Contents
2020
Volume: 22 Issue 6
19 Article(s)

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Applications and Influence of Transport Big Data in Human and Economic Geography
HUANG Jie, and WANG Jiaoe
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1180 (2020)
Research on the Spatial Layout of and Factors Affecting the Price of Industrial Land in China
GAO Boyang, LUO Huilin, HUANG Zhiji, XU Fanya, and LIU Baihong
In the context of fiscal decentralization and local competition, local government in China usually adopts means of supplying excessive industrial land and lowering the transfer price of industrial land, in order to attract more investment from enterprises. These measures could directly lead to lots of problems, such as
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1189 (2020)
Study on Spatial Distribution of Modern Sweet Diet and its Impact Factors in China based on Big Data from Internet
YAO Kezhen, and YUE Shuping
As the most important element with local characteristics in regional culture, dietary geographical culture presents a new diversified situation under the background of large scale population movement. However, up to now, the domestic research on the distribution characteristics of sweet diet based on traditional cognit
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1202 (2020)
The Spatial Distribution of Automobile Manufacturing Enterprises and its Influencing Factors in Liuzhou
SUN Wei, and LIN Xiaona
China is a world leader in automobile production, and its production and sales has ranked first in the world for nine consecutive years. However, research on the automobile industry is more concentrated on the regional scale, and research on the urban scale is relatively rare. This paper takes Liuzhou City as a case, a
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1216 (2020)
A Study on the Influencing Factors and Driving Forces of Spatial Differentiation of Retail Formats in Guangzhou
WU Kangmin, WANG Yang, YE Yuyao, and ZHANG Hongou
Exploration of the spatial differentiation of the retail industry based on large-scale geospatial data is of great significance for urban development. In the recent years, POI data has become an important data source for studying urban dynamics. POI data abstracts retail stores as a point on the map, and the data are o
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1228 (2020)
Research on Travel Pattern and Network Characteristics of Inter-city Travel in China's Urban Agglomeration during the National Day Week based on Tencent Migration Data
LI Tao, WANG Jiaoe, and HUANG Jie
Intercity travel is a time-dependent behavior, which has different spatial characteristics with different time constraints or during different time periods. The patterns of intercity travel and geographical spatial connections revealed by intercity travel could be different with time. However, intercity travel with var
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1240 (2020)
Within-Day Variation of the Complexity of Bus Passenger Flow Network based on Smart Card Data
ZHAO Shaoya, YANG Xingdou, DAI Teqi, and ZHANG Chao
Public transportation in large cities is a typical complex giant system. The use of complex network methods to analyze large city public transport network systems is of great significance for urban transport development. Most of current studies take public transport stations as nodes and routes as connecting edges to c
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1254 (2020)
Discovery of Urban Human Mobility Patterns from Smart Card Transactions and Taxi GPS Trajectories: A Comparative Study
ZHENG Xiaolin, LIU Qiliang, LIU Wenkai, and WU Zhihui
In the era of big data, traffic flows play an important role in understanding our socioeconomic environment. In recent years, two types of traffic flows, smart card transactions and taxi GPS trajectories, have been widely but usually separately utilized to understand human mobility in big cities. To date, although nume
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1268 (2020)
Estimating the Potential Demand for Bicycle Travel based on Large-scale Mobile Phone Location Data
ZHOU Yajuan, ZHAO Zhiyuan, WU Sheng, FANG Zhixiang, and CHEN Zuoqi
The potential bicycle travel demand indicates the travel demand that could potentially be served by bicycles. Assessing the potential bicycle travel demand can help to optimize the allocation of the related infrastructure (e.g., bike parking areas and bike lanes) in cities. Mobile phone location data have the advantage
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1282 (2020)
Assessment of Smart City Development Status in China based on Multi-source Data
DU Delin, HUANG Jie, and WANG Jiaoe
With the development of information and communication technology, such as mobile internet, cloud computing, and big data, smart city has gradually become the important development tendency of urban construction. During the period of the 13 th five-year plan, cities have formulated their smart city construction (or deve
