Post-socialist urban growth of Bucharest, Romania – a change detection analysis on Landsat imagery (1984–2010)

Mihai, Bogdan; Nistor, Constantin; Simion, Gabriel

doi:10.3986/ags.709

Cited by 34 publications

(24 citation statements)

References 12 publications

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“…The choice of migration destination was based on good transportation networks and attractive natural environments (e.g., the municipalities of Nadarzyn, Milanówek, Piaseczno, and Łomianki near Warsaw). This trend can be observed in various western, central, and eastern European cities (White 1981;Mieszkowski and Mills 1993;Grochowski , Pieniążek and Wilk 2005;Solarek 2005;Mantey 2013;Mihai, Nistor and Simion 2015) In the »Tri-City« (Gdańsk, Sopot, and Gdynia), population flows from the urban core were directed toward selected municipalities (e.g., Pruszcz Gdański). The rate of population exchange between the three cities was rather low because of the unique nature of the region (Parysek 2005).…”

Section: Regional Differences In Suburbanization Processes In Polish mentioning

confidence: 99%

Suburbanization and migration in Polish metropolitan areas during political transition

Gałka

Warych-Juras

2018

AGS

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This article presents the development of suburbanization processes that occurred in Polish metropolitan areas during the political transition from communism. We analyze data on population and migration for municipalities in seven metropolitan areas from 1995 to 2012. Our results show that the suburban development phase was strongly associated with cities’ size and level of economic development. The article concludes that the outflow of the urban population to the suburbs started earliest in centers that had successfully undergone the transition period.

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Section: Regional Differences In Suburbanization Processes In Polish mentioning

confidence: 99%

Suburbanization and migration in Polish metropolitan areas during political transition

Gałka

Warych-Juras

2018

AGS

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“…Remote sensing provides a useful tool for monitoring and quantifying land use/land cover (LULC) changes at high spatial resolution and annual temporal scales, to systematically track the magnitude and spatial trends of urbanization [2,5,13]. Several LULC datasets have been developed using remote sensing, such as the 500-m Moderate-Resolution Imaging Spectroradiometer Global Yearly Land Cover Type (MCD12Q1, from 2001 to 2013) [14], 30-m National Land Cover Database (NLCD, 1992(NLCD, , 2001(NLCD, , 2006, and 2011) [15], and the 30-m Finer Resolution Observation and Monitoring-Global Land Cover (GLOBELAND30, 2000 and 2010) [16].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Variation Analysis of Landscape Pattern Response to Land Use Change from 1985 to 2015 in Xuzhou City, China

Thinh

2018

Sustainability

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Rapid urbanization has dramatically spurred economic development since the 1980s, especially in China, but has had negative impacts on natural resources since it is an irreversible process. Thus, timely monitoring and quantitative analysis of the changes in land use over time and identification of landscape pattern variation related to growth modes in different periods are essential. This study aimed to inspect spatiotemporal characteristics of landscape pattern responses to land use changes in Xuzhou, China durfing the period of 1985–2015. In this context, we propose a new spectral index, called the Normalized Difference Enhanced Urban Index (NDEUI), which combines Nighttime light from the Defense Meteorological Satellite Program/Operational Linescan System with annual maximum Enhanced Vegetation Index to reduce the detection confusion between urban areas and barren land. The NDEUI-assisted random forests algorithm was implemented to obtain the land use/land cover maps of Xuzhou in 1985, 1995, 2005, and 2015, respectively. Four different periods (1985–1995, 1995–2005, 2005–2015, and 1985–2015) were chosen for the change analysis of land use and landscape patterns. The results indicate that the urban area has increased by about 30.65%, 10.54%, 68.77%, and 143.75% during the four periods at the main expense of agricultural land, respectively. The spatial trend maps revealed that continuous transition from other land use types into urban land has occurred in a dual-core development mode throughout the urbanization process. We quantified the patch complexity, aggregation, connectivity, and diversity of the landscape, employing a number of landscape metrics to represent the changes in landscape patterns at both the class and landscape levels. The results show that with respect to the four aspects of landscape patterns, there were considerable differences among the four years, mainly owing to the increasing dominance of urbanized land. Spatiotemporal variation in landscape patterns was examined based on 900 × 900 m sub-grids. Combined with the land use changes and spatiotemporal variations in landscape patterns, urban growth mainly occurred in a leapfrog mode along both sides of the roads during the period of 1985 to 1995, and then shifted into edge-expansion mode during the period of 1995 to 2005, and the edge-expansion and leapfrog modes coexisted in the period from 2005 to 2015. The high value spatiotemporal information generated using remote sensing and geographic information system in this study could assist urban planners and policymakers to better understand urban dynamics and evaluate their spatiotemporal and environmental impacts at the local level to enable sustainable urban planning in the future.

