scholarly journals The Interannual Calibration and Global Nighttime Light Fluctuation Assessment Based on Pixel-Level Linear Regression Analysis

2019 ◽  
Vol 11 (18) ◽  
pp. 2185 ◽  
Author(s):  
Zheng ◽  
Yang ◽  
Chen ◽  
Wu ◽  
Marinello
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Intensity Change ◽  
Calibration Model ◽  
Visible Radiation ◽  
Calibration Process ◽  
Nighttime Light ◽  
Normalized Difference Index

The Operational Linescan System (OLS) carried by the National Defense Meteorological Satellite Program (DMSP) can capture the weak visible radiation emitted from earth at night and produce a series of annual cloudless nighttime light (NTL) images, effectively supporting multi-scale, long-term human activities and urbanization process research. However, the interannual instability and sensor bias of NTL time series products greatly limit further studies of lighting data in time series with OLS. Several calibration models for OLS have been proposed to implement interannual corrections to improve the continuity and consistency of time series NTL products; however, due to the subjective factors intervention and insufficient automation in the calibration process, the interannual correction study of NTL time series images is still worth being developed further. Therefore, to avoid the involvement of subjective factors and to optimize the Pseudo-Invariant Features (PIF) identification, an interannual calibration model Pixel-based PIF (PBPIF) is proposed, which identifies PIF by pixel fluctuation characteristics. Results show that a PBPIF-based model can reduce subjective interference and improve the degree of automation during the NTL interannual calibration process. The calibration performance evaluation based on Total Sum of Lights (TSOL) and Sum of the Normalized Difference Index (SNDI) shows that compared to the traditional PIF-based (tPIF-based) and Ridgeline Sampling Regression based (RSR-based) models, the PBPIF-based one achieves better performance in reducing NTL interannual turbulence and minimizing the deviation between sensors. In addition, based on the corrected NTL time series products, pixel-level linear regression analysis is implemented to maximize the potential of the NTL resolution to produce global Light Intensity Change Coefficient (LICC). The results of global LICC can be widely applied to the detailed study of the characteristics of economic development and urbanization.

scholarly journals THE COMPARISON OF TWO PRECIPITATION PREDICTION METHODS

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 1025-1032
Author(s):  
X. Q. Mo ◽  
G. W. Lan ◽  
Y. L. Du ◽  
Z. X. Chen
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Time Series Analysis ◽  
Daily Precipitation ◽  
Linear Regression Analysis ◽  
Time Series Model ◽  
Residual Error ◽  
Actual Situation ◽  
Monthly Average

Abstract. Precipitation forecasts play the role in flood control and drought relief. At present, the time series analysis and the linear regression analysis are two of most commonly used methods. The time series analysis is relatively simple as it only requires historical precipitation data. The model of the linear regression analysis can ensure high accuracy for causality analysis and short, medium and long-term prediction. Guilin is the region of the heavy rain center in Guangxi, which frequently suffers serious losses from rainstorms. Selecting a better model to predict precipitation has the important reference significance for improving the accuracy of precipitation weather forecast. In this research, the two methods are used to predict precipitation in Guilin. According to data of the monthly maximum precipitation, monthly average daily precipitation and monthly total precipitation from 2014 to 2016, this paper establishes the time series model and linear regression analysis model to predict precipitation in 2017 and compare the forecast results. The results show that the monthly average daily precipitation model is best with the accuracy of the time series model, and the residual error of predicted precipitation is 3.08 mm, but the change trend of predicted precipitation is not accord with the actual situation. The residual error is only 0.45 mm through using inter-annual linear regression equation to predict the precipitation, but the predicted summer precipitation is quite different from the actual one. The linear equation established by different seasons is used to predict the precipitation with residual error of 3.25 mm, and it is coincident for the predicted precipitation trend with the actual situation. Furthermore, the predictions fitting errors of spring, summer, autumn and winter are all less than 20%, which are within the scope of the specification prediction error.

scholarly journals Pengaruh Pertumbuhan Ekonomi, Tingkat Inflasi, dan Pertumbuhan Penduduk terhadap Tingkat Pengangguran Terbuka di Indonesia

2019 ◽  
Vol 18 (1) ◽  
pp. 52
Author(s):  
Irma Yuni Astuti ◽  
Nanik Istiyani ◽  
Lilis Yuliati
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Population Growth ◽  
Multiple Linear Regression ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Series Data

