Suburban Morphology Dynamics: The Case of the Tricity Agglomeration, Poland

Suburbanization is a phase of the development of cities that consists in the growth of the suburban zone at the expense of the city center, which becomes gradually depopulated. The phenomenon of uncontrolled suburbanization (urban sprawl) causes infrastructural (including transport), environmental, social, economic, and legal problems. This paper presents the results of a study of the phenomenon of suburbanization conducted on the basis of vector data using two methods: one based on the use of a grid of primary square fields, and one based on the use of concentric zones/rings. The analyses were conducted in the surroundings of the Tricity agglomeration, which is located in the northern part of Poland on the Gulf of Gdansk, and covered the period from 2000 to 2018. Using a grid of primary fields, the areas of the greatest increase and decrease in the developed areas, irrespective of administrative boundaries, were determined for the selected periods, and the areas of the constant positive and negative balance of the buildings were identified. Using concentric rings, the process of the shifting of the new development zones was traced. The paper also refers to the route of the Pomeranian Metropolitan Railway (PKM), which was commissioned in 2015, and its potential impact on suburbanization in the Tricity area. The results made it possible to trace the suburbanization process in time and space and to learn the advantages and disadvantages of the use of vector data in spatial studies.

Urban Development and the (Re)use of the Communist-Built Industrial and Agricultural Sites after 1990. The Showcase of Bucharest–Ilfov Development Region

Urban development and changing the patterns of industry and agriculture had caused the foremost spatial and functional transformations of the post-communist period in Romania. These changes have resulted in increased land consumption, often including the reuse of abandoned or non-residential built-up areas (e.g., industrial, agricultural). By integrating spatial and statistical data, the current analysis has revealed as key features: spatial shrinkage, fragmentation, functional diversification, tertiarization and change of patterns. Using a functional change matrix, five main (re)use types have been identified and quantified: maintenance, conversion, replacement, abandonment, and demolition. Overall, between 1990 and 2018, over 50% functional losses have been recorded.

Evaluating the Territorial Impact of Built-Up Area Expansion in the Surroundings of Bucharest (Romania) through a Multilevel Approach Based on Landsat Satellite Imagery

Assessing the relentless expansion of built-up areas is one of the most important tasks for achieving sustainable planning and supporting decision-making on the regional and local level. In this context, techniques based on remote sensing can play a crucial role in monitoring the fast rhythm of urban growth, allowing the regular appraisal of territorial dynamics. The main aim of the study is to evaluate, in a multi-scalar perspective, the built-up area expansion and the spatio–temporal changes in Ilfov County, which overlaps the surroundings of Bucharest, capital of Romania. Our research focuses on processing multi-date Landsat satellite imagery from three selected time references (2000, 2008, 2018) through the supervised classification process. Further on, the types of built-up area dynamics are explored using LDTtool, a landscape metrics instrument. The results reveal massive territorial restructuring in the 18 years, as the new built-up developments occupy a larger area than the settlements’ surface in 2000. The rhythm of the transformations also changed over time, denoting a significant acceleration after 2008, when 75% of the new development occurred. At the regional level, the spatial pattern has become more and more complex, in a patchwork of spatial arrangements characterized by the proliferation of low density areas interspersed with clusters of high density developments and undeveloped land. At the local level, a comparative assessment of the administrative territorial units’ pathway was conducted based on the annual growth of built-up areas, highlighting the most attractive places and the main territorial directions of development. In terms of the specific dynamics of built-up areas, the main change patterns are “F—NP increment by gain”, followed by “G—Aggregation by gain”, both comprising around 80% of the total number of cells. The first type was prevalent in the first period (2000–2008), while the second is identified only after 2008, when it became the most represented, followed in the hierarchy by the previously dominant category. The spatial pattern differentiations were further explored in three complementary case studies investigated in correlation with socioeconomic data, revealing a heterogeneous landscape.

