scholarly journals Estimation of Cargo Handling Capacity of Coastal Ports in China Based on Panel Model and DMSP-OLS Nighttime Light Data

2019 ◽  
Vol 11 (5) ◽  
pp. 582 ◽  
Author(s):  
Aoshuang Liu ◽  
Ye Wei ◽  
Bailang Yu ◽  
Wei Song
Keyword(s):  
Remote Sensing ◽  
Statistical Data ◽  
Estimation Method ◽  
River Delta ◽  
Important Indicator ◽  
Strong Basis ◽  
Cargo Handling ◽  
Panel Model ◽  
Nighttime Light Data ◽  
Nighttime Light

The cargo handling capacity of a port is the most basic and important indicator of port size. Based on the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime light data and panel model, this study attempts to estimate the cargo handling capacity of 28 coastal ports in China using satellite remote sensing. The study confirmed that there is a very close correlation between DMSP-OLS nighttime light data and the cargo handling capacity of the ports. Based on this correlation, the panel data model was established for remote sensing-based estimation of cargo handling capacity at the port and port group scales. The test results confirm that the nighttime light data can be used to accurately estimate the cargo handling capacity of Chinese ports, especially for the Yangtze River Delta Port Group, Pearl River Delta Port Group, Southeast Coastal Port Group, and Southwest Coastal Port Group that possess huge cargo handling capacities. The high accuracy of the model reveals that the remote sensing analysis method can make up for the lack of statistical data to a certain extent, which helps to scientifically analyze the spatiotemporal dynamic changes of coastal ports, provides a strong basis for decision-making regarding port development, and more importantly provides a convenient estimation method for areas that have long lacked statistical data on cargo handling capacity.

scholarly journals Spatial Pattern of the Vitality of Chinese Characteristic Towns: A Perspective from Nighttime Lights

Land ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 85
Author(s):  
Yuqing Zhang ◽  
Kun Shang ◽  
Zhipeng Shi ◽  
Hui Wang ◽  
Xueming Li
Keyword(s):  
Evaluation Studies ◽  
Geographical Location ◽  
Coastal Areas ◽  
River Delta ◽  
East China ◽  
Industrial Enterprises ◽  
South Central ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
The Town

Nighttime light images are valuable indicators of regional economic development, and nighttime light data are now widely used in town monitoring and evaluation studies. Using the nighttime light data acquired through Luojia1-01 and the geographic information system spatial analysis method, this study analyzed the spatial vitality pattern of 402 characteristic towns in six geographic divisions of China. The average DN (Digital Number) value of Guzhen, having the highest vitality level, was 0.05665221, whereas that of Xin’an, having the lowest vitality level, was 0.00000186. A total of 89.5% of towns have a low level of vitality. The regional differences were significant; high vitality towns are concentrated in economically developed coastal areas, mainly in two large regions of east China and south central. The average lighting densities of the towns in east China and south central were 0.004838 and 0.003190, respectively. The lighting density of the towns in west central was low, and the vitality intensity was generally low. A spatially significant positive correlation of small-town vitality was observed, and “high–high” agglomeration was primarily distributed in the Yangtze River Delta, Pearl River Delta, and Fujian coastal areas in east and south China. The towns with high vitality intensity had similarities in their geographical location, convenient transportation conditions, and profound historical heritage or cultural accumulation along with many industrial enterprises. This research empirically demonstrates the feasibility of using the 130-m-high resolution of the nighttime lighting data of Luojia1-01 to evaluate the vitality at the town scale, and the vitality evaluation focuses on the spatial attributes of the town, which is meaningful to guide the development of the town in each region given the vast area of China and the large differences in the development of different regions.

