scholarly journals Analysis of Trends in the FireCCI Global Long Term Burned Area Product (1982–2018)

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 74
Author(s):  
Gonzalo Otón ◽  
José Miguel C. Pereira ◽  
João M. N. Silva ◽  
Emilio Chuvieco
Keyword(s):  
Time Series ◽  
Temporal Trends ◽  
European Space Agency ◽  
Eastern Africa ◽  
Burned Area ◽  
Data Series ◽  
Short Term ◽  
The Impact ◽  
Term Data

We present an analysis of the spatio-temporal trends derived from long-term burned area (BA) data series. Two global BA products were included in our analysis, the FireCCI51 (2001–2019) and the FireCCILT11 (1982–2018) datasets. The former was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m reflectance data, guided by 1 km active fires. The FireCCILT11 dataset was generated from Land Long-Term Data Record data (0.05°), which provides a consistent time series for Advanced Very High Resolution Radiometer images, acquired from the NOAA satellite series. FireCCILT11 is the longest time series of a BA product currently available, making it possible to carry out temporal analysis of long-term trends. Both products were developed under the FireCCI project of the European Space Agency. The two datasets were pre-processed to correct for temporal autocorrelation. Unburnable areas were removed and the lack of the FireCCILT11 data in 1994 was examined to evaluate the impact of this gap on the BA trends. An analysis and comparison between the two BA products was performed using a contextual approach. Results of the contextual Mann-Kendall analysis identified significant trends in both datasets, with very different regional values. The long-term series presented larger clusters than the short-term ones. Africa displayed significant decreasing trends in the short-term, and increasing trends in the long-term data series, except in the east. In the long-term series, Eastern Africa, boreal regions, Central Asia and South Australia showed large BA decrease clusters, and Western and Central Africa, South America, USA and North Australia presented BA increase clusters.

scholarly journals Estimation of Burned Area in the Northeastern Siberian Boreal Forest from a Long-Term Data Record (LTDR) 1982–2015 Time Series

2018 ◽  
Vol 10 (6) ◽  
pp. 940 ◽  
Author(s):  
José García-Lázaro ◽  
José Moreno-Ruiz ◽  
David Riaño ◽  
Manuel Arbelo
Keyword(s):  
Time Series ◽  
Boreal Forest ◽  
Burned Area ◽  
Data Record ◽  
Term Data

scholarly journals The impact of burning on lion Panthera leo habitat choice in an African savanna

2013 ◽  
Vol 59 (3) ◽  
pp. 335-339 ◽  
Author(s):  
Stephanie Eby ◽  
Anna Mosser ◽  
Ali Swanson ◽  
Craig Packer ◽  
Mark Ritchie
Keyword(s):  
National Park ◽  
Habitat Choice ◽  
Territory Size ◽  
Short Term ◽  
Data Set ◽  
Burned Areas ◽  
The Impact ◽  
Term Data ◽  
Prey Attraction

Abstract Carnivores play a central role in ecosystem processes by exerting top-down control, while fire exerts bottom-up control in ecosystems throughout the world, yet, little is known about how fire affects short-term carnivore distributions across the landscape. Through the use of a long-term data set we investigated the distribution of lions, during the daytime, in relation to burned areas in Serengeti National Park, Tanzania. We found that lions avoid burned areas despite the fact that herbivores, their prey, are attracted to burned areas. Prey attraction, however, likely results from the reduction in cover caused by burning, that may thereby decrease lion hunting success. Lions also do not preferentially utilize the edges of burned areas over unburned areas despite the possibility that edges would combine the benefit of cover with proximity to abundant prey. Despite the fact that lions avoid burned areas, lion territory size and reproductive success were not affected by the proportion of the territory burned each year. Therefore, burning does not seem to reduce lion fitness perhaps because of the heterogeneity of burned areas across the landscape or because it is possible that when hunting at night lions visit burned areas despite their daytime avoidance of these areas.

