scholarly journals Measurement of Urban Expansion and Spatial Correlation of Central Yunnan Urban Agglomeration Using Nighttime Light Data

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Enwei Zhang ◽  
Huamei Feng ◽  
Shuangyun Peng
Keyword(s):  
Urban Expansion ◽  
Urban Agglomeration ◽  
Coordinated Development ◽  
Gravity Center ◽  
Changing Trends ◽  
Stellar Radiation ◽  
Nighttime Light Data ◽  
Western Development ◽  
Nighttime Light ◽  
Statistical Yearbook

The Central Yunnan Urban Agglomeration (CYUA) is an important zone of western development in China. The clarification of the spatial structure and changing trends in CYUA could help promote the coordinated development of the CYUA and enhance the overall competitiveness of the region. Based on data from the Yunnan Statistical Yearbook and the nighttime light data, this paper extracts the urban built-up area of the CYUA and analyzes the urban expansion and urban spatial connection intensity of the CYUA from 2000 to 2018 by using the urban gravity center model and the gravity model. The results show the following: (1) From 2000 to 2018, the urban built-up area of the CYUA expanded rapidly, and the urban built-up area increased by 369.35%, with Kunming accounting for 45.41% of the increased area. Kunming was the main contributor to the increase in the urban built-up area in the CYUA. From 2000 to 2018, the urban built-up areas of the CYUA were scattered in various mountain basins. (2) Overall, the urban gravity center of the CYUA has moved to Kunming, and the distance of the urban gravity center has increased since 2005, indicating that urban expansion has accelerated since 2005. (3) The development of the CYUA is extremely unbalanced. The urban spatial connection intensity between Kunming city, Yuxi city, and Qujing city, and Yi Autonomous Prefecture of Chuxiong is relatively strong, while the urban spatial connection intensity among cities other than Kunming is weak. Overall, the CYUA is characterized by stellar radiation with Kunming city as the core and Yuxi city as the secondary core.

scholarly journals Mapping Development Pattern in Beijing-Tianjin-Hebei Urban Agglomeration Using DMSP/OLS Nighttime Light Data

2017 ◽  
Vol 9 (7) ◽  
pp. 760 ◽  
Author(s):  
Yi’na Hu ◽  
Jian Peng ◽  
Yanxu Liu ◽  
Yueyue Du ◽  
Huilei Li ◽  
...  
Keyword(s):  
Urban Agglomeration ◽  
Development Pattern ◽  
Nighttime Light Data ◽  
Nighttime Light

Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008

2012 ◽  
Vol 106 (1) ◽  
pp. 62-72 ◽  
Author(s):  
Zhifeng Liu ◽  
Chunyang He ◽  
Qiaofeng Zhang ◽  
Qingxu Huang ◽  
Yang Yang
Keyword(s):  
Urban Expansion ◽  
Nighttime Light Data ◽  
Nighttime Light

scholarly journals An Unsupervised Urban Extent Extraction Method from NPP-VIIRS Nighttime Light Data

2020 ◽  
Vol 12 (22) ◽  
pp. 3810
Author(s):  
Xiuxiu Chen ◽  
Feng Zhang ◽  
Zhenhong Du ◽  
Renyi Liu
Keyword(s):  
Clustering Algorithm ◽  
Urban Expansion ◽  
Spatial Context ◽  
Support Vector ◽  
Free Access ◽  
Urban Edge ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Urban Mapping ◽  
Urban Extent

An accelerating trend of global urbanization accompanying various environmental and urban issues makes frequently urban mapping. Nighttime light data (NTL) has shown great advantages in urban mapping at regional and global scales over long time series because of its appropriate spatial and temporal resolution, free access, and global coverage. However, the existing urban extent extraction methods based on nighttime light data rely on auxiliary data and training samples, which require labor and time for data preparation, leading to the difficulty to extract urban extent at a large scale. This study seeks to develop an unsupervised method to extract urban extent from nighttime light data rapidly and accurately without ancillary data. The clustering algorithm is applied to segment urban areas from the background and multi-scale spatial context constraints are utilized to reduce errors arising from the low brightness areas and increase detail information in urban edge district. Firstly, the urban edge district is detected using spatial context constrained clustering, and the NTL image is divided into urban interior district, urban edge district and non-urban interior district. Secondly, the urban edge pixels are classified by an adaptive direction filtering clustering. Finally, the full urban extent is obtained by merging the urban inner pixels and the urban pixels in urban edge district. The proposed method was validated using the urban extents of 25 Chinese cities, obtained by Landsat8 images and compared with two common methods, the local-optimized threshold method (LOT) and the integrated night light, normalized vegetation index, and surface temperature support vector machine classification method (INNL-SVM). The Kappa coefficient ranged from 0.687 to 0.829 with an average of 0.7686 (1.80% higher than LOT and 4.88% higher than INNL-SVM). The results in this study show that the proposed method is a reliable and efficient method for extracting urban extent with high accuracy and simple operation. These imply the significant potential for urban mapping and urban expansion research at regional and global scales automatically and accurately.