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 Exploring the Relationship between Urbanization and Ecological Environment Using Remote Sensing Images and Statistical Data: A Case Study in the Yangtze River Delta, China

2020 ◽  
Vol 12 (14) ◽  
pp. 5620 ◽  
Author(s):  
Zhenfeng Shao ◽  
Lin Ding ◽  
Deren Li ◽  
Orhan Altan ◽  
Md. Enamul Huq ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Yangtze River ◽  
Statistical Data ◽  
Yangtze River Delta ◽  
River Delta ◽  
Ecological Environment ◽  
The Yangtze River ◽  
Remote Sensing Images ◽  
The Yangtze River Delta ◽  
Coordination Degree

With the rapid urban development in China, urbanization has brought more and more pressure on the ecological environment. As one of the most dynamic, open, and innovative regions in China, the eco-environmental issues in the Yangtze River Delta have attracted much attention. This paper takes the central region of the Yangtze River Delta as the research object, through building the index system of urbanization and ecological environment based on statistical data and two new indicators (fraction of vegetation coverage and surface urban heat island intensity) extracted from remote sensing images, uses the Entropy-TOPSIS method to complete the comprehensive assessment, and then analyzes the coupling coordination degree between the urbanization and ecological environment and main obstacle factors. The results showed that the coupling coordination degree in the study region generally shows an upward trend from 0.604 in 2008 to 0.753 in 2017, generally changing from an imbalanced state towards a basically balanced state. However, regional imbalance of urbanization and ecological environment always exists, which is mainly affected by social urbanization, economic urbanization, landscape urbanization, pollution loading and resource consumption. Finally, on the basis of the obstacle factor analysis, some specific suggestions for promoting the coordinated development of the Yangtze River Delta are put forward.

scholarly journals A Novel Method of Evaluating Highway Traffic Prosperity Based on Nighttime Light Remote Sensing

2019 ◽  
Vol 12 (1) ◽  
pp. 102
Author(s):  
Ying Chang ◽  
Shixin Wang ◽  
Yi Zhou ◽  
Litao Wang ◽  
Futao Wang
Keyword(s):  
Remote Sensing ◽  
Traffic Flow ◽  
Pearson Correlation ◽  
Flow Volume ◽  
Highway Traffic ◽  
Freeway Traffic ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Per Capita

As the backbone and arteries of a comprehensive transportation network, highways play an important role in improving people’s living standards and promoting economic growth. However, globally, there is limited quantifiable data evaluating the highway traffic state, characteristics, and performance. From the 1960s to the present, remote sensing has been regarded as the most effective technology for long-term and large-scale monitoring of surface information. However, how to reflect the dynamic “flow” information of traffic with a static remote sensing image has always been a difficult problem that is hard to solve in the field. This study aims to construct a method of evaluating highway traffic prosperity using nighttime remote sensing. First, based on nighttime light data that indicate social and economic activities, a highway-oriented method was proposed to extract highway nighttime light data from 2015 annual nighttime light data of the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite sensor (SNPP-VIIRS). Subsequently, Pearson correlation analysis was used to fit the relationship between freeway traffic flow volume and freeway nighttime light at the provincial level. The results showed that Pearson Correlation Coefficient of freeway nighttime light and freeway traffic flow volume for coach and truck are 0.905 and 0.731, respectively, which are higher than between freeway traffic flow volume for coach and truck and total nighttime light (0.593 and 0.516, respectively). A new index—Highway Nighttime Traffic Prosperity Index (HNTPI)—was proposed to evaluate highway traffic across China. The results showed that HNTPI has a strong correspondence with socio-economic parameters. The Pearson Correlation Coefficient of HNTPI and gross domestic product (GDP) per capita, consumption per capita, and population are 0.772, 0.895, and 0.968, respectively. There is a huge spatial heterogeneity in China nighttime traffic, the prosperity degree of highway traffic in developed coastal areas is obviously higher than that inland. The national general highway is the most prosperous highway at night and the national general highway nighttime prosperity of Shanghai reached 22.34%. This research provides basic data for the long-term monitoring and evaluation of regional traffic operation at night and research on the correlation between regional highway construction and the economy.

