Monitoring Regional Urban Dynamics Using DMSP/OLS Nighttime Light Data in Zhejiang Province

Accurate monitoring of urban regions and urban sprawls is critical to the detection and assessment of regional development. The nighttime light images of Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) provide us direct solutions to make spatial descriptions of urban regions. Unfortunately, accurate monitoring of urban regions is apt to be hampered due to the shortages of the DMSP/OLS data. In this study, we utilized a new urban region extraction strategy based on the edge-detection method which is widely applied in automatic digital image processing. The edges of urban areas in Zhejiang province were identified based on the distributions and values of pixels. Compared with other traditional methods, the urban regions extracted in this study present a higher overall accuracy and kappa coefficient (OA = 93.1409%; Kappa = 0.8755). Two periods of the urban dynamic process and urban sprawl pattern in Zhejiang from 1992–2013 were further detected by the proposed method. At city level, the drastic increase in urban areas was found in cities of Hangzhou and Ningbo. This study provides an objective and convenient solution to the accurate identification of urban regions, which is also an important step to better understand the urban dynamics and urban development.

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Towards the Polycentric Urban Region: Impacts on Centres and Milieus

Open House International ◽

10.1108/ohi-03-2005-b0002 ◽

2005 ◽

Vol 30 (3) ◽

pp. 9-16

Author(s):

Sako Musterd ◽

Marco Bontje ◽

Wim Ostendorf

Keyword(s):

Population Dynamics ◽

Residential Mobility ◽

Central City ◽

Urban System ◽

Urban Region ◽

Urban Dynamics ◽

Urban Regions ◽

The Past ◽

Using Data ◽

Insight Into

Over the past four decades, many urban regions, including the Amsterdam region, have changed from compact monocentric urban entities to - albeit still fairly compact - polycentric urban regions. This has been illustrated frequently and in various ways, for example with daily interaction information. A question relevant to this transformation concerns the implications it poses to the different centres and milieus in the urban region, especially the “old” central city. Is the central city quickly losing position, or is it gaining a new, vital place in the urban region? Can the answer to that be deduced from the population dynamics in the urban region? Is insight into the residential mobility process helpful in understanding the changing residential structure and the functioning of the urban system? This paper addresses these questions, using data that make it possible to analyse urban dynamics.

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Bypass urbanism: Re-ordering center-periphery relations in Kolkata, Lagos and Mexico City

Environment and Planning A Economy and Space ◽

10.1177/0308518x20983818 ◽

2021 ◽

pp. 0308518X2098381

Author(s):

Lindsay Sawyer ◽

Christian Schmid ◽

Monika Streule ◽

Pascal Kallenberger

Keyword(s):

Mexico City ◽

Urban Areas ◽

Large Scale ◽

State Agency ◽

Urban Region ◽

New Town ◽

Urban Regions ◽

Regulatory Frameworks ◽

Massive Scale ◽

Center Periphery

This paper introduces the concept of “bypass urbanism” to account for a process of urbanization that is reordering center-periphery relations of urban regions into new hierarchies. Bypass urbanism became visible through a comparison of large-scale urban transformations at the peripheries of Kolkata, Lagos, and Mexico City by zooming out and considering their impacts on the socio-spatial structure of the extended urban regions. Bypass urbanism is not emerging from the construction of a singular new town or real estate project, but is the result of the simultaneous development of an ensemble of various independent but related projects. Therefore, bypass urbanism usually does not emanate from a coherent planning initiative, even less so from a hidden “master plan” at the hands of any single developer or state agency, but it emerges through a convergence of interests over large areas of land at the geographical periphery of urban regions that have been made available for new urban developments by various measures. We understand bypass urbanism as a multidimensional process that includes material-geographical bypassing, the bypassing of regulatory frameworks, and socio-economic bypassing in everyday life. It results in the creation of exclusive and excluding spaces that enable middle and upper-class lifestyles, at the same time leading to the peripheralization of extant urban areas that are bypassed and neglected. The massive scale of bypass urbanism that we have observed represents a new quality of urban development resulting not in isolated urban enclaves or archipelagos, but in the fundamental restructuring of the extended urban region with far reaching and incalculable repercussions.

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Extending the Concept of City for the Delineation of Large Urban Regions (LUR) for the Cities of the World

10.20944/preprints202003.0213.v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Celine Rozenblat

Keyword(s):

Urban Areas ◽

Urban Region ◽

City Region ◽

Top Down ◽

Bottom Up ◽

Urban Regions ◽

City Regions ◽

The World

Cities’ delineation remains a hot topic of debate in a time where comparisons between cities are becoming increasingly based on different issues that address various scales of interventions and thus different concepts of cities. Aiming to compare cities and their insertion into globalization, we suggest that the “urban field of influence” is the best way to approach cities for this specific perspective. However, after reviewing the different existing possible concepts, we replace this concept with four different approaches proposed by Pumain et al. (1992): political entities, morphological agglomerations, functional urban areas and conurbations/Mega city regions. We discuss the top-down and bottom-up existing initiatives launched at the world scale and then use a mixed top-down and bottom-up approach to propose a new delineation of a large urban region (LUR), denoting a concept close to the conurbation or Mega city-region concept. The compositions of these LURs are published as an initial incomplete framework, suggesting the need for further critical comments and contributions to improve them.

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Multi-View Joint Graph Representation Learning for Urban Region Embedding

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2020/611 ◽

2020 ◽

Author(s):

Mingyang Zhang ◽

Tong Li ◽

Yong Li ◽

Pan Hui

Keyword(s):

Urban Areas ◽

Human Mobility ◽

Representation Learning ◽

Learning Model ◽

Graph Representation ◽

Urban Region ◽

Real World Data ◽

Joint Learning ◽

Urban Dynamics ◽

Urban Data

The increasing amount of urban data enable us to investigate urban dynamics, assist urban planning, and eventually, make our cities more livable and sustainable. In this paper, we focus on learning an embedding space from urban data for urban regions. For the first time, we propose a multi-view joint learning model to learn comprehensive and representative urban region embeddings. We first model different types of region correlations based on both human mobility and inherent region properties. Then, we apply a graph attention mechanism in learning region representations from each view of the built correlations. Moreover, we introduce a joint learning module that boosts the region embedding learning by sharing cross-view information and fuses multi-view embeddings by learning adaptive weights. Finally, we exploit the learned embeddings in the downstream applications of land usage classification and crime prediction in urban areas with real-world data. Extensive experiment results demonstrate that by exploiting our proposed joint learning model, the performance is improved by a large margin on both tasks compared with the state-of-the-art methods.

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Modeling Spatiotemporal Population Changes by Integrating DMSP-OLS and NPP-VIIRS Nighttime Light Data in Chongqing, China

Remote Sensing ◽

10.3390/rs13020284 ◽

2021 ◽

Vol 13 (2) ◽

pp. 284

Author(s):

Dan Lu ◽

Yahui Wang ◽

Qingyuan Yang ◽

Kangchuan Su ◽

Haozhe Zhang ◽

...

Keyword(s):

Spatial Distribution ◽

Relative Error ◽

Urban Areas ◽

Large Scale ◽

Population Distribution ◽

Spatial Optimization ◽

Distribution Data ◽

Mountainous Areas ◽

Mean Relative Error ◽

Nighttime Light

The sustained growth of non-farm wages has led to large-scale migration of rural population to cities in China, especially in mountainous areas. It is of great significance to study the spatial and temporal pattern of population migration mentioned above for guiding population spatial optimization and the effective supply of public services in the mountainous areas. Here, we determined the spatiotemporal evolution of population in the Chongqing municipality of China from 2000–2018 by employing multi-period spatial distribution data, including nighttime light (NTL) data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). There was a power function relationship between the two datasets at the pixel scale, with a mean relative error of NTL integration of 8.19%, 4.78% less than achieved by a previous study at the provincial scale. The spatial simulations of population distribution achieved a mean relative error of 26.98%, improved the simulation accuracy for mountainous population by nearly 20% and confirmed the feasibility of this method in Chongqing. During the study period, the spatial distribution of Chongqing’s population has increased in the west and decreased in the east, while also increased in low-altitude areas and decreased in medium-high altitude areas. Population agglomeration was common in all of districts and counties and the population density of central urban areas and its surrounding areas significantly increased, while that of non-urban areas such as northeast Chongqing significantly decreased.

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An Optimized Approach for Extracting Urban Land Based on Log-Transformed DMSP-OLS Nighttime Light, NDVI, and NDWI

Remote Sensing ◽

10.3390/rs13040766 ◽

2021 ◽

Vol 13 (4) ◽

pp. 766

Author(s):

Yuanmao Zheng ◽

Qiang Zhou ◽

Yuanrong He ◽

Cuiping Wang ◽

Xiaorong Wang ◽

...