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“…Remote sensing provides us a useful tool to monitor and quantify land use/land cover (LUCC) change at high spatial resolution and annual temporal scales, so as to systematically track the magnitude and trends of urbanization [2,5,13]. Several LULC datasets have been developed using remote sensing, such as the 500-m Moderate-Resolution Imaging Spectroradiometer Global Yearly Land Cover Type (MCD12Q1, from 2001 to 2013) [14], 30-m National Land Cover Database (NLCD, 1992(NLCD, , 2001(NLCD, , 2006(NLCD, , 2011 [15], and the 30-m Finer Resolution Observation and Monitoring-Global Land Cover (GLOBELAND30, 2000,2010) [16].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Variation Analysis of Landscape Pattern Respond to Land Use Change from 1985 to 2015 in Xuzhou City, China

Xi¹,

Thinh²,

Li³

2018

Preprint

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Rapid urbanization has dramatically spurred the economic development over the past three decades, especially in China, but has nevertheless had negative impacts on natural resources since it is an irreversible process. Thus, it is essential to timely monitor and quantitatively analysis the changes in land use over time and to identify the landscape pattern variation related to growth mode in different period. This study aims at inspecting spatiotemporal characteristics of landscape pattern respond to land use changes in Xuzhou city during the period from 1985 to 2015. In this connection, we proposed a new spectral index, named the Normalized Difference Enhanced Urban Index (NDEUI), which combines data from NTL (Nighttime light) from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) with annual maximum Enhanced Vegetation Index (EVI) to reduce the detection confusion between urban areas and barren land, as well as follows. NDEUI-assisted Random Forests algorithm was implemented to obtain the land use/land cover (LULC) maps of Xuzhou in 1985, 1995, 2005 and 2015, respectively. Here, four different periods viz. 1985–1995, 1995–2005, 2005–2015 and 1985–2015 are chosen for the change analysis of land use and landscape pattern. The results indicated that the urban area has increased by about 30.65%, 10.54%, 68.77%, and 143.75% during the four periods mentioned above at the main expense of agricultural land, respectively. The spatial trend maps revealed that continuous transition from other land use types into urban land has appeared a dual-core development mode throughout the urbanization process, located at the new city region and the Jiawang district, mainly affected by the construction of new city region, freeway and the high railway station. Furthermore, we quantified the patch complexity, aggregation, connectivity and diversity of landscape employing a number of landscape metrics to represent the changes of landscape pattern at both class and landscape level, affected by urbanization during the study period. The results showed that with regard to the four aspects of landscape pattern, there were considerable differences among the four years, mainly owing to the increasing dominance of urbanized land. Spatiotemporal variation of landscape pattern was also conducted on the basis of subgrids in 900 m × 900 m. Combined with the land use changes and spatiotemporal variation of landscape pattern, it can be concluded that different urbanization modes and intensity result in variously the spatiotemporal evolution of landscape patterns. For Xuzhou city, the urban growth mainly appeared a leapfrog mode alone both sides of the roads during the period of 1985 to 1995, and then shifted into edge-expansion mode during the period from 1995 to 2005, whereas the edge-expansion and leapfrog modes coexisted for the period from 2005 to 2015. The high valuable spatiotemporal information generated utilizing RS and GIS in this study may give assistance to urban planners and policymakers to well understand urban dynamics and evaluate their spatiotemporal and environmental impacts at a local level for the sake of sustainable urban planning in the future.

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Post-socialist urban growth of Bucharest, Romania – a change detection analysis on Landsat imagery (1984–2010)

Cited by 34 publications

References 12 publications

Suburbanization and migration in Polish metropolitan areas during political transition

Suburbanization and migration in Polish metropolitan areas during political transition

Spatio-Temporal Variation Analysis of Landscape Pattern Response to Land Use Change from 1985 to 2015 in Xuzhou City, China

Spatio-Temporal Variation Analysis of Landscape Pattern Respond to Land Use Change from 1985 to 2015 in Xuzhou City, China

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