scholarly journals Spatial variation characteristics of vegetation phenology and its influencing factors in the subtropical monsoon climate region of southern China

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250825
Author(s):  
Huanhua Peng ◽  
Haonan Xia ◽  
Hao Chen ◽  
Panding Zhi ◽  
Zhonglin Xu
Keyword(s):  
Influencing Factors ◽  
Climatic Factors ◽  
Series Data ◽  
Vegetation Phenology ◽  
Monsoon Climate ◽  
Growth Season ◽  
Xiangjiang River ◽  
Modis Evi ◽  
Subtropical Monsoon Climate ◽  
The Impact

Understanding the response mechanism of ecosystems to climate change and human disturbance can be improved by analyzing the spatial patterns of vegetation phenology and its influencing factors. Because the diverse phenological patterns are impacted by cloud cover contamination issues in the satellite observations, there are few remote sensing phenological research data in subtropical monsoon climate regions. To better understand the horizontal and vertical changes of vegetation phenology in these regions and how it may be affected by climatic factors and topographical features, we first extracted vegetation phenological information (such as start of growth season (SOS), end of growth season (EOS) and length of growth season (LEN)) from a reconstructed MODIS EVI time-series data. We then used geographic detectors to identify the influencing factors of phenology in different elevation zoning areas. We have found that in the Xiangjiang River Basin: 1) gradual changes in the longitudinal or latitudinal gradient of vegetation phenology were not obvious. Instead of horizontal changes, the variation pattern of phenology was similar to the striped river network of the Xiangjiang River. Earlier SOS mainly appeared in the areas far away from the river; later SOS appeared in the midstream and downstream reaches.2) Elevation played an important role in the regional differentiation of phenology. Boundaries at elevations of 320 m and 520 m distinctly separated the region into plain, hilly, and mountain vegetation phenological characteristics. 3) The impacts of climatic factors were quite different in the three vertical zoning areas. Precipitation was the most crucial factor affecting SOS both in plain and mountain areas. There was no significant factor affecting EOS in the plain area, but temperature had an essential effect on EOS in the mountain area. The hilly areas had a concentrated growth period with no significant factors affecting phenology. These findings highlight the importance of elevation in phenology at a watershed scale, enhance our understanding of the impact of climate changes on subtropical ecosystems, and provide a reference for further land-use change monitoring.

scholarly journals Analysis of Natural Streamflow Variation and Its Influential Factors on the Yellow River from 1957 to 2010

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1155 ◽  
Author(s):  
Jie Wu ◽  
Zhihui Wang ◽  
Zengchuan Dong ◽  
Qiuhong Tang ◽  
Xizhi Lv ◽  
...  
Keyword(s):  
Yellow River ◽  
Climatic Factors ◽  
Influential Factors ◽  
Annual Precipitation ◽  
Series Data ◽  
The Yellow River ◽  
Annual Streamflow ◽  
Flood Season ◽  
Precipitation Decrease ◽  
The Impact

In this study, variation characteristics of hydrometeorological factors were explored based on observed time-series data between 1957 and 2010 in four subregions of the Yellow River Basin. For each region, precipitation–streamflow models at annual and flood-season scales were developed to quantify the impact of annual precipitation, temperature, percentage of flood-season precipitation, and anthropogenic interference. The sensitivities of annual streamflow to these three climatic factors were then calculated using a modified elasticity coefficient model. The results presented the following: (1) Annual streamflow exhibited a negative trend in all regions; (2) The reduction of annual streamflow was mainly caused by a precipitation decrease and temperature increase for all regions before 2000, whereas the contribution of anthropogenic interference increased significantly—more than 45%, except for Tang-Tou region after 2000. The percentage of flood-season precipitation variation can also be responsible for annual streamflow reduction with a range of 7.36% (Tang-Tou) to 21.88% (Source); (3) Annual streamflow was more sensitive to annual precipitation than temperature in the humid region, and the opposite situation was observed in the arid region. The sensitivities to intra-annual climate variation increased after 2000 for all regions, and the increase was more significant in Tou-Long and Long-Hua regions.

scholarly journals Modeling the Impact of Climate and Non-Climatic Factors on Cereal Production: Evidence from Indian Agriculture

2021 ◽  
Author(s):  
Abbas Ali Chandio ◽  
Yuansheg Jiang ◽  
Asad Amin ◽  
Waqar Akram ◽  
Ilhan Ozturk ◽  
...  
Keyword(s):  
Labor Force ◽  
Financial Development ◽  
Time Series Data ◽  
Climatic Factors ◽  
Series Data ◽  
Causality Test ◽  
Indian Agriculture ◽  
Long Run ◽  
Cereal Production ◽  
The Impact

Abstract The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965–2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise granger causality test confirmed that both climatic and non-climatc factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals.

scholarly journals COVID-19 and The Impact of Climatic Parameters: A Case Study of Bangladesh

2021 ◽  
Author(s):  
Rehana Parvin
Keyword(s):  
Wind Speed ◽  
Correlation Coefficient ◽  
Climatic Factors ◽  
Climatic Variables ◽  
Series Data ◽  
Climatic Parameters ◽  
Pm 2.5 ◽  
Lagged Effects ◽  
The Impact ◽  
The Relationship

Abstract This study examines the relationship between climatic factors and the prevalence of COVID-19 in Bangladesh. Pearson correlation coefficient, Spearman correlation coefficient, and Kendall's correlation coefficient have all been put to use to assess the intensity and direction of the relationship between climatic factors and COVID-19. The lagged effects of climatic parameters on COVID-19 daily-confirmed cases from Bangladesh are being looked into using the Auto Regressive Distributed Lag (ARDL) model. As a result, two non-climatic variables, such as population density and the human development index, are taken into account as control variables. As climatic variables, average temperature (°C), average humidity (percent), average PM 2.5, and average wind speed (km/h) were well chosen. The time series data used in this analysis was from May 1, 2020 to April 14, 2021. The findings of correlation analysis indicate that there is an important, significant, and positive relationship between COVID-19 widespread and temperature (°C), humidity (percent), and wind speed (km/h), whereas there is a negative, weak, and significant relationship between PM 2.5 and COVID-19 widespread. In addition, the ARDL findings suggested that temperature (°C), PM 2.5, and wind speed (km/h) have major lagged effects on COVID-19 in Bangladesh, while humidity (percent) has negligible lagged effects. For policymakers and investors alike, the consequences of this study are important in Bangladesh.

scholarly journals Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

2018 ◽  
Vol 10 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Babatunde Adeniyi Osunmadewa ◽  
Worku Zewdie Gebrehiwot ◽  
Elmar Csaplovics ◽  
Olabinjo Clement Adeofun
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Time Series Data ◽  
Anthropogenic Activities ◽  
Phase 1 ◽  
Climatic Variability ◽  
Annual Rainfall ◽  
Series Data ◽  
Vegetation Phenology ◽  
The Impact

Abstract Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

Impact of exchange rate and oil price on the yield of sovereign bond and sukuk: Evidence from Malaysian capital market

2017 ◽  
Vol 5 (4) ◽  
pp. 27
Author(s):  
Huda Arshad ◽  
Ruhaini Muda ◽  
Ismah Osman
Keyword(s):  
Exchange Rate ◽  
Capital Market ◽  
Time Series Data ◽  
Oil Prices ◽  
Oil Price ◽  
Series Data ◽  
Sovereign Bond ◽  
Long Run ◽  
Short Run ◽  
The Impact

This study analyses the impact of exchange rate and oil prices on the yield of sovereign bond and sukuk for Malaysian capital market. This study aims to ascertain the effect of weakening Malaysian Ringgit and declining of crude oil price on the fixed income investors in the emerging capital market. This study utilises daily time series data of Malaysian exchange rate, oil price and the yield of Malaysian sovereign bond and sukuk from year 2006 until 2015. The findings show that the weakening of exchange rate and oil prices contribute different impacts in the short and long run. In the short run, the exchange rate and oil prices does not have a direct relation with the yield of sovereign bond and sukuk. However, in the long run, the result reveals that there is a significant relationship between exchange rate and oil prices on the yield of sovereign bond and sukuk. It is evident that only a unidirectional causality relation is present between exchange rate and oil price towards selected yield of Malaysian sovereign bond and sukuk. This study provides numerical and empirical insights on issues relating to capital market that supports public authorities and private institutions on their decision and policymaking process.

Transport infrastructure of the Rostov Oblast: Problems and prospects for development in the context of national projects implementation

2020 ◽  
Vol 19 (6) ◽  
pp. 1015-1034
Author(s):  
O.Yu. Patrakeeva
Keyword(s):  
Time Series Data ◽  
Mutual Influence ◽  
Rostov Oblast ◽  
Transport Infrastructure ◽  
Series Data ◽  
Cointegration Tests ◽  
Level Of Economic Development ◽  
Short Run ◽  
The Government ◽  
The Impact

Subject. The paper considers national projects in the field of transport infrastructure, i.e. Safe and High-quality Roads and Comprehensive Plan for Modernization and Expansion of Trunk Infrastructure, and the specifics of their implementation in the Rostov Oblast. Objectives. The aim is to conduct a statistical assessment of the impact of transport infrastructure on the region’s economic performance and define prospects for and risks of the implementation of national infrastructure projects in conditions of a shrinking economy. Methods. I use available statistics and apply methods and approaches with time-series data, namely stationarity and cointegration tests, vector autoregression models. Results. The level of economic development has an impact on transport infrastructure in the short run. However, the mutual influence has not been statistically confirmed. The paper revealed that investments in the sphere of transport reduce risk of accidents on the roads of the Rostov Oblast. Improving the quality of roads with high traffic flow by reducing investments in the maintenance of subsidiary roads enables to decrease accident rate on the whole. Conclusions. In conditions of economy shrinking caused by the complex epidemiological situation and measures aimed at minimizing the spread of coronavirus, it is crucial to create a solid foundation for further economic recovery. At the government level, it is decided to continue implementing national projects as significant tools for recovery growth.

Working conditions and occupational pathology of coal miners in the Arctic

2019 ◽  
pp. 452-457 ◽  
Author(s):  
S. A. Gorbanev ◽  
S. A. Syurin ◽  
N. M. Frolova
Keyword(s):  
Coal Mining ◽  
Working Conditions ◽  
Occupational Diseases ◽  
Climatic Factors ◽  
Coal Mines ◽  
The Arctic ◽  
Morbidity Rate ◽  
Coal Miners ◽  
Increased Risk ◽  
The Impact

Introduction. Due to the impact of adverse working conditions and climate, workers in coal-mining enterprises in the Arctic are at increased risk of occupational diseases (OD).The aim of the study was to study the working conditions, causes, structure and prevalence of occupational diseases in miners of coal mines in the Arctic.Materials and methods. Th e data of social and hygienic monitoring “Working conditions and occupational morbidity” of the population of Vorkuta and Chukotka Autonomous District in 2007–2017 are studied.Results. It was established that in 2007–2017 years, 2,296 ODs were diagnosed for the first time in 1851 coal mines, mainly in the drifters, clearing face miners, repairmen and machinists of mining excavating machines. Most often, the ODs occurred when exposed to the severity of labor, fibrogenic aerosols and hand-arm vibration. The development of professional pathology in 98% of cases was due to design flaws of machines and mechanisms, as well as imperfections of workplaces and technological processes. Diseases of the musculoskeletal system (36.2%), respiratory organs (28.9%) and nervous system (22.5%) prevailed in the structure of professional pathology of miners of coal mines. Among the three most common nosological forms of OD were radiculopathy (32.1%), chronic bronchitis (27.7%) and mono-polyneuropathy (15.4%). In 2017, coal miners in the Arctic had a professional morbidity rate of 2.82 times higher than the national rates for coal mining.Conclusions. To preserve the health of miners of coal mining enterprises, technical measures to improve working conditions and medical interventions aimed at increasing the body’s resistance to the effects of harmful production and climatic factors are necessary.

THE MODEL FOR MANAGING INVESTMENTS IN THE MOSCOW ENVIRONMENT BASED ON A POWER REGRESSION EQUATION

2020 ◽  
Vol 2 (7) ◽  
pp. 91-99
Author(s):  
E. V. KOSTYRIN ◽  
◽  
M. S. SINODSKAYA ◽  
Keyword(s):  
Solid Waste ◽  
Influencing Factors ◽  
Pair Correlation ◽  
Approximation Error ◽  
Regression Equation ◽  
Regression Equations ◽  
The Impact ◽  
The Relationship ◽  
Average Approximation ◽  
Average Approximation Error

The article analyzes the impact of certain factors on the volume of investments in the environment. Regression equations describing the relationship between the volume of investment in the environment and each of the influencing factors are constructed, the coefficients of the Pearson pair correlation between the dependent variable and the influencing factors, as well as pairwise between the influencing factors, are calculated. The average approximation error for each regression equation is determined. A correlation matrix is constructed and a conclusion is made. The developed econometric model is implemented in the program of separate collection of municipal solid waste (MSW) in Moscow. The efficiency of the model of investment management in the environment is evaluated on the example of the growth of planned investments in the activities of companies specializing in the export and processing of solid waste.

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