scholarly journals Monitoring Urban Sprawl Using Time-Series Data: Famagusta Region of Northern Cyprus

SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110074
Author(s):  
Kamyar Fuladlu ◽  
Müge Riza ◽  
Mustafa Ilkan
Keyword(s):  
Time Series ◽  
Urban Sprawl ◽  
Census Data ◽  
Time Series Data ◽  
Developed Countries ◽  
Geographical Information ◽  
Series Data ◽  
Great Success ◽  
European Cities ◽  
Northern Cyprus

Monitoring urban sprawl is a controversial topic among scholars. Many studies have tried to employ various methods for monitoring urban sprawl in cases of North American and Northern and Western European cities. Although numerous methods have been applied with great success in various developed countries, they are predominantly impractical for cases of developing Mediterranean European cities that lack reliable census data. Besides, the complexity of the methods made them difficult to perform in underfunded situations. Therefore, this study aims to develop a new multidimensional method that researchers and planners can apply readily in developing Mediterranean European cities. The new method was tested in the Famagusta region of Northern Cyprus, which has been experiencing unplanned growth for the past half-century. In support of this proposal, a detailed review of the existing literature is presented with an emphasis on urban sprawl characteristics. Four characteristics were chosen to monitor urban sprawl’s development in the Famagusta region. The method was structured based on a time-series (2001, 2006, 2011, and 2016) dataset that used remote sensing data and geographical information systems to monitor the urban sprawl. Based on the findings, the Famagusta region experienced rapid growth during the last 15 years. The lack of a masterplan resulted in the uncontrolled expansion of the city in the exurban areas. The development configuration was polycentric and linear in form with single-use composition. Together, the expansion and configuration manifested as more built-up area, scattered development, and increased automobile dependency.

scholarly journals Relationship between Corruption and FDI Inflow: A Causality Test

2019 ◽  
Vol 11 (1) ◽  
pp. 93-99
Author(s):  
Abdelhamid A. Mahboub ◽  
Hatem Hassan Garamon
Keyword(s):  
Time Series ◽  
Foreign Direct Investment ◽  
Direct Investment ◽  
Time Series Data ◽  
Developed Countries ◽  
Series Data ◽  
Strong Impact ◽  
Causality Test ◽  
The Developed Countries ◽  
The Impact

This study examines the relationship between the inflow of foreign direct investment and corruption. By using 2006 – 2015 time series data from 19 developed countries and 18 developing countries, it starts by testing the Granger causality between these two variables. It finds that causality direction goes from corruption to foreign direct investment. After making the time series data stationary, the study runs regression analysis for each country group separately. Significant and strong impact of corruption on foreign direct investment is found for each group, and the impact is even stronger for the developed countries. Data from each group could not support the hypothesis of ‘greasing the wheels of business’, which is used for justifying soft treatment of corruption in some countries. Policy implication is to stand strong against corruption in order to promote the inflow of foreign direct investment.

scholarly journals Workers' Remittances and Growth Linkages in Pakistan

2016 ◽  
Vol 2 (2) ◽  
pp. 81-92
Author(s):  
Fouzia Yasmin ◽  
Muhammad Zahir Faridi ◽  
Hina Ali ◽  
Adnan Yasin
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Developed Countries ◽  
Least Square ◽  
Series Data ◽  
Estimation Technique ◽  
Least Square Estimation ◽  
Ordinary Least Square ◽  
The Right

Remittances are considered as the cash inflows to the economy and are imperative international source of revenue for most of the less developed countries (LDCs). For data analysis, the Ordinary least square estimation technique was employed to the time series data for the years 1981 to 2010. This research comes with the conclusion that level of GDP is positively associated with the worker's remittances and the findings also support the optimistic view of remittances. It is suggested that govt. should take serious steps and proper measures to utilize the workers' remittances so, that the economy will be on the right track towards the development.  

scholarly journals Computational algorithms for predictive health assessments

2015 ◽  
Author(s):  
◽  
Zahra Hajihashemi
Keyword(s):  
Older Adults ◽  
Health Care ◽  
Time Series ◽  
Health Care Providers ◽  
Elderly Population ◽  
Time Series Data ◽  
The Elderly ◽  
Developed Countries ◽  
Series Data ◽  
Care Providers

Rapid aging of the population in the US requires increased attention from health care providers and from the entire society as a whole. While the elderly population (aged over 65) will increase by 8% until 2050 in the developed countries, the working-age population (age between 15 and 64 years) will decrease and its ratio to the elderly population will decline from 4.3 to 2.3. A possible solution to prevent unreported health problems in independently living older adults is through automatic health monitoring systems. The aim of this dissertation is to use sensor network technology to detect changes in health status of elderly living alone, alert health care providers, and augment traditional health care. In this dissertation, we address three topics. First, we discuss the problem of measuring the temporal similarity of two multidimensional time series. The second topic of this work is predicting health patterns using time series similarities. Third, we also propose three methods for identification of deviations in patterns of activities of daily livings (ADL) of older adults and use them to generate alerts for the healthcare providers. ADLs such as bathroom visits can be monitored by automated in-home sensor systems. Our proposed methods find periodicity in sensor time series data using clustering, item set mining, and statistical approaches.

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Exploratory Data

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

2017 ◽  
Vol 1 (2) ◽  
pp. 177-191
Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
The United States ◽  
Economic Conditions ◽  
Series Data ◽  
Arch Model ◽  
United States Dollar ◽  
The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Detection Method ◽  
Series Data

The Comparison of Land Subsidence between East and West Side of Bangkok, Thailand

2020 ◽  
Vol 17 (3) ◽  
pp. 1
Author(s):  
Angkana Pumpuang ◽  
Anuphao Aobpaet
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Time Series Data ◽  
Series Data ◽  
Industrial Estates ◽  
Vertical Displacements ◽  
Land Deformation ◽  
Extensive Farming ◽  
Chao Phraya River ◽  
Set Up

The land deformation in line of sight (LOS) direction can be measured using time series InSAR. InSAR can successfully measure land subsidence based on LOS in many big cities, including the eastern and western regions of Bangkok which is separated by Chao Phraya River. There are differences in prosperity between both sides due to human activities, land use, and land cover. This study focuses on the land subsidence difference between the western and eastern regions of Bangkok and the most possible cause affecting the land subsidence rates. The Radarsat-2 single look complex (SLC) was used to set up the time series data for long term monitoring. To generate interferograms, StaMPS for Time Series InSAR processing was applied by using the PSI algorithm in DORIS software. It was found that the subsidence was more to the eastern regions of Bangkok where the vertical displacements were +0.461 millimetres and -0.919 millimetres on the western and the eastern side respectively. The districts of Nong Chok, Lat Krabang, and Khlong Samwa have the most extensive farming area in eastern Bangkok. Besides, there were also three major industrial estates located in eastern Bangkok like Lat Krabang, Anya Thani and Bang Chan Industrial Estate. By the assumption of water demand, there were forty-eight wells and three wells found in the eastern and western part respectively. The number of groundwater wells shows that eastern Bangkok has the demand for water over the west, and the pumping of groundwater is a significant factor that causes land subsidence in the area.Keywords: Subsidence, InSAR, Radarsat-2, Bangkok

Sign in / Sign up

Export Citation Format

Share Document