Quantifying urban growth patterns in Hanoi using landscape expansion modes and time series spatial metrics

Spatio-temporal change analysis and prediction of land use and land cover changes using CA-ANN model

The spatial and temporal representation of land use and land cover (LULC) changes helps to understand the interactions between natural habitats and other areas and to plan for sustainability. Research on the models used to determine the spatio-temporal change of LULC and simulation of possible future scenarios provides a perspective for future planning and development strategies. Landsat 5 TM for 1990, Landsat 7 ETM + for 2006, and Landsat 8 OLI for 2022 satellite imageries were used to estimate spatial and temporal variations of transition potentials and future LULC simulation. Independent variables (DEM, slope, and distances to roads and buildings) and the cellular automata-artificial neural network (CA-ANN) model integrated in the MOLUSCE plugin of QGIS were used. The CA-ANN model was used to predict the LULC maps for 2038 and 2054, and the results suggest that artificial surfaces will continue to increase. The Düzce City center's artificial surfaces grew by 100% between 1990 and 2022, from 16.04 to 33.10 km2, and are projected to be 41.13 km2 and 50.32 km2 in 2038 and 2054, respectively. Artificial surfaces, which covered 20% of the study area in 1990, are estimated to cover 64.07% in 2054. If this trend continues, most of the 1st-class agricultural lands may be lost. The study's results can assist local governments in their land management strategies and aid them in planning for the future. The results suggest that policies are necessary to control the expansion of artificial surfaces, ensuring a balanced distribution of land use.

Measuring the extent and impact of urban expansion in an agricultural-urbanized landscape in Central Iran

The unplanned urban expansion is a major environmental challenge in Iran resulting in vast degradation of agricultural lands. Focusing on an agricultural-urbanized landscape in Central Iran, the spatial pattern of built-up expansion was assessed from Landsat data processed in 1992 (TM), 2002 (ETM+), 2012 (TM), and 2022 (OLI). Multi-year crop NDVI was also used as a proxy for cropland suitability to assess the intensity of the urban growth impact. Results showed that (1) the area of built-up surfaces increased almost up to double than that of 1992 and passed 36% (413.42 km2) by 2022, (2) the region experienced a coalescence-diffusion transition phase with decreasing spatial connectivity of newly developed patches with old ones, (3) the most suitable croplands were lost in the middle period (2002-2012) when urban patches started to diffuse, and (4) a significantly positive spatial (Spearman's) relationship (r (22100) = 0.181, p = 0.000) was found between the area and quality of croplands which further highlights the high importance of cropland protection in the region.

The Spatio-Temporal Patterns and Driving Forces of Land Use in the Context of Urbanization in China: Evidence from Nanchang City

Land use change has been one of the common problems in the context of urbanization in China. Social economy and land use interact with each other, and it is especially important for human society to adhere to sustainable development, and to deal with the contradictory relationship between the social-economic needs and land use change. The objectives of this study are: (1) Obtain time-series land-use classification data and its spatial distribution in Nanchang City; (2) Identify the characteristics and driving force of spatial-temporal land use changes in Nanchang City from 2000 to 2020; (3) Discuss the relationship between the urban expansion and social economy in Nanchang City. The results show that the spatial distribution of land use in Nanchang City has changed significantly from 2000 to 2020, and the largest area of land-use type in Nanchang City has been cropland. The cropland has continuously declined, and the urban area has increased significantly. A lot of cropland has been transformed into urban areas, and land use degree in Nanchang City has significantly increased. The spatial pattern of land use has greatly changed, and the city spatial pattern has become more aggregated, while the spatial distribution of cropland, forest and grassland has become more fragmented. Moreover, there has been an obvious correlation between social-economic development and the level of land use, and GDP has been the main driver of land use change. The central urban area of Nanchang city has been the main hotspot of land use change.

Urbanization and Cognitive Function Among Middle-Aged and Old Adults in China

OBJECTIVES

Our study examined the effect of urbanization on cognitive function and its possible pathways among Chinese middle-aged and older adults independent of the influence of health-selective migration.

METHODS

Using data from the China Health and Retirement Longitudinal Study, we compared cognitive function among three groups (urbanized-rural residents, rural nonmigrants, and urban nonmigrants). Logistic regression and structural equation models were applied to explore the impact of urbanization on cognitive function and the potential mechanisms.

RESULTS

Compared with the urbanized-rural group, urban nonmigrants had better cognitive function, with a significant coefficient of 1.56 (95% CI: 1.22, 1.89) for global cognition scores and 0.37 (95% CI: 0.22, 0.53) for episodic memory scores. The rural nonmigrants had the worst cognitive function (β = -0.79, 95% CI: -1.04, -0.55) and lower scores of mental intactness (β = -0.65, 95% CI: -0.84, -0.57) and episodic memory (β = -0.14, 95% CI: -0.26, -0.03). The association between urbanization and cognitive function was mainly mediated by income and living conditions among middle-aged and older adults.

DISCUSSION

Rural people who experienced planned urbanization in China had higher cognitive scores than rural non-migrants. Urbanization could thus have a beneficial and cumulative effect on cognitive function. Improvements in living conditions and changes in income are the main drivers behind the relationship. However, urbanization could compensate for the negative impact on cognitive function from disadvantaged early-life conditions, but it cannot completely eliminate the gap between urbanized-rural people and urban nonmigrants.

District-based urban expansion monitoring using multitemporal satellite data: application in two mega cities

Urban expansion is a process of urban development as a result of population growth. Urban sprawl, known as unplanned and unrestricted urban expansion, is among the most important topics in urban studies. In recent decades, many cities around the world in both developing and developed countries have experienced urban expansion. Istanbul and Sydney are two of those cities encountering the urban expansion. Thus, in this study, the spatial and temporal pattern of urban expansion of the most urbanized districts of Istanbul (Arnavutköy) and Sydney (Hills Shire) was analyzed using multi-temporal remote sensing data. Initially, the Landsat images were classified to evaluate the land use/land cover (LULC) changes. The change detection analysis revealed that urban area of Arnavutköy district has increased about 669% from 1997 to 2017 and urban area of Hills Shire Local Government Area (LGA) increased by 78% between 1996 and 2018. The relationship of land surface temperature (LST) and urban areas extracted by recoding the LULC maps was also evaluated in different buffer zones. The results showed that with the increase in urban area extent, the LST has also increased. Then, Shannon's entropy and spatial landscape metrics were used to analyze the district-based urban expansion. The results showed that both study areas expanded over the time but the main differences observed are that Arnavutköy has more fragmented and Hills Shire has a more compact urban growth process.

The Historical Transformation of Peri-Urban Land Use Patterns, via Landscape GIS-Based Analysis and Landscape Metrics, in the Vesuvius Area

Peri-urban areas constitute an enormous resource in terms of natural capital, landscape heritage and economic activities, but, at the same time, they are often affected by physical and socio-economic degradation, drawing the attention of decision makers and planners. Many studies have focused on these contexts both in terms of suburbs, with a close dependence on urban centers, and new land typologies. The present paper focuses on documentary evidence of the direct impacts of urban growth on rural lands. The study area entails the Vesuvius National Park, which, belonging the Naples metropolis, is well-known for its historical, geo-morphologic and naturalistic value. Furthermore, the area has a history of high-quality cartographic production: the 1817, 1907, 1960, 2009 time steps maps were digitized, georeferenced, vectorized and compared in a GIS environment. The results highlight a strong change in land-use, in vineyards and urban class types, with a more disaggregated landscape mosaic. The approach shows that the historical modeling of land-use changes supports the understanding of current land-use dynamics and landscape patterns. The study also shows the need to integrate landscape planning and landscape ecology approaches, highlighting the close interactions between urban, agricultural and natural areas, for the purpose of supporting decision makers in land-use management and conservation policies.

Urban Land Expansion from Scratch to Urban Agglomeration in the Federal District of Brazil in the Past 60 Years

Empirical studies of urban expansion have increased rapidly in recent decades worldwide. Previous studies mainly focused on cities in China, the United States or African countries, with Brazilian cities receiving less attention. Moreover, such studies are rare in purpose-built cities. Taking the urban expansion from scratch (1960) to urban agglomeration (2015) in the Federal District of Brazil (FDB) as an example, this study aims to quantify the magnitude, patterns, modes, types and efficiency of urban land expansion and attempts to reveal some implications within sustainable urban expansion thinking. Annual expansion, landscape metrics, local Moran’s I index, area weighted mean expansion index, and land-use efficiency were computed. The suitability of diffusion–coalescence theory and the impact of population growth and urban development policies on urban expansion were discussed. Urban land continuously expanded and became more fragmented during 1960–2015, which mainly occurred in SSW and WSW directions. Urban land evolved in a polycentric way. Edge expansion was identified as the stable contributor, and the importance of infilling and spontaneous growth alternated. Urban expansion in this region supported the diffusion–coalescence theory. Population growth promoted urban expansion, and the creation of peripheral urban nuclei and their development were associated with the urban expansion and the changes in urban land structure. This study adds new empirical evidence of urban expansion to Brazil urbanization, and compact urbanization, population control, and efficient urban land use should be considered in the future.

Using Satellite Data to Analyse Raw Material Consumption in Hanoi, Vietnam

In this work, we provide an innovative route for analysing urban expansion and population growth and their link to the consumption of construction materials by combining satellite data with material consumption analysis within the Hanoi Province (Vietnam). Urban expansion is investigated with the use of landcover maps for the period 1975–2020 derived from satellite. During this period, artificial surfaces and agricultural areas have increased by 11.6% and 15.5%, respectively, while forests have decreased by 26.7%. We have used publicly available datasets to calculate and forecast the construction materials consumption and measure its statistical correlation with urban expansion between 2007 and 2018. Our results show that official figures for sand consumption are currently underestimated, and that by 2030, steel and sand and gravel consumption will increase even further by three and two times, respectively. Our analysis uses a new method to assess urban development and associated impacts by combining socio-economic and Earth Observation datasets. The analysis can provide evidence, underpin decision-making by authorities, policymakers, urban planners and sustainability experts, as well as support the development of informed strategies for resource consumption. It can also provide important information for identifying areas of land conservation and ecological greenways during urban planning.

Rural–Urban Transition of Hanoi (Vietnam): Using Landsat Imagery to Map Its Recent Peri-Urbanization

The current trend towards global urbanization presents new environmental and social challenges. For this reason, it is increasingly important to monitor urban growth, mainly in those regions undergoing the fastest urbanization, such as Southeast Asia. Hanoi (Vietnam) is a rapidly growing medium-sized city: since new economic policies were introduced in 1986, this area has experienced a rapid demographic rise and radical socio-economic transformation. In this study, we aim to map not only the recent urban expansion of Hanoi, but also of its surroundings. For this reason, our study area consists of the districts within a 30km radius of the city center. To analyze the rural–urban dynamics, we identified three hypothetical rings from the center: the core (within a 10 km radius), the first ring (the area between 10 and 20 km) and, finally, the outer zone (over 20 km). To map land use/land cover (LULC) changes, we classified a miniseries of Landsat images, collected approximately every ten years (1989, 2000, 2010 and 2019). To better define the urban dynamics, we then applied the following spatial indexes: the rate of urban expansion, four landscape metrics (the number of patches, the edge length, the mean patch area and the largest patch index) and the landscape expansion index. The results show how much the city’s original shape has changed over the last thirty years: confined for hundreds of years in a limited space on the right bank of the Red River, it is now a fringed city which has developed beyond the river into the surrounding periurban areas. Moreover, the region around Hanoi is no longer solely rural: in just thirty years, urbanization has converted this territory into an industrial and commercial region.

Analysis of land cover evolution within the built-up areas of provincial capital cities in northeastern China based on nighttime light data and Landsat data

Mastering the evolution of urban land cover is important for urban management and planning. In this paper, a method for analyzing land cover evolution within urban built-up areas based on nighttime light data and Landsat data is proposed. The method solves the problem of inaccurate descriptions of urban built-up area boundaries from the use of single-source diurnal or nocturnal remote sensing data and was able to achieve an effective analysis of land cover evolution within built-up areas. Four main procedures are involved: (1) The neighborhood extremum method and maximum likelihood method are used to extract nighttime light data and the urban built-up area boundaries from the Landsat data, respectively; (2) multisource urban boundaries are obtained using boundary pixel fusion of the nighttime light data and Landsat urban built-up area boundaries; (3) the maximum likelihood method is used to classify Landsat data within multisource urban boundaries into land cover classes, such as impervious surface, vegetation and water, and to calculate landscape indexes, such as overall landscape trends, degree of fragmentation and degree of aggregation; (4) the changes in the multisource urban boundaries and landscape indexes were obtained using the abovementioned methods, which were supported by multitemporal nighttime light data and Landsat data, to model the urban land cover evolution. Using the cities of Shenyang, Changchun and Harbin in northeastern China as experimental areas, the multitemporal landscape index showed that the integration and aggregation of land cover in the urban areas had an increasing trend, the natural environment of Shenyang and Harbin was improving, while Changchun laid more emphasis on the construction of artificial facilities. At the same time, the method proposed in this paper to extract built-up areas from multi-source city data showed that the user accuracy, production accuracy, overall accuracy and Kappa coefficient are at least 3%, 1%, 1% and 0.04 higher than the single-source data method.

Two centuries of settlement and urban development in the United States

Over the past 200 years, the population of the United States grew more than 40-fold. The resulting development of the built environment has had a profound impact on the regional economic, demographic, and environmental structure of North America. Unfortunately, constraints on data availability limit opportunities to study long-term development patterns and how population growth relates to land-use change. Using hundreds of millions of property records, we undertake the finest-resolution analysis to date, in space and time, of urbanization patterns from 1810 to 2015. Temporally consistent metrics reveal distinct long-term urban development patterns characterizing processes such as settlement expansion and densification at fine granularity. Furthermore, we demonstrate that these settlement measures are robust proxies for population throughout the record and thus potential surrogates for estimating population changes at fine scales. These new insights and data vastly expand opportunities to study land use, population change, and urbanization over the past two centuries.

Expansion of Impervious Surfaces and Their Driving Forces in Highly Urbanized Cities in Kyrgyzstan

The expansion of urban areas due to population increase and economic expansion creates demand and depletes natural resources, thereby causing land use changes in the main cities. This study focuses on land cover datasets to characterize impervious surface (urban area) expansion in select cities from 1993 to 2017, using supervised classification maximum likelihood techniques and by quantifying impervious surfaces. The results indicate an increasing trend in the impervious surface area by 35% in Bishkek, 75% in Osh, and 15% in Jalal-Abad. The overall accuracy (OA) for the image classification of two different datasets for the three cities was between 82% and 93%, and the kappa coefficients (KCs) were approximately 77% and 91%. The Landsat images with other supplementary data showed positive urban growth in all of the cities. The GDP, industrial growth, and urban population growth were driving factors of impervious surface sprawl in these cities from 1993 to 2017.Landscape Expansion Index (LEI) results also provided good evidence for the change of impervious surfaces during the study period. The results emphasize the idea of applying future planning and sustainable urban development procedures for sustainable use of natural resources and their management, which will increase life quality in urban areas and environments.