This study aims to determine the effect of economic growth, inflation and population growth in open unemployment rate in Indonesia. The type of data used in this study is secondary data in the form of time series data and variable data used are annual data in the period 1986-2017 with the object of research in the country o Indonesia. The data sources used in this study were obtained from the Central Statistics Agency (BPS) Indonesia and World Bank. The analytical method used in this study is multiple linear regression analysis with the Ordinary Least Square (OLS) technique. The estimation of time series data with multiple linear regression analysis shows that the economics growth variable has a positive and not significant effect on the level of open unemployment, the inflation variable has a positive and not significant effect on the level of open unemployment, and the population growth variable has a negative and significant effect on the level of open unemployment in Indonesia. Keywords: Open Unemployment, Economic Growth, Inflation, Population Growth

scholarly journals Trend Analysis of Red Chili Price-Formation Models

2020 ◽  
Vol 40 (1) ◽  
pp. 57
Author(s):  
Siti Mir'atul Khasanah ◽  
Mochammad Maksum ◽  
Endy Suwondo
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Production Cost ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Price Formation ◽  
Changing Trends ◽  
Continuous Demand

Red chili’s characteristic flavor has been a popular element in Indonesian cuisine. A large and continuous demand for red chili is inconsistent with production volumes, causing frequent and extreme price fluctuations throughout the year. This study explores the changing trends in red chili prices to identify the influencing factors. The study was conducted in the Sleman district of Yogyakarta, Indonesia. Time-series datasets of monthly production rates and prices of chili for 3 years were subject to multiple linear regression analysis. The study found a rising trend in prices in the Sleman Regency from January 2014 to December 2016. The factors significantly influencing the red chili prices was the price of cayenne pepper. The production cost of chili, the price of tomatoes, and the price of chili for the previous 2 months had only partial and nonsignificant effects. The timing of great Muslim celebrations, such as Eid Al-Fitr and Eid Al-Adha had no significant effect on the price of red chili. However, Christmas and New Year events were associated with higher prices.

scholarly journals Faktor - faktor yang yang mempengaruhi produksi kerajinan batik di Kota Jambi

2020 ◽  
Vol 9 (3) ◽  
pp. 131-140
Author(s):  
Andrian Dwi Ramadan ◽  
Rahma Nurjanah ◽  
Erni Achmad
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Data Collection ◽  
Quantitative Data ◽  
Linear Regression Analysis ◽  
Secondary Data ◽  
Multiple Linear Regression Analysis ◽  
Business Units ◽  
Collection Methods

This study aims to determine the development of labor, investment and business units in the production of the batik industry in Jambi City. This research uses quantitative data collection methods. The data used in this study is secondary data, secondary data used is a combination of periodic series (time series). In this study, it is assumed that labor, investment, and business units have a positive and significant effect on Jambi batik production in Jambi City. The data used in this study are data on labor, investment, business units, and batik production in Jambi City from 2006-2017. The data is processed using SPSS with multiple linear regression analysis methods. Keywords: Labor, Investment, Business units, Production.

scholarly journals Peran Kepemilikan Asing, Leverage dan Profitabilitas Terhadap Pengungkapan Coorporate Social Responsibility Perusahaan

2020 ◽  
Vol 4 (1) ◽  
pp. 154
Author(s):  
Amilia Paramita Sari
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Social Responsibility ◽  
Multiple Linear Regression ◽  
Significant Influence ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Foreign Ownership ◽  
Manufacturing Company

This research seeks to verify and explain the role foreign ownership, leverage, and profitability to Disclosure of Coorporate Social Responsibility. While the method used is a method of multiple linear regression analysis. The data used in this study is time series period from January 2014 to December 2018. Studies find that simultaneously shows a significant effect about 31% foreign ownership, leverage, and profitability impact on the disclosure of coorporate social responsibility to manufacturing company in Bursa Efek Indonesia. It was found that a significant effect on disclosure of coorporate social responsibility is foreign ownership and leverage, whereas profitability has no significant influence. 

scholarly journals ANALISIS PENGARUH KUALITAS SUMBER DAYA MANUSIA TERHADAP PERTUMBUHAN EKONOMI SUMATERA BARAT

2013 ◽  
Vol 2 (2) ◽  
pp. 145
Author(s):  
Dewi Zaini Putri ◽  
Melti Roza Adry
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Regression Analysis ◽  
Data Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Health Index ◽  
Education And Health ◽  
Analysis Technique ◽  
Growth Types

The purposes of this research are to analyze the effect of (1) education index to economic growth, and (2) health index to economic growth. Types of research are descriptive and associative that show how exogen variable (X) effect endogenous variable (Y). Type of data is polled time series that combination of data or combinatioan from 19 regency/district in west Sumatera during 4 years and amount of data is 76 (n>30). Data analysis technique is linear regression analysis. Based on research that (1) education index has significant effect and poistive to economic growth, and (2) health index has significant effect and negative to economic growth. Based on reseach and analysis, government should increase facilities and infrastructure for education and health services to improve human qualities and increase the economic growth.

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