaks at 2.3 - 2.9 months and 4.2 - 4.9 months. These short periodicities correspond remarkably in the all three last solar cycles. The larger periodicities are different in respective cycles.

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