Keyword(s):

Urban Development ◽

Urban Areas ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Development Planning ◽

Urban Land ◽

Sustainable Urban Development ◽

Land Use Patterns ◽

Water Index ◽

Nighttime Light

Quantitative and accurate urban land information on regional and global scales is urgently required for studying socioeconomic and eco-environmental problems. The spatial distribution of urban land is a significant part of urban development planning, which is vital for optimizing land use patterns and promoting sustainable urban development. Composite nighttime light (NTL) data from the Defense Meteorological Program Operational Line-Scan System (DMSP-OLS) have been proven to be effective for extracting urban land. However, the saturation and blooming within the DMSP-OLS NTL hinder its capacity to provide accurate urban information. This paper proposes an optimized approach that combines NTL with multiple index data to overcome the limitations of extracting urban land based only on NTL data. We combined three sources of data, the DMSP-OLS, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI), to establish a novel approach called the vegetation–water-adjusted NTL urban index (VWANUI), which is used to rapidly extract urban land areas on regional and global scales. The results show that the proposed approach reduces the saturation of DMSP-OLS and essentially eliminates blooming effects. Next, we developed regression models based on the normalized DMSP-OLS, the human settlement index (HSI), the vegetation-adjusted NTL urban index (VANUI), and the VWANUI to analyze and estimate urban land areas. The results show that the VWANUI regression model provides the highest performance of all the models tested. To summarize, the VWANUI reduces saturation and blooming, and improves the accuracy with which urban areas are extracted, thereby providing valuable support and decision-making references for designing sustainable urban development.

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Trends in prevalence of gestational diabetes mellitus in Zhejiang Province, China, 2016–2018

Nutrition & Metabolism ◽

10.1186/s12986-020-00539-8 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Meng Wang ◽

Ru-Ying Hu ◽

Wei-Wei Gong ◽

Jin Pan ◽

Fang-Rong Fei ◽

...

Keyword(s):

Diabetes Mellitus ◽

Gestational Diabetes ◽

Gestational Diabetes Mellitus ◽

Rural Areas ◽

Urban Areas ◽

Age Groups ◽

Zhejiang Province ◽

Advanced Age ◽

Female Population ◽

Annual Prevalence

Abstract Background Limited population-based studies have investigated the secular trend of prevalence of gestational diabetes mellitus (GDM) in mainland China. Therefore, this study aimed to estimate the prevalence of GDM and time trends in Chinese female population. Methods Based on Diabetes Surveillance System of Zhejiang Province, 97,063 diagnosed GDM cases aged 20–50 years were identified from January 1, 2016 to December 31, 2018. Annual prevalence, prevalence rate ratios (PRRs) and average annual percentage change with their 95% confidence intervals (CIs) were reported. Results The age-standardized overall prevalence of GDM was reported to be 7.30% (95% CI 7.27–7.33%); 9.13% (95% CI 9.07–9.19%) in urban areas and 6.24% (95% CI 6.21–6.27%) in rural areas. Compared with 20–24 years age group, women in advanced age groups (25–50 years) were at higher risk for GDM (PRRs ranged from 1.37 to 8.95 and the 95% CIs did not include the null). Compared with rural areas, the risk for GDM was higher in urban areas (PRR: 1.69, 95% CI 1.67–1.72). The standardized annual prevalence increased from 6.02% in 2016 to 7.94% in 2018, with an average annual increase of 5.48%, and grew more rapidly in rural than urban areas (11.28% vs. 0.00%). Conclusions This study suggested a significant increase in the prevalence of GDM among Chinese female population in Zhejiang province during 2016–2018, especially in women characterized by advanced age and rural areas.

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Mapping 20 Years of Urban Expansion in 45 Urban Areas of Sub-Saharan Africa

Remote Sensing ◽

10.3390/rs13030525 ◽

2021 ◽

Vol 13 (3) ◽

pp. 525

Author(s):

Yann Forget ◽

Michal Shimoni ◽

Marius Gilbert ◽

Catherine Linard

Keyword(s):

Case Studies ◽

Urban Areas ◽

Urban Expansion ◽

Local Population ◽

Sub Saharan Africa ◽

Annual Growth Rate ◽

Urban Dynamics ◽

Mapping Approach ◽

Sub Saharan ◽

The Impact

By 2050, half of the net increase in the world’s population is expected to reside in sub-Saharan Africa (SSA), driving high urbanization rates and drastic land cover changes. However, the data-scarce environment of SSA limits our understanding of the urban dynamics in the region. In this context, Earth Observation (EO) is an opportunity to gather accurate and up-to-date spatial information on urban extents. During the last decade, the adoption of open-access policies by major EO programs (CBERS, Landsat, Sentinel) has allowed the production of several global high resolution (10–30 m) maps of human settlements. However, mapping accuracies in SSA are usually lower, limited by the lack of reference datasets to support the training and the validation of the classification models. Here we propose a mapping approach based on multi-sensor satellite imagery (Landsat, Sentinel-1, Envisat, ERS) and volunteered geographic information (OpenStreetMap) to solve the challenges of urban remote sensing in SSA. The proposed mapping approach is assessed in 17 case studies for an average F1-score of 0.93, and applied in 45 urban areas of SSA to produce a dataset of urban expansion from 1995 to 2015. Across the case studies, built-up areas averaged a compound annual growth rate of 5.5% between 1995 and 2015. The comparison with local population dynamics reveals the heterogeneity of urban dynamics in SSA. Overall, population densities in built-up areas are decreasing. However, the impact of population growth on urban expansion differs depending on the size of the urban area and its income class.

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Delineating the Urban Areas of a Cross-Boundary City with Open-Access Data: Guangzhou–Foshan, South China

Sustainability ◽

10.3390/su13052930 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2930

Author(s):

Pengfei Ban ◽

Wei Zhan ◽

Qifeng Yuan ◽

Xiaojian Li

Keyword(s):

Urban Area ◽

Urban Areas ◽

City Size ◽

Border City ◽

Point Of Interest ◽

Nighttime Light Data ◽

Profile Line ◽

Point Analysis ◽

Nighttime Light ◽

Single Data

Cities defined mainly from the administrative aspect can create impact and problems especially in the case of China. However, only a few researchers from China have attempted to identify urban areas from the morphology dimension. In addition, previous studies have been mostly based on the national and regional scales or a single prefecture city and have completely ignored cross-boundary cities. Defining urban areas on the basis of a single data type also has limitations. To address these problems, this study integrates point of interest and nighttime light data, applies the breaking point analysis method to determine the physical geographic scope of the Guangzhou–Foshan cross-border city, and then compares this city with Beijing and Shanghai. Results show that Guangzhou–Foshan comprises one core urban area and six suburban counties, among which the core urban area extends across the administrative boundaries of Guangzhou and Foshan. The urban area and average urban radius of Guangzhou–Foshan are larger than those of Beijing and Shanghai, and this finding contradicts the city size measurements based on the administrative division system of China and those published on traditional official statistical yearbooks. In terms of urban density value, Shanghai has the steepest profile followed by Guangzhou–Foshan and Beijing, and the profile line of Guangzhou–Foshan has a bimodal shape.

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Quantitative Recognition and Characteristic Analysis of Production-Living-Ecological Space Evolution for Five Resource-Based Cities: Zululand, Xuzhou, Lota, Surf Coast and Ruhr

Remote Sensing ◽

10.3390/rs13081563 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1563

Author(s):

Yuanyuan Tao ◽

Qianxin Wang

Keyword(s):

Remote Sensing ◽

Urban Areas ◽

Large Scale ◽

Remote Sensing Image ◽

Data Availability ◽

Function Evaluation ◽

Characteristic Analysis ◽

Accurate Identification ◽

Living Space ◽

Evolution Characteristics

The accurate identification of PLES changes and the discovery of their evolution characteristics is a key issue to improve the ability of the sustainable development for resource-based urban areas. However, the current methods are unsuitable for the long-term and large-scale PLES investigation. In this study, a modified method of PLES recognition is proposed based on the remote sensing image classification and land function evaluation technology. A multi-dimensional index system is constructed, which can provide a comprehensive evaluation for PLES evolution characteristics. For validation of the proposed methods, the remote sensing image, geographic information, and socio-economic data of five resource-based urbans (Zululand in South Africa, Xuzhou in China, Lota in Chile, Surf Coast in Australia, and Ruhr in Germany) from 1975 to 2020 are collected and tested. The results show that the data availability and calculation efficiency are significantly improved by the proposed method, and the recognition precision is better than 87% (Kappa coefficient). Furthermore, the PLES evolution characteristics show obvious differences at the different urban development stages. The expansions of production, living, and ecological space are fastest at the mining, the initial, and the middle ecological restoration stages, respectively. However, the expansion of living space is always increasing at any stage, and the disorder expansion of living space has led to the decrease of integration of production and ecological spaces. Therefore, the active polices should be formulated to guide the transformation of the living space expansion from jumping-type and spreading-type to filling-type, and the renovation of abandoned industrial and mining lands should be encouraged.

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