scholarly journals CHANGE PATTERN EXPLORATION WITH HIERARCHICAL BI-CLUSTERING ON SENTINEL-1 SAR AND NIGHTTIME LIGHT DATA

2020 ◽  
Vol IV-3/W2-2020 ◽  
pp. 13-18
Author(s):  
M. Che ◽  
P. Gamba
Keyword(s):  
Remote Sensing ◽  
Hierarchical Clustering ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Change Pattern ◽  
Novel Approach ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Spatio Temporal ◽  
Multispectral Sensors

Abstract. In the last few decades, urbanization activities have promoted the emergence of megacities, megalopolis, urban clusters or large urban aggregations, but only a few studies have analyzed them using remote sensing data in both the spatial and the temporal domains. In this paper, combining SAR and multispectral sensors with different resolutions, a novel approach, improved by means of a hierarchical clustering technique, is proposed. Urban changes are mapped in the form of multiple spatio-temporal patterns, visualized by change vectors exploiting the combination of SAR and nighttime light data.

scholarly journals Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives

2019 ◽  
Vol 11 (17) ◽  
pp. 1971 ◽  
Author(s):  
Zhao ◽  
Zhou ◽  
Li ◽  
Cao ◽  
He ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Human Activities ◽  
Energy Use ◽  
Environmental Changes ◽  
Deep Understanding ◽  
Historical Review ◽  
Ancillary Data ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Changing World

Nighttime light observations from remote sensing provide us with a timely and spatially explicit measure of human activities, and therefore enable a host of applications such as tracking urbanization and socioeconomic dynamics, evaluating armed conflicts and disasters, investigating fisheries, assessing greenhouse gas emissions and energy use, and analyzing light pollution and health effects. The new and improved sensors, algorithms, and products for nighttime lights, in association with other Earth observations and ancillary data (e.g., geo-located big data), together offer great potential for a deep understanding of human activities and related environmental consequences in a changing world. This paper reviews the advances of nighttime light sensors and products and examines the contributions of nighttime light remote sensing to perceiving the changing world from two aspects (i.e., human activities and environmental changes). Based on the historical review of the advances in nighttime light remote sensing, we summarize the challenges in current nighttime light remote sensing research and propose four strategic directions, including: Improving nighttime light data; developing a long time series of consistent nighttime light data; integrating nighttime light observations with other data and knowledge; and promoting multidisciplinary and interdisciplinary analyses of nighttime light observations.

scholarly journals Multi-Scene Building Height Estimation Method Based on Shadow in High Resolution Imagery

2021 ◽  
Vol 13 (15) ◽  
pp. 2862
Author(s):  
Yakun Xie ◽  
Dejun Feng ◽  
Sifan Xiong ◽  
Jun Zhu ◽  
Yangge Liu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Estimation Method ◽  
Absolute Error ◽  
Large Error ◽  
Estimation Methods ◽  
Height Estimation ◽  
Building Height ◽  
Remote Sensing Imagery ◽  
High Resolution Imagery

Accurately building height estimation from remote sensing imagery is an important and challenging task. However, the existing shadow-based building height estimation methods have large errors due to the complex environment in remote sensing imagery. In this paper, we propose a multi-scene building height estimation method based on shadow in high resolution imagery. First, the shadow of building is classified and described by analyzing the features of building shadow in remote sensing imagery. Second, a variety of shadow-based building height estimation models is established in different scenes. In addition, a method of shadow regularization extraction is proposed, which can solve the problem of mutual adhesion shadows in dense building areas effectively. Finally, we propose a method for shadow length calculation combines with the fish net and the pauta criterion, which means that the large error caused by the complex shape of building shadow can be avoided. Multi-scene areas are selected for experimental analysis to prove the validity of our method. The experiment results show that the accuracy rate is as high as 96% within 2 m of absolute error of our method. In addition, we compared our proposed approach with the existing methods, and the results show that the absolute error of our method are reduced by 1.24 m-3.76 m, which can achieve high-precision estimation of building height.

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