Remote Sensing-Based Analysis of Urban Landscape Change in the City of Bucharest, Romania

The paper investigates the urban landscape changes for the last 50 years in Bucharest, the capital city of Romania. Bucharest shows a complex structural transformation driven by the socialist urban policy, followed by an intensive real-estate market development. Our analysis is based on a diachronic set of high-resolution satellite imagery: declassified CORONA KH-4B from 1968, SPOT-1 from 1989, and multisensor stacked layers from Sentinel-1 SAR together with Sentinel-2MSI from 2018. Three different datasets of land cover/use are extracted for the reference years. Each dataset reveals its own urban structure pattern. The first one illustrates a radiography of the city in the second part of the 20th century, where rural patterns meet the modern ones, while the second one reveals the frame of a city in a full process of transformation with multiple constructions sites, based on the socialist model. The third one presents an image of a cosmopolitan city during an expansion process, with a high degree of landscape heterogeneity. All the datasets are included in a built-up change analysis in order to map and assess the spatial transformations of the city pattern over 5 decades. In order to quantify and map the changes, the Built-up Change Index (BCI) is introduced. The results highlight a particular situation linked to the policy development visions for each decade, with major changes of about 50% for different built-up classes. The GIS analysis illustrates two major landscape transformations: from the old semirural structures with houses surrounded by gardens from 1968, to a compact pattern with large districts of blocks of flats in 1989, and a contemporary city defined by an uncontrolled urban sprawl process in 2018.

Comparative Assessment of the Built-Up Area Expansion Based on Corine Land Cover and Landsat Datasets: A Case Study of a Post-Socialist City

Monitoring uncontained built-up area expansion remains a complex challenge for the development and implementation of a sustainable planning system. In this regard, proper planning requires accurate monitoring tools and up-to-date information on rapid territorial transformations. The purpose of the study was to assess built-up area expansion, comparing two freely available and widely used datasets, respectively, Corine Land Cover and Landsat, to each other, as well as the ground truth, with the goal of identifying the most cost-effective and reliable tool. The analysis was based on the largest post-socialist city in the European Union, the capital of Romania, Bucharest, and its neighboring Ilfov County, from 1990 to 2018. This study generally represents a new approach to measuring the process of urban expansion, offering insights about the strengths and limitations of the two datasets through a multi-level territorial perspective. The results point out discrepancies between the datasets, both at the macro-scale level and at the administrative unit’s level. On the macro-scale level, despite the noticeable differences, the two datasets revealed the spatiotemporal magnitude of the expansion of the built-up area and can be a useful tool for supporting the decision-making process. On the smaller territorial scale, detailed comparative analyses through five case-studies were conducted, indicating that, if used alone, limitations on the information that can be derived from the datasets would lead to inaccuracies, thus significantly limiting their potential to be used in the development of enforceable regulation in urban planning.

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

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.

Suburbanization and migration in Polish metropolitan areas during political transition

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.

Change detection using Landsat images and an analysis of the linkages between the change and property tax values in the Istanbul Province of Turkey

In this study, the Istanbul Province was monitored using Landsat 5 TM, MSS, Landsat 7 ETM+, and Landsat 8 OLI imagery from the years 1986, 2000, 2009, 2011, 2013, and 2015 in order to assess land cover changes in the province. The aim of the study was to classify manmade structures, land, green, and water areas, and to observe the changes in the province using satellite images. After classification, the images were compared in selected years to observe land cover. Moreover, these changes were correlated with the property tax values of Istanbul by years. The findings of the study showed that manmade structure areas increased while vegetation areas decreased due to rapid population growth, urbanization, and industrial and commercial development in Istanbul. These changes also explain the transformation of land from rural and natural areas to residential use, and serve as a tool with which to assess land value increments. Land value capturing is critical for the analysis of the linkages between the changes in land cover, and for assessing land transformation and urban growth. Due to inadequate market data, real estate tax values were used to analyze the linkages between detection changes, land cover, and taxation. In fact, the declared tax values of land owners are generally lower than the actual market values and therefore it is not possible to transfer the value increasing of land in urban areas by using property taxation from the owner to local and central governments. The research results also show that the integration of remote sensing results with real estate market data give us to determine the tax base values of real estate more realistically.