Travel Behaviours of Sharing Bicycles in the Central Urban Area Based on Geographically Weighted Regression: The Case of Guangzhou, China

Mobile information and communication technologies(MICTs) have fully penetrated everyday life in smart societies;this has greatly compressed time, space, and distance, and consequently, reshaped residents’ travel behaviour patterns. As a new mode of shared mobility, the sharing bicycle offers a variety of options for the daily travel of urban residents. Extant studies have mainly examined the travel characteristics and influencing factors of public bicycles with piles, while the travel patterns for sharing bicycles and their driving mechanisms have been largely ignored. Using one week’s travel data for Mobike, this study investigated the spatial and temporal distribution patterns of sharing bicycle travel behaviours in the central urban area of Guangzhou, China;furthermore, it identified the influences of built environment density factors on sharing bicycle travel behaviours based on the geographically weighted regression method. Obvious morning and evening peaks were observed in the sharing bicycle travel patterns for both weekdays and weekends. The old urban area, which had a high degree of mixed function, dense road networks, and cycling-friendly built environments, was the main travel area that attracted sharing bicycles on both weekdays and weekends. Furthermore, factors including the point of interest(POI) for the density of public transport stations, the functional mixing degree, and the density of residential POIs significantly affected residents’ travel behaviours. These findings could enrich discourse regarding shared mobility with a Chinese case characterised by rapidly developing MICTs and also provide references to local authorities for improving slow traffic environments.

Directional Analysis of Urban Expansion Based on Sub-pixel and Regional Scale: A Case Study of Main Districts in Guangzhou, China

Multi-scale data have had a wide-ranging level of performance in the area of urban change monitoring. Herein we investigate the correlation between the impervious surface fraction(ISF) and the Defense Meteorological Satellite Program/Operational Linescan System(DMSP/OLS) nighttime stable light(NTL) data with respect to the urban expansion in the main districts of Guangzhou. Landsat 5 Thematic Mapper and Landsat 8 Operational Land Image(OLI) data from 1988 to 2015 were used to extract the ISF using the linear spectral mixture analysis model and normal difference build-up index at the sub-pixel scale. DMSP/OLS NTL data from 1992 to 2013 were calibrated to illustrate the urban nighttime light conditions at the regional scale. Urban expansion directions were identified by statistics and kernel density analysis for the ISF study area at the sub-pixel scale. In addition, the correlation between the ISF and DMSP/OLS NTL data were illustrated by linear regression analysis. Furthermore, Profile Graph in ArcGIS was employed to illustrate the urban expansion from the differences in correlation in different directions. The conclusions are as follows: 1) The impervious surface(IS)in the study area has expanded to the northeast and the east, starting with the old urban zones, and the high-density IS area has increased by321.14 km^2. 2) The linear regression analysis reveals a positive correlation between the ISF and the DMSP/OLS NTL data. The multi-scale data changes are consistent with the actual urban planning of Guangzhou. 3) The DMSP/OLS NTL data overestimate the urban extent because of its saturation and blooming effects, causing its correlation with ISF to decrease. The pattern of urban expansion influences the saturation and blooming effects of the DMSP/OLS NTL data.

Spatial Structure of China's E-commerce Express Logistics Network Based on Space of Flows

The intermediate link compression characteristics of e-commerce express logistics ne tworks influence the tradition al mode of circulation of goods and economic organization,and alter the city spatial pattern.Based on the theory of space of flows,this study adopts China Smart Logistics Network relational data to build China's e-commerce express logistics network and explore its spatial structure characteristics through social network analysis(SNA),the PageRank technique,and geospatial methods.The results are as follows:the network density is 0.9270,which is close to 1;hence,indicating that e-commerce express logistics lines between Chinese cities are nearly complete and they form a typical network structure,thereby eliminating fragmented spaces.Moreover,the average minimum number of edges is 1.1375,which indicates that the network has a small world effect and thus has a high flow efficiency of logistics elements.A significant hierarchical diffusion effect was observed in dominant flows with the highest edge weights.A diamond-structured network was formed with Shanghai,Guangzhou,Chongqing,and Beijing as the four core nodes.Other node cities with a large logistics scale and importance in the network are mainly located in the 19 city agglomerations of China,revealing the fact that the development of city agglomerations is essential for promoting the separation of experience space and changing the urban spatial pattern.This study enriches the theory of urban networks,reveals the flow laws of modern logistics elements,and encourages coordinated development of urban logistics.