scholarly journals Spatiotemporal Heterogeneity Analysis of Yangtze River Delta Urban Agglomeration: Evidence from Nighttime Light Data (2001–2019)

2021 ◽  
Vol 13 (7) ◽  
pp. 1235
Author(s):  
Min Yu ◽  
Shan Guo ◽  
Yanning Guan ◽  
Danlu Cai ◽  
Chunyan Zhang ◽  
...  
Keyword(s):  
Light Intensity ◽  
Urban Development ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
Spatiotemporal Variability ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Spatiotemporal Heterogeneity

The long-term changes of the relationship between nighttime light and urbanization related built-up areas are explored using nighttime light data obtained from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS, data before 2013) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP/VIIRS, data after 2012) and information of the spatiotemporal heterogeneity of urban evolution. This study assimilates two datasets and diagnoses the spatial heterogeneity in administrative city scale based on built-up area tendencies, temporal heterogeneity in pixel scale based on nighttime light intensity tendencies, and GDP associated spatiotemporal variability over the Yangtze River Delta comparing the first two decades of this century (2001–2010 versus 2011–2019). The analysis reveals the following main results: (1) The built-up areas have generally increased in the second period with the center of fast expansion moving southward, including Suzhou-Wuxi-Changzhou, Hangzhou, Ningbo, Nanjing, and Hefei. (2) Urban development in the original city core has saturated and is spilling over to the suburbs and countryside, leading to nighttime light intensity tendency shift from a “rapid to moderate” and a “moderate to rapid” development (a “hot to cold” and a “cold to hot” spatial clustering distribution). (3) The tendency shifts of built-up area and nighttime light intensity occur most frequently in 2010, after which the urban development is transforming from light intensity growth to built-up area growth, particularly in the developed city cores. The urban agglomeration process with nighttime light intensity reaching saturation prior to the urban development spreading into the surrounding suburbs and countryside, appears to be a suitable model, which provides insights in addressing related environmental problems and contribute to regional sustainable urban planning and management.

scholarly journals Coupling Coordination Relationship between Urban Sprawl and Urbanization Quality in the West Taiwan Strait Urban Agglomeration, China: Observation and Analysis from DMSP/OLS Nighttime Light Imagery and Panel Data

2020 ◽  
Vol 12 (19) ◽  
pp. 3217
Author(s):  
Chunyan Lu ◽  
Lin Li ◽  
Yifan Lei ◽  
Chunying Ren ◽  
Ying Su ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Urban Sprawl ◽  
Urban Areas ◽  
Driving Forces ◽  
Urban Expansion ◽  
Taiwan Strait ◽  
Urban Agglomeration ◽  
The West ◽  
Nighttime Light ◽  
Nighttime Light Imagery

Urban sprawl is the most prominent characteristic of urbanization, and increasingly affects local and regional sustainable development. The observation and analysis of urban sprawl dynamics and their relationship with urbanization quality are essential for framing integrative urban planning. In this study, the urban areas of the West Taiwan Strait Urban Agglomeration (WTSUA) were extracted using nighttime light imagery from 1992 to 2013. The spatio-temporal characteristics and pattern of urban sprawl were quantitatively analyzed by combining an urban expansion rate index and a standard deviation ellipse model. The urbanization quality was assessed using an entropy weight model, and its relationship with urban sprawl was calculated by a coupling coordination degree model. The results showed that the urban area in the WTSUA experienced a significant increase, i.e., 18,806.73 km2, during the period 1992–2013. The central cities grew by 11.08% and noncentral cities by 27.43%, with a general uneven city rank-size distribution. The urban sprawl showed a circular expansion pattern, accompanied by a gradual centroid migration of urban areas from the southeast coast to the central-western regions. The coupling coordination level between urban expansion and urbanization quality increased from serious incoordination in 1992 to basic coordination in 2013. Dual driving forces involving state-led policies and market-oriented land reform had a positive influence on the harmonious development of urban sprawl and urbanization quality of the WTSUA. This research offers an effective approach to monitor changes in urban sprawl and explore the coupling coordination relationship between urban sprawl and urbanization quality. The study provides important scientific references for the formulation of future policies and planning for sustainable development in urban agglomerations.