Rapid Assessment of Flood Inundation and Damaged Rice Area in Red River Delta from Sentinel 1A Imagery

The Red River Delta (RRD), including 11 provinces, is one of the four largest rice-growing areas in Vietnam. Tropical storms often occur and cause serious flooding from May to October annually in the RRD, which strongly affects the productivity of the summer–autumn rice, one of two main rice crops. Therefore, the rapid assessment of damaged rice area by flooding inundation is critical for farmers and the government. In this study, we proposed a methodology for quick estimation of rice areas damaged by flooding using Sentinel 1A (S1A) imagery. Firstly, the latest rice map was produced. Then, a Near Real-Time (NRT) flood map, which is estimated from S1A images at the closest time to a flooding event, was generated by excluding the yearly permanent map from the temporal water map. Our experiment was conducted for the assessment of damaged rice area by flooding from the tropical storm named Son-Tinh, which happened on 19–21 July 2018. A Support Vector Machine (SVM) classifier was applied on time-series of S1A VV with VH data (VVVH) to obtain a rice map for the winter-spring season of 2018 with 90.5% Overall Accuracy (OA) and 2.37% difference (12,544 ha) from the General Statistics Office (GSO) of Vietnam’s reports for the whole region. Then, the Otsu thresholding method was applied for permanent water surface extraction and NRT flood mapping. The estimated damaged area was compared to available provincial and communal statistics for validation and further analysis. Right after the Son-Tinh storm, the estimation of inundated rice was approximately 50% of the total rice area in the RRD (271,092 ha). As a result, rice damage level strongly corresponds to the inundation period. In addition, the rice-flooding frequency map over the RRD was estimated to show rice fields suffering a high risk of flooding during the rainy season in the RRD. Our experiment’s results highlight the potential of using Synthetic-Aperture Radar (SAR) imagery for fast monitoring and assessment of paddy rice areas affected by flooding at a large scale in the RRD region.

Edge-Urbanization: Land Policy, Development Zones, and Urban Expansion in Tianjin

Fast-paced urban growth in China has produced a specific, transient form of urban periphery, which continuously shifts outwards as the city expands. Seeing this process as a distinctive type of (sub)urbanization, this paper encapsulates it under the notion of edge-urbanization. The paper argues that edge-urbanization in China is fueled by deliberate government policies, which seek to mobilize peripheral land for high-growth strategies. The relationships between urban expansions and spatial economic policy are analyzed more closely in the case of Tianjin. Geospatial analysis derived from satellite imagery for the period of 1980–2015 reveals the morphological and temporal dynamics of urban growth in the post-reform era. Built-up land in Tianjin has expanded 1.8 times during this period, with the dominant growth type being edge-expansion. This character of urban expansion is shown to be closely associated with government’s “project fever”—setting up development zones and new economic activity on city edge. The results demonstrate a decisive role of the state in shaping (edge) urbanization in China’s major cities.

The Environmental Effects of Urban Development in Hanoi, Vietnam from Satellite and Meteorological Observations from 1999–2016

Since 1990 the Hanoi capital region (or Hanoi metropolitan area) in Vietnam has undergone rapid development, which has gone together with increasing socio-economic growth and prosperity. However, the environmental degradation that has accompanied urban development has raised considerable concern from the public in recent years. This research investigates the effects of urban development on urban sprawl, urban heat island (UHI), and metropolitan weather phenomena that are related to the quality of urban life in the period from 1999–2016. To achieve these objectives, remote sensing technologies were applied to satellite images at three time points (i.e., 1999, 2009, and 2016) that were associated with the meteorological dataset from ground-based stations. The spatial distribution evolution was examined for the land use/land cover changes while using the normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). The increasing impact of urban sprawl on UHI intensity is determined based on the land surface temperature (LST) in multi-temporal forms. Increasing urbanization with the development of gradual outward and northward expansion from the city centre intensified the correlation analysis shows that the UHI. The potential formation of new UHI areas in the near future is also indicated. Furthermore, more than 30% of the metropolitan area is decaying in ecological quality according to an assessment of the urban thermal field variance index (UTFVI). With respect to metropolitan weather, the urbanization in Hanoi affected the observation of meteorological parameters revealed that the relative humidity, total rainfall, temperature, and wind speed over both urban and rural areas. The overall results imply that urban development and its environmental effects and impacts have imposed pressing issues and new challenges to sustainable development in the Hanoi metropolitan area.