scholarly journals Landsat Time Series Analysis of Vegetation Changes in Solar Energy Development Areas of the Lower Colorado Desert, Southern California

2016 ◽  
Vol 04 (02) ◽  
pp. 1-6 ◽  
Author(s):  
Christopher Potter
Keyword(s):  
Time Series ◽  
Solar Energy ◽  
Time Series Analysis ◽  
Southern California ◽  
Energy Development ◽  
Vegetation Changes ◽  
Series Analysis ◽  
Colorado Desert

scholarly journals Detection of Vegetation Cover Change in Renewable Energy Development Zones of Southern California Using MODIS NDVI Time Series Analysis, 2000 to 2018

Environments ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 40 ◽  
Author(s):  
Justin Nghiem ◽  
Christopher Potter ◽  
Rebecca Baiman
Keyword(s):  
Time Series ◽  
Solar Energy ◽  
Vegetation Cover ◽  
National Park ◽  
Southern California ◽  
Statistical Significance ◽  
Energy Development ◽  
Vegetation Response ◽  
Human Disturbances ◽  
Significant Difference

New solar energy facilities on public lands in the deserts of southern California are being monitored long-term to detect environmental impacts. For this purpose, we have developed a framework for detecting changes in vegetation cover region-wide using greenness index data sets from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor. This study focused on three sites, Joshua Tree National Park (JOTR), Mojave National Preserve (MOJA), and a proximal group of solar energy Development Focus Areas (DFAs). Three MODIS vegetation indices (VIs), the normalized difference (NDVI), enhanced (EVI), and soil-adjusted (SAVI), all at 250-m spatial resolution, were evaluated using the Breaks for Additive Season and Trend (BFAST) methodology to estimate significant time series shifts (“breakpoints”) in green vegetation cover, from February 2000 to May 2018. The sample cross-correlation function with local precipitation records and comparison with timing of wildfires near the study sites for breakpoint density (proportion of area with a breakpoint) showed that NDVI had the strongest response and hence greatest sensitivity to these major disturbances compared to EVI and SAVI, supporting its use over the other VIs for subsequent analysis. Time series of NDVI breakpoint change densities for individual solar energy DFAs did not have a consistent vegetation response following construction. Bootstrap-derived 95% confidence intervals show that the DFAs have significantly larger kurtosis and standard deviation in positive NDVI breakpoint distribution than protected National Park System (NPS) sites, but no significant difference appeared in the negative distribution among all sites. The inconsistent postconstruction NDVI signal and the large number of detected breakpoints across all three sites suggested that the largest shifts in greenness are tied to seasonal and total annual precipitation amounts. Further results indicated that existing site-specific conditions are the main control on vegetation response, mostly driven by the history of human disturbances in DFAs. Although the results do not support persistent breakpoints in solar energy DFAs, future work should seek to establish links between statistical significance and physical significance through ground-based studies to provide a more robust interpretation.

scholarly journals Landsat time series analysis of fractional plant cover changes on abandoned energy development sites

2018 ◽  
Vol 73 ◽  
pp. 407-419 ◽  
Author(s):  
Eric K. Waller ◽  
Miguel L. Villarreal ◽  
Travis B. Poitras ◽  
Travis W. Nauman ◽  
Michael C. Duniway
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Plant Cover ◽  
Energy Development ◽  
Series Analysis

Dynamical Peculiarities of Concatenational Changes in Functional Cardiovascular Parameters

2018 ◽  
Vol 3 (82) ◽  
Author(s):  
Eurelija Venskaitytė ◽  
Jonas Poderys ◽  
Tadas Česnaitis
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Functional State ◽  
The Body ◽  
Functional Changes ◽  
High Intensity Training ◽  
Series Analysis ◽  
Greco Roman ◽  
St Segment ◽  
Standard Lead

Research  background  and  hypothesis.  Traditional  time  series  analysis  techniques,  which  are  also  used  for the analysis of cardiovascular signals, do not reveal the relationship between the  changes in the indices recorded associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-term structural and functional changes.Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval and amplitude of ST segment taken from the V standard lead.Research  results.  Significant  differences  were  found  between  inter-parametric  connections  of  ST  segment amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate of the myocardium and reflected in the dynamics of all investigated interactions.Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions show the exposure of the  functional changes in the body at the onset of the workload. The alterations of the functional state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation of the interactions of physiological signals by using time series analysis methods is suitable for the observation of these processes and the functional state of the body.Keywords: electrocardiogram, time series, functional state.

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