Identifying Spatial Heterogeneity in the Effects of High-Tech Firm Density on Housing Prices:Evidence from Guangdong-Hong Kong-Macao Greater Bay Area,China

Innovation capitalization is a new concept in innovation geography research.Extant research on a city scale has proven that innovation is an important factor affecting housing prices and verified that innovation has a capitalization effect.However,few studies investigate the spatial heterogeneity of innovation capitalization.Thus,case verification at the urban agglomeration scale is needed.Therefore,this study proposes a theoretical framework for the spatial heterogeneity of innovation capitalization at the urban agglomeration scale.Examining the Guangdong-Hong Kong-Macao Greater Bay Area(GHMGBA),China as a case study,the study investigated the spatial heterogeneity of the influence of high-tech firms,representing innovation,on housing prices.This work verified the spatial heterogeneity of innovation capitalization.The study constructed a data set influencing housing prices,comprising 11 factors in 5 categories(high-tech firms,convenience of living facilities,built environment,the natural environment,and the fundamentals of the districts)for 419 subdistricts in the GHMGBA.On the global scale,the study finds that high-tech firms have a significant and positive influence on housing prices,with the housing price increasing by 0.0156%when high-tech firm density increases by 1%.Furthermore,a semi-geographically weighted regression(SGWR)analysis shows that the influence of high-tech firms on housing prices has spatial heterogeneity.The areas where high-tech firms have a significant and positive influence on housing prices are mainly in the GuangzhouFoshan metropolitan area,western Shenzhen-Dongguan,north-central Zhongshan-Nansha district,and Guangzhou—all areas with densely distributed high-tech firms.These results confirm the spatial heterogeneity of innovation capitalization and the need for further discussion of its scale and spatial limitations.The study offers implications for relevant GHMGBA administrative authorities for spatially differentiated development strategies and housing policies that consider the role of innovation in successful urban development.

Influencing Factors of Housing Sales Vacancy in the Guangzhou Metropolitan Area,China

In this paper,nine indicators selected from three perspectives(convenience,environmental and location characteristics)and three regression models(OLS,SLM and SEM)are used to explore the influencing factors of housing sales vacancy in the Guangzhou Metropolitan Area,China.The results show that subway accessibility,peripheral aversion municipal facilities and distance from the CBD(Central Business District)are consistent with theoretical expectations.Subway accessibility is negatively correlated with the housing sales vacancy rates,while peripheral aversion municipal facilities and distance from the CBD are positively correlated with housing vacancy rates.

Spatial Pattern of Housing Sales Vacancy in Guangzhou’s Urban District, China

Housing vacancy can reflect the destocking degree of the real estate market.Based on the data of 57 opened residential quarters(46,622 units)from 2015 to 2018,this paper constructs a calculation formula of the sales vacancy rate and then analyzes the spatial pattern in Guangzhou’s urban district.The results show that there is obvious differentiation in the spatial pattern of housing sales vacancy in Guangzhou’s urban district,showing a higher spatial pattern in the old area and urban district and a lower spatial pattern in the core area.Subdistricts with high vacancy rates are mainly located in the east of the old area,the south and east of the urban district and near Baiyun Mountain in the north.

Rental Location Choice Characteristics and Tendencies of Migrants in Guangzhou,China

The inner-urban residential location choice is a topic of continuing interest in urban geography.However,not much research has been done on migrants’rental location choices.Based on data from a questionnaire completed by 276 migrant renters in Guangzhou,this paper analyzes the demographics and social class characteristics of migrants,and the condition and location of housing preferred by this population.The results show that the migrants in Guangzhou mainly rent in the Center Business District(CBD)area(Tianhe District)and Huangpu,Panyu and Haizhu districts.The main reason for this choice of location choices is the houses’convenience to their workplaces.A second reason is that nearby subways make travel convenient,for consumption and daily life,for children to go to school,and for access to large shopping centers/malls.

Evaluation of Three-dimensional Urban Expansion: A Case Study of Yangzhou City, Jiangsu Province, China

With rapid urban development in China in the last two decades, the three-dimensional(3D) characteristic has been the main feature of urban morphology. However, the vast majority of researches of urban growth have focused on the planar area(two-dimensional(2D)) expansion. Few studies have been conducted from a 3D perspective. In this paper, the 3D urban expansion of the Yangzhou City, Jiangsu Province, China from 2003 to 2012 was evaluated based on Geographical Information System(GIS) tools and high-resolution remote sensing images. Four indices, namely weighted average height of buildings, volume of buildings, 3D expansion intensity and 3D fractal dimension are used to quantify the 3D urban expansion. The weighted average height of buildings and the volume of buildings are used to illustrate the temporal change of the 3D urban morphology, while the other two indices are used to calculate the expansion intensity and the fractal dimension of the 3D urban morphology. The results show that the spatial distribution of the high-rise buildings in Yangzhou has significantly spread and the utilization of the 3D space of Yangzhou has become more efficient and intensive. The methods proposed in this paper laid a foundation for a wide range of study of 3D urban morphology changes.