Predicting Time Series from Short-Term High-Dimensional Data

2014 ◽  
Vol 24 (12) ◽  
pp. 1430033 ◽  
Author(s):  
Huanfei Ma ◽  
Tianshou Zhou ◽  
Kazuyuki Aihara ◽  
Luonan Chen
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
High Dimensional Data ◽  
Series Data ◽  
High Dimensional ◽  
Short Term ◽  
Low Dimensional ◽  
Low Dimensional Dynamics ◽  
Term Data

The prediction of future values of time series is a challenging task in many fields. In particular, making prediction based on short-term data is believed to be difficult. Here, we propose a method to predict systems' low-dimensional dynamics from high-dimensional but short-term data. Intuitively, it can be considered as a transformation from the inter-variable information of the observed high-dimensional data into the corresponding low-dimensional but long-term data, thereby equivalent to prediction of time series data. Technically, this method can be viewed as an inverse implementation of delayed embedding reconstruction. Both methods and algorithms are developed. To demonstrate the effectiveness of the theoretical result, benchmark examples and real-world problems from various fields are studied.

SUMBER-SUMBER RESILIENSI PADA REMAJA AKHIR YANG MENGALAMI KEKERASAN DARI ORANGTUA PADA MASA KANAK-KANAK

Psibernetika ◽  
2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Devina Calista ◽  
Garvin Garvin
Keyword(s):  
Late Adolescents ◽  
Long Term Effects ◽  
Short Term ◽  
Parental Affection ◽  
Resilience Factors ◽  
Childhood Violence ◽  
Past Experiences ◽  
The Impact ◽  
Depth Interviews

<p><em>Child abuse by parents is common in households. The impact of violence on children will bring short-term effects and long-term effects that can be attributed to their various emotional, behavioral and social problems in the future; especially in late adolescence that will enter adulthood. Resilience factors increase the likelihood that adolescents who are victims of childhood violence recover from their past experiences</em><em>,</em><em> become more powerful individuals and have a better life. The purpose of this study was to determine the source of resilience in late adolescents who experienced violence from parents in their childhood. This research uses qualitative research methods with in-depth interviews as a method of data collection. The result shows that the three research participants have the aspects of "I Have", "I Am", and "I Can"; a participant has "I Can" aspects as a source of resilience, and one other subject has no source of resilience. The study concluded that parental affection and acceptance of the past experience have role to the three sources of resilience (I Have, I Am, and I Can)</em></p><p><em> </em></p><p><strong><em>Keyword : </em></strong><em>Resilience, adolescence, violence, parents</em></p>

Diel, lunar and seasonal vertical migration in the deep western Gulf of Mexico evidenced from a long-term data series of acoustic backscatter

2021 ◽  
pp. 102562
Author(s):  
Laura Ursella ◽  
Sara Pensieri ◽  
Enric Pallàs-Sanz ◽  
Sharon Z. Herzka ◽  
Roberto Bozzano ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Vertical Migration ◽  
Acoustic Backscatter ◽  
Data Series ◽  
Term Data

Forecasting Revenue Impacts from COVID-19: The Case of Florida Municipalities

2021 ◽  
pp. 0160323X2110120
Author(s):  
Hai (David) Guo ◽  
Can Chen
Keyword(s):  
Local Government ◽  
Short Term ◽  
Fiscal Planning ◽  
Revenue Structure ◽  
Municipal Managers ◽  
The Impact

Early in the pandemic, Florida municipal managers indicated that forecasting the impact on local revenues was one of their top priorities in responding to the pandemic, yet such a tool has not been widely available. This study offers simple and straightforward fiscal planning guides for assessing the short-term and long-term impacts of the COVID 19 recession on local government revenues by estimating the revenue declines among 411 Florida municipalities from FY 2021 to FY 2023. The forecast results predict revenues will be reduced by $5.11 billion from 2019 pre-pandemic levels for Florida cities in fiscal years 2021 through 2023. The decline is forecast to be 3.54 percent in FY 2021, 4.02 percent in FY 2022, and 3.29 percent in FY 2023. The revenue structure matters for estimating the revenue decline.

scholarly journals Long-Term Data Traffic Forecasting for Network Dimensioning in LTE with Short Time Series

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1151
Author(s):  
Carolina Gijón ◽  
Matías Toril ◽  
Salvador Luna-Ramírez ◽  
María Luisa Marí-Altozano ◽  
José María Ruiz-Avilés
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Analysis ◽  
Data Traffic ◽  
Medium Term ◽  
Short Term ◽  
Traffic Forecasting ◽  
Series Analysis ◽  
Radio Planning