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1294 (2020)
Study on the Administration and Construction of Urban Agglomeration with Spatiotemporal Big Data: A Progress Review
CHEN Fangmiao, HUANG Huiping, and JIA Kun
With the development of the new type of urbanization, urban agglomeration plays a key role in modern social-economical development. To date, big data has been considered as a technological breakthrough and applied in many fields in recent years. Spatiotemporal big data mining and data fusion analysis can improve the ef
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1307 (2020)
Identifying Mixed Functions of Urban Public Service Facilities in Beijing by Cumulative Opportunity Accessibility Method
ZHAN Dongsheng, XIE Chunxin, ZHANG Wenzhong, DING Liang, XU Jingxue, and ZHEN Maocheng
Rapid development and application of urban space-time big data have provided a new data environment and technical means for identifying urban functional areas. However, the literature regarding mixed urban functional areas detection in the field of urban public service facilities is still lacking. Using spatial point-l
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1320 (2020)
Street Space Quality Evaluation in Yuexiu District of Guangzhou City based on Multi-feature Fusion of Street View Imagery
CUI Cheng, REN Hongyan, ZHAO Lu, and ZHUANG Dafang
Street View Imagery (SVI) is one of the important data sources for the quantitative research of urban built environment. However, it is difficult to fully represent all the information with one type of feature in the SVI due to its complexity and diversity. In this paper, we proposed an effective multi-feature fusion m
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1330 (2020)
A Study on the Method for Functional Classification of Urban Buildings by Using POI Data
CAO Yuanhui, LIU Jiping, WANG Yong, WANG Liangjie, WU Wenzhou, and SU Fenzhen
As the carrier of human activity and social development, buildings are the most important geographical entities that constitute the spatial structure of a city. It is one of the urgent tasks in the construction of smart cities in China to build elaborate digital models of urban buildings. Classifying a large amount of
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1339 (2020)
Research on Urban Wind Environment Simulation: A Case Study of Zhengzhou Central Area
SHEN Xinjie, ZHAO Rui, HE Ruizhen, WANG Qi, and GUO Yuchen
Urban wind environment is an important research field of urban climate, which is of great significance to the analysis of urban heat island effect and ventilation. Taking the central area of Zhengzhou city as an example, this paper used meteorological observation data in 1971-2018, the data from ZY-3 satellite in 2016,
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1349 (2020)
Practice of Scientific Data Sharing: A Case Study of the National Earth System Science Data Center
YANG Yaping, JIANG Hou, and SUN Jiulin
Earth System Science (ESS) is a comprehensive interdisciplinary discipline, which originates from the study of global climate change and benefits from the progress of remote sensing technology. Now, ESS has entered the era of big data and artificial intelligence technology has played a key role in solving the frontier
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1358 (2020)
Extracting Mixed Topic Patterns within Downtown Beijing at the Block Level
LIU Jingjing, LIU Yusi, YI Disheng, YANG Jing, and ZHANG Jing
Cities with different land use types influenced by rapid urbanization and urban expansion support various human activities, such as shopping, eating, living, working, and recreation. The mixed use of land can stimulate the vitality of the city, enable the city togather enough people at different points in time, thus pr
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1370 (2020)
A Framework for AR Spatial Analysis based on Edge-Cloud Integration
BIE Yongpan, GUAN Qingfeng, and YAO Yao
Augmented Reality (AR) for geographic data is an important development direction of geographic information visualization. In recent years, some geographic studies have begun to use head-wear AR devices to visualize geographic data, making geographic spatial information more fully expressed. However, due to the limited
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1383 (2020)
An OD Flow Spatio-temporal Joint Clustering Algorithm based on Step-by-step Merge Strategy
XIANG Qiuliang, WU Qunyong, and ZHANG Liangpan
Most of the existing OD flow clustering methods adopt the strategy of dividing the OD flow into O point and D point or considering flow as the four-dimensional point to implement flow clustering, which ignores the effects caused by the length, direction and time information on the clustering process. In this paper, we
Journal of Geo-information Science
  • Publication Date: Jun. 25, 2020
  • Vol.22 Issue, 6 1394 (2020)