Haibin Liu

Bio: Haibin Liu is an academic researcher from China University of Mining and Technology. The author has contributed to research in topics: Supply chain & Business. The author has an hindex of 2, co-authored 5 publications receiving 98 citations.

Spatiotemporal Evolution of Multiscale Urbanization Level in the Beijing-Tianjin-Hebei Region Using the Integration of DMSP/OLS and NPP/VIIRS Night Light Datasets

Abstract: The level of urbanization is a key factor in urban development. In this study, to better characterize the level of urbanization, the panel entropy weight method is used to weight the factors of population, industry, and area to construct a composite indicator of urbanization. A panel regression between this composite index and the average night light values after fusion shows a strong correlation. An accuracy test indicates that the estimated value of fused average light as calculated by the urbanization level estimation model that adequately represents the urbanization level. On this basis, night light data is corrected for zero error on the pixel scale, and spatiotemporal evolution analyses are performed on the city and county scales. The standard deviation ellipse method is used to find that the spatial distribution pattern of the Beijing-Tianjin-Hebei urbanization level from 1995 to 2018 radiates and spreads to the northeast, with Beijing-Tianjin as the center. The spatial pattern shows a contracting trend that is strengthening year by year. Slope analyses show that areas with rapid urbanization growth are mainly concentrated in Beijing and Tianjin. The urbanization development speed of most counties in the Hebei Province is at a low level.

The County-Scale Economic Spatial Pattern and Influencing Factors of Seven Urban Agglomerations in the Yellow River Basin—A Study Based on the Integrated Nighttime Light Data

Abstract: The integrated night light (NTL) datasets were used to represent the economic development level, and visual analysis was carried out on the evolution characteristics of the economic spatial pattern of various urban agglomerations in the Yellow River Basin (YRB), at a county-scale, in 1992, 2005, and 2018. The Global Moran’s I and the local Getis-Ord G methods were used to explore the overall spatial correlation and local cold–hot spot of economic development levels, respectively. The spatial heterogeneity of the influence of relevant factors on the economic development level at the municipal scale was analyzed by using the multi-scale geographically weighted regression (MGWR) model. The results show that the county-level economic spatial pattern of urban agglomeration in the YRB has an obvious “pyramid” characteristic. The hot spots are concentrated in the hinterland of the Guanzhong Plain, the Central Plains, and the Shandong Peninsula urban agglomeration. The cold spots are concentrated in the junction of urban agglomerations, and the characteristics of “cold in the west and hot in the east” are obvious. Labor input and import and exporthave a positive impact on the economic development level for each urban agglomeration, government force has a negative impact, and education shows both positive and negative polarization on economic development.

County-level CO2 emissions and sequestration in China during 1997–2017

Abstract: With the implementation of China's top-down CO2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO2 emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO2 emissions in 2,735 Chinese counties during 1997-2017. Moreover, as vegetation has a significant ability to sequester and reduce CO2 emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO2 emissions in China.

Evolutionary biogeography-based whale optimization methods with communication structure: Towards measuring the balance

Abstract: Whale Optimization Algorithm (WOA) is a popular swarm-based algorithm with some spotted defects in its generated patterns during the searching phases. In this study, an enhanced WOA-based method is proposed in order to overcome the drawbacks of slow convergence speed and easy falling of WOA into the local optimum. The designed variant is called enhanced WOA (EWOA), which combines two strategies at the same time. First, a new communication mechanism (CM) is embedded into the basic WOA to promote the global optimal search ability and the exploitation tendency of the WOA. Then, the Biogeography-based Optimization (BBO) algorithm is partially utilized to harmonize the exploration and exploitation trends. A representative set of comprehensive benchmark cases and three engineering cases are utilized to verify the advantages of the proposed EWOA. The experimental results show that the exploration ability, exploitation ability, state of the balance, and convergence style of the algorithm has been improved significantly. Based on results, the proposed EWOA is a promising and excellent algorithm, and it has achieved better solution quality and faster convergence rate compared with other most advanced algorithms. For access to material and guide for users of this paper, we host an online page at https://aliasgharheidari.com .