Network dimensioning is a critical task in current mobile networks, as any failure in this process leads to degraded user experience or unnecessary upgrades of network resources. For this purpose, radio planning tools often predict monthly busy-hour data traffic to detect capacity bottlenecks in advance. Supervised Learning (SL) arises as a promising solution to improve predictions obtained with legacy approaches. Previous works have shown that deep learning outperforms classical time series analysis when predicting data traffic in cellular networks in the short term (seconds/minutes) and medium term (hours/days) from long historical data series. However, long-term forecasting (several months horizon) performed in radio planning tools relies on short and noisy time series, thus requiring a separate analysis. In this work, we present the first study comparing SL and time series analysis approaches to predict monthly busy-hour data traffic on a cell basis in a live LTE network. To this end, an extensive dataset is collected, comprising data traffic per cell for a whole country during 30 months. The considered methods include Random Forest, different Neural Networks, Support Vector Regression, Seasonal Auto Regressive Integrated Moving Average and Additive Holt–Winters. Results show that SL models outperform time series approaches, while reducing data storage capacity requirements. More importantly, unlike in short-term and medium-term traffic forecasting, non-deep SL approaches are competitive with deep learning while being more computationally efficient.

scholarly journals Paleolithic Diet—Effect on the Health Status and Performance of Athletes?

Nutrients ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 1019
Author(s):  
Barbara Frączek ◽  
Aleksandra Pięta ◽  
Adrian Burda ◽  
Paulina Mazur-Kurach ◽  
Florentyna Tyrała
Keyword(s):  
Blood Pressure ◽  
Body Mass ◽  
Positive Impact ◽  
Model Assessment ◽  
Paleolithic Diet ◽  
Short Term ◽  
Positive Effects ◽  
Short And Long Term ◽  
The Impact

The aim of this meta-analysis was to review the impact of a Paleolithic diet (PD) on selected health indicators (body composition, lipid profile, blood pressure, and carbohydrate metabolism) in the short and long term of nutrition intervention in healthy and unhealthy adults. A systematic review of randomized controlled trials of 21 full-text original human studies was conducted. Both the PD and a variety of healthy diets (control diets (CDs)) caused reduction in anthropometric parameters, both in the short and long term. For many indicators, such as weight (body mass (BM)), body mass index (BMI), and waist circumference (WC), impact was stronger and especially found in the short term. All diets caused a decrease in total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG), albeit the impact of PD was stronger. Among long-term studies, only PD cased a decline in TC and LDL-C. Impact on blood pressure was observed mainly in the short term. PD caused a decrease in fasting plasma (fP) glucose, fP insulin, and homeostasis model assessment of insulin resistance (HOMA-IR) and glycated hemoglobin (HbA1c) in the short run, contrary to CD. In the long term, only PD caused a decrease in fP glucose and fP insulin. Lower positive impact of PD on performance was observed in the group without exercise. Positive effects of the PD on health and the lack of experiments among professional athletes require longer-term interventions to determine the effect of the Paleo diet on athletic performance.

scholarly journals Assessing Stream-Aquifer Connectivity in a Coastal California Watershed

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 416
Author(s):  
Bwalya Malama ◽  
Devin Pritchard-Peterson ◽  
John J. Jasbinsek ◽  
Christopher Surfleet
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Water Level ◽  
Time Series Data ◽  
Series Data ◽  
Low Permeability ◽  
Pumping Tests ◽  
Stream Flows ◽  
The Impact

We report the results of field and laboratory investigations of stream-aquifer interactions in a watershed along the California coast to assess the impact of groundwater pumping for irrigation on stream flows. The methods used include subsurface sediment sampling using direct-push drilling, laboratory permeability and particle size analyses of sediment, piezometer installation and instrumentation, stream discharge and stage monitoring, pumping tests for aquifer characterization, resistivity surveys, and long-term passive monitoring of stream stage and groundwater levels. Spectral analysis of long-term water level data was used to assess correlation between stream and groundwater level time series data. The investigations revealed the presence of a thin low permeability silt-clay aquitard unit between the main aquifer and the stream. This suggested a three layer conceptual model of the subsurface comprising unconfined and confined aquifers separated by an aquitard layer. This was broadly confirmed by resistivity surveys and pumping tests, the latter of which indicated the occurrence of leakage across the aquitard. The aquitard was determined to be 2–3 orders of magnitude less permeable than the aquifer, which is indicative of weak stream-aquifer connectivity and was confirmed by spectral analysis of stream-aquifer water level time series. The results illustrate the importance of site-specific investigations and suggest that even in systems where the stream is not in direct hydraulic contact with the producing aquifer, long-term stream depletion can occur due to leakage across low permeability units. This has implications for management of stream flows, groundwater abstraction, and water resources management during prolonged periods of drought.

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