scholarly journals Spatiotemporal Characterization of the Urban Expansion Patterns in the Yangtze River Delta Region

2021 ◽  
Vol 13 (21) ◽  
pp. 4484
Author(s):  
Ziqi Yu ◽  
Longqian Chen ◽  
Long Li ◽  
Ting Zhang ◽  
Lina Yuan ◽  
...  
Keyword(s):  
Yangtze River ◽  
Urban Expansion ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
Delta Region ◽  
Gravity Center ◽  
Yangtze River Delta Region ◽  
The Yangtze River Delta

Characterizing urban expansion patterns is of great significance to planning and decision-making for urban agglomeration development. This study examined the urban expansion in the entire Yangtze River Delta Region (YRDR) with its land-use data of six years (1995, 2000, 2005, 2010, 2015, and 2018). On the basis of traditional methods, we comprehensively considered the four aspects of urban agglomeration: expansion speed, expansion difference, expansion direction, and landscape pattern, as well as the interconnection of and difference in the expansion process between each city. The spatiotemporal heterogeneity of urban expansion development in this region was investigated by using the speed and differentiation indices of urban expansion, gravity center migration, landscape indices, and spatial autocorrelations. The results show that: (1) over the 23 years, the expansion of built-up land in the Yangtze River Delta Region was significant, (2) the rapidly expanding cities were mainly located along the Yangtze River and coastal areas, while the slowly expanding cities were mainly located in the inland areas, (3) the expansion direction of each city varied and the gravity center of the urban agglomeration moved toward the southwest, and (4) the spatial structure of the region became more clustered, the shape of built-up land turned simpler, and fragmentation decreased. This study unravels the spatiotemporal change of urban expansion patterns in this large urban agglomeration, and more importantly, can serve as a guide for formulating urban agglomeration development plans.

scholarly journals An Improved Method for Urban Built-Up Area Extraction Supported by Multi-Source Data

2021 ◽  
Vol 13 (9) ◽  
pp. 5042
Author(s):  
Chengming Li ◽  
Xiaoyan Wang ◽  
Zheng Wu ◽  
Zhaoxin Dai ◽  
Jie Yin ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Urban Expansion ◽  
Social Factor ◽  
Road Networks ◽  
Extraction Methods ◽  
Boundary Extraction ◽  
Points Of Interest ◽  
Nighttime Light Data ◽  
The Social ◽  
Nighttime Light

Urban built-up areas, where urbanization process takes place, represent well-developed areas in a city. The accurate and timely extraction of urban built-up areas has a fundamental role in the comprehension and management of urbanization dynamics. Urban built-up areas are not only a reflection of urban expansion but also the main space carrier of social activities. Recent research has attempted to integrate the social factor to improve the extraction accuracy. However, the existing extraction methods based on nighttime light data only focus on the integration of a single factor, such as points of interest or road networks, which leads to weak constraint and low accuracy. To address this issue, a new index-based methodology for urban built-up area extraction that fuses nighttime light data with multisource big data is proposed in this paper. The proposed index, while being conceptually simple and computationally inexpensive, can extract the built-up areas efficiently. First, a new index-based methodology, which integrates nighttime light data with points-of-interest, road networks, and the enhanced vegetation index, was constructed. Then, based on the proposed new index and the reference urban built-up data area, urban built-up area extraction was performed based on the dynamic threshold dichotomy method. Finally, the proposed method was validated based on actual data in a city. The experimental results indicate that the proposed index has high accuracy (recall, precision and F1 score) and applicability for urban built-up area boundary extraction. Moreover, this paper discussed different existing urban area extraction methods, and provides an insight into the appropriate approaches selection for further urban built-up area extraction in cities with different conditions.

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