scholarly journals Iterative Cellular Automation Approach to Analyze Spatial Dynamics of Urbanization and Population Growth

2021 ◽  
Vol 30 (5) ◽  
pp. 4621-4632
Author(s):  
Urooj Saeed ◽  
Sajid Ahmad
Keyword(s):  
Population Growth ◽  
Spatial Dynamics ◽  
Cellular Automation

scholarly journals Spatial Dynamics Model for Land Carrying Capacity Prediction in Tangerang Selatan City

2019 ◽  
Vol 125 ◽  
pp. 01006
Author(s):  
Rizky Lamonda ◽  
Supriatna ◽  
Revi Hernina ◽  
Masita Dwi Mandini Manessa ◽  
Yoanna Ristya
Keyword(s):  
Population Growth ◽  
Carrying Capacity ◽  
Spatial Dynamics ◽  
Population Data ◽  
Landsat 8 ◽  
Dynamics Model ◽  
Model Method ◽  
The Status ◽  
Land Carrying Capacity ◽  
The Relationship

Tangerang Selatan is a city with the highest economic and population growth in Banten Province which makes the built-up land have high and rapid growth so that it can reduce the land carrying capacity of the city. This causes the predictions on the land carrying capacity need to be done so that the status of land carrying capacity can be detected before declining. The aim of this study is to produce a spatial dynamics model of land carrying capacity in Tangerang Selatan City. This study uses population data of 2008-2018, Landsat 5 TM (2008) images, and Landsat 8 OLI images (2013 and 2018). The land carrying capacity is predicted from 2008-2100 using the system dynamics model method based on the relationship between land requirements based on population growth and land availability based on built-up land, which then converted to spatial to see the spatial distribution with spatial dynamics model method. Research shows that in 2026 the land carrying capacity in Tangerang Selatan City has reached 30% and in 2056 the land carrying capacity has been exhausted.

scholarly journals Spatial Dynamics Model of Land Availability and Population Growth Prediction in Bengkulu City

2020 ◽  
Vol 52 (3) ◽  
pp. 427
Author(s):  
Della Ayu Lestari ◽  
Dewi Susiloningtyas ◽  
Supriatna Supriatna
Keyword(s):  
Growth Rate ◽  
Population Growth ◽  
Carrying Capacity ◽  
Population Growth Rate ◽  
Spatial Dynamics ◽  
Distribution Patterns ◽  
High Population ◽  
Dynamics Model ◽  
Land Availability ◽  
High Population Growth

Bengkulu City is the center for almost all activities and has a high population growth rate. Because of the high population growth rate, human needs for space and land will increase. Land availability will continue to decline, while it cannot increase the existing area. This will impact the carrying capacity of the environment, so it needs predictions for land availability. This study used a spatial dynamics model which is an analysis of the dynamic system model and the suitability of the built-up area. The carrying capacity to reach excellent quality when the length of the built-up area is 30-70% of the total area that can be used. The results showed that the built-up area will reach 70% in 2030, which means it will exceed the environmental carrying capacity threshold. The results showed there were differences between the distribution patterns of built-up area in the spatial dynamics model and Spatial Planning Bengkulu City in 2032 at Kampung Melayu Subdistrict, Selebar Subdistrict, Singaran Pati Subdistrict, and Sungai Serut Subdistrict.

Sozial-räumliche Dynamiken der Agrartreibstoffe.

2016 ◽  
Vol 46 (184) ◽  
pp. 423-440 ◽  
Author(s):  
Kristina Dietz ◽  
Bettina Engels ◽  
Oliver Pye
Keyword(s):  
Political Economy ◽  
Capital Flows ◽  
Spatial Dynamics ◽  
Financial Sector ◽  
Comprehensive Analysis ◽  
Spatial Theory ◽  
Global Political Economy

This article explores the spatial dynamics of agrofuels. Building on categories from the field of critical spatial theory, it shows how these categories enable a comprehensive analysis of the spatial dynamics of agrofuels that links the macro-structures of the global political economy to concrete, place-based struggles. Four core socio-spatial dynamics of agrofuel politics are highlighted and applied to empirical findings: territorialization, the financial sector as a new scale of regulation, place-based struggles and transnational spaces of resources and capital flows.

İstanbul İlçelerinin Nüfus Değişimi ve Kütük Bilgilerinin Analizi

2019 ◽  
Vol 6 (1) ◽  
pp. 37-72
Author(s):  
Ulaş Sunata ◽  
Dila Ergül
Keyword(s):  
Population Growth ◽  
Population Growth Rate ◽  
Population Change ◽  
Urban Migration ◽  
Specific Population ◽  
Related Factors ◽  
Internal Migrant ◽  
Level Analysis ◽  
Study District ◽  
Demographic Features

39 ilçesiyle Türkiye’nin en büyük nüfusuna sahip ili İstanbul aynı zamanda Türkiye’nin en çok iç göç alan şehridir. Özellikle kırdan kente göç bağlamında sosyo-ekonomik ve demografik özellikleriyle birçok araştırmaya konu olmuştur. Fakat İstanbul yerleşik nüfusunun Türkiye’nin diğer şehirlerine kayıtlı olma yoğunluğu da önemlidir. Bu çalışmanın amacı 2012 ve 2017 yıllarındaki nüfus değişimini göz önünde bulundurarak İstanbul ilçelerinin ayrıntılı nüfus yoğunluğu ve büyüme analizini yapmak, ilgili faktörleri değerlendirmek, hemşehri ağlarını okumak adına yerleşik nüfus kütük bilgileri bakımından inceleyerek elde edilen örüntüler doğrultusunda ilçe tipolojileri oluşturmaktır. Çalışmanın birinci bölümünde ilgili beş yıllık nüfus değişimlerine göre İstanbul ilçe nüfusları analiz edilmiştir. Ardından her bir ilçe için nüfusa kayıtlı olunan kente göre nüfus büyüme hızlarına bakılarak ilçelerin ağırlıklı olarak barındırdığı hemşehri ağları belirlenmiştir. İkinci bölümde ise ilçeler nüfus değişim özelliklerine göre belirli kategorilere ayrılmış ve bu kategoriler doğrultusunda ilçe tipolojileri oluşturulmuştur..ABSTRACT IN ENGLISHA District Level Analysis of Istanbul’s Population Change (2012-2017)Istanbul having the largest population of Turkey with its 39 districts is the most internal-migrant-receiving city in Turkey. Particularly in the context of rural-to-urban migration, Istanbul has been became a subject of various researches with its socio-economic and demographic features. However, the density of Istanbul’s settled population who registered other cities of Turkey is important. The main aim of this study is to analyse population growth of all districts considering the population change between 2012 and 2017, to evaluate the related factors and to develop a district typology by using the data of settled population according to their family registration in the name of reading the current countryman networks. In the first section of the study, district populations of Istanbul are examined regarding the related five-year change. Afterwards, most repeated countryman networks of all Istanbul’s districts are specified regarding the population growth rate of the registered cities. In the latter section of the study, districts were divided into categories regarding the specific population change features which help to create district typology.

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