Evaluating the performance of LBSM data to estimate the gross domestic product of China at multiple scales: A comparison with NPP-VIIRS nighttime light data

2021 ◽  
pp. 129558
Author(s):  
Ziwei Huang ◽  
Shaoying Li ◽  
Feng Gao ◽  
Fang Wang ◽  
Jinyao Lin ◽  
...  
Author(s):  
Yizhen Wu ◽  
Mingyue Jiang ◽  
Zhijian Chang ◽  
Yuanqing Li ◽  
Kaifang Shi

Currently, whether the urban development in China satisfies Zipf’s law across different scales is still unclear. Thus, this study attempted to explore whether China’s urban development satisfies Zipf’s law across different scales from the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data. First, the NPP-VIIRS data were corrected. Then, based on the Zipf law model, the corrected NPP-VIIRS data were used to evaluate China’s urban development at multiple scales. The results showed that the corrected NPP-VIIRS data could effectively reflect the state of urban development in China. Additionally, the Zipf index (q) values, which could express the degree of urban development, decreased from 2012 to 2018 overall in all provinces, prefectures, and counties. Since the value of q was relatively close to 1 with an R2 value > 0.70, the development of the provinces and prefectures was close to the ideal Zipf’s law state. In all counties, q > 1 with an R2 value > 0.70, which showed that the primate county had a relatively stronger monopoly capacity. When the value of q < 1 with a continuous declination in the top 2000 counties, the top 250 prefectures, and the top 20 provinces in equilibrium, there was little difference in the scale of development at the multiscale level with an R2 > 0.90. The results enriched our understanding of urban development in terms of Zipf’s law and had valuable implications for relevant decision-makers and stakeholders.


Author(s):  
Agnė JOTAUTAITĖ ◽  
Eglė JOTAUTIENĖ

In this paper, export opportunities of textile products from Turkey to Lithuania are analyzed. The main goal of this article is to present an analysis of the opportunities to import textile products from Turkey to Lithuania. The empirical research basing on the statistical database analysis was used. The analysis of Turkey’s markets was showed that the economy is strongly dependent on exports of various products from Turkey and it is about one forth of Turkey’s GDP (Gross Domestic Product). The bulk of exports from Turkey is t o countries in the European Union. Turkey is one of the world’s largest manufacturers and exporters of textiles. The analysis of Lithuanian markets was indicated that Lithuania has a feasible market for imports due to its fast growing GDP, increasing labor wages and modernization of agriculture industry. Furthermore, advantageous and adequate policies of Lithuania’s foreign trade should encourage the development of imports to this country. The demand for textile products in Lithuania is growing rapidly and it is one of the most important sectors in fostering its economy


2016 ◽  
Vol 21 (1) ◽  
pp. 9-20
Author(s):  
Ersalina Tang

The purpose of this study is to analyze the impact of Foreign Direct Investment, Gross Domestic Product, Energy Consumption, Electric Consumption, and Meat Consumption on CO2 emissions of 41 countries in the world using panel data from 1999 to 2013. After analyzing 41 countries in the world data, furthermore 17 countries in Asia was analyzed with the same period. This study utilized quantitative approach with Ordinary Least Square (OLS) regression method. The results of 41 countries in the world data indicates that Foreign Direct Investment, Gross Domestic Product, Energy Consumption, and Meat Consumption significantlyaffect Environmental Qualities which measured by CO2 emissions. Whilst the results of 17 countries in Asia data implies that Foreign Direct Investment, Energy Consumption, and Electric Consumption significantlyaffect Environmental Qualities. However, Gross Domestic Product and Meat Consumption does not affect Environmental Qualities.


2017 ◽  
Vol 21 (2) ◽  
pp. 85-95
Author(s):  
John Marcell Rumondor

This research aims to understand the influenceof foreign investment, international trade, Gross Domestic Product per capita, agriculture and urbanization of the working population. Country used as an object in this research is Indonesia. This research uses the method of analysis Ordinary Least Square (OLS) and the multiple linear regression analysis method. Research period are from 1997 – 2012. The results showed that the international trade, Gross Domestic Product per capita, agriculture and urbanization have significantpositive influenceon the population work in Indonesia, but foreign investment has no significanteffect on the working population in Indonesia.


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