Impact of the Built Environment on the Spatial Heterogeneity of Regional Innovation Productivity:Evidence from the Pearl River Delta,China

With the global economy increasingly dependent on innovation,urban discourse has shifted to consider what kinds of spatial designs may best nurture innovation.We examined the relationship between the built environment and the spatial heterogeneity of regional innovation productivity(RIP)using the example of China's Pearl River Delta(PRD).Based on a spatial database of 522546 patent data from 2017,this study proposed an innovation-based built environment framework with the following five aspects:healthy en-vironment,daily interaction,mixed land use,commuting convenience,and technology atmosphere.Combining negative binomial regression and Geodetector to examine the impact of the built environment on RIP,the results show that the spatial distribution of innovation productivity in the PRD region is extremely uneven.The negative binomial regression results show that the built environment has a significant impact on the spatial differentiation of RIP,and,specifically,that healthy environment,mixed land use,commuting convenience,and technology atmosphere all demonstrate significant positive impacts.Meanwhile,the Geodetector results show that the built environment factor impacts the spatial heterogeneity of RIP to varying degrees,with technology atmosphere demonstrating the greatest impact intensity.We conclude that as regional development discourse shifts focus to the knowledge and innovation economy,the innovation-oriented design and updating of built environments will become extremely important to policymakers.

Residents'environmental conservation behaviour in the mountain tourism destinations in China:Case studies of Jiuzhaigou and Mount Qingcheng

This study aimed at gaining an understanding of the formation of residents' Environmental Conservation Behaviour(ECB) to promote sustainable tourism development in Chinese mountain areas. In particular, a theoretical framework was constructed by merging residents' mountain attachment and their environmental values,and awareness of environmental consequences based on the Cognition Behaviour Theory. This research sampled 642 residents with convenience sampling method in Jiuzhaigou and Mount Qingcheng, and structural equation modelling analysis was conducted to identify the relationships among the above variables. Results verified that mountain attachment affected people's awareness of environmental consequences, which then affected their ECB.Environmental values and mountain attachment directly and positively influenced ECB. Moreover,awareness of environmental consequences played the most prominent role in predicting ECB among all the predictors in this study. In all, this study derived several significant implications which can not only contribute to environmental management policies in tourism field but also help to improve the levels of the antecedents of residents' ECB and promote sustainable tourism development in Chinese mountain areas.

Retrieval of Atmospheric Horizontal Visibility by Statistical Regression from NOAA/AVHRR Satellite Data

Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during January 2001 to December 2002, the spectral characters associated with visibility were investigated. Successful retrieval of visibility from multichannel NOAA/AVHRR data was performed using the principal component regression (PCR) method. A sample of retrieved visibility distribution was discussed with a sea fog process. The correlation coefficient between the observed and retrieved visibility was about 0.82, which is far higher than the 99.[KG-*7]9% confidence level by statistical test. The rate of successful retrieval is 94.98% of the 458 cases during 2001-2002. The error distribution showed that high visibilities were usually under-estimated and low visibilities were over-estimated and the relative error between the observed and retrieved visibilities was about 21.4%.

Study on the Development of Under-forest Economy in Guangdong Mountain Areas

From the origin and connotation of the under-forest economy,this paper analyzed plight of the development of under-forest economy in Guangdong mountain areas. It discussed benefits of under-forest economy,favorable conditions and development path of under-forest economy in Guangdong mountain areas. Results indicate that developing under-forest economy is an essential path for realizing green growth and coordinated development of Guangdong mountain areas. However,due to terrain,market,management and technology reasons,the under-forest economy is still not fully developed in Guangdong mountain areas. The development path of under-forest economy suitable for Guangdong mountain areas should be based on ecological protection and oriented towards maximizing ecological,economic and social benefits. Guangdong mountain areas have in-born natural and resource advantages,economic pull of development mode and market demand change,and favorable condition of policy encouragement for development of under-forest economy. Finally,it came up with recommendations for development of under-forest economy in Guangdong mountain areas from development mode,industrial distribution and development direction.

Spatial Distribution Pattern and Han Subgroup Characteristics of Traditional Villages in Guangdong

A total of 126 traditional villages in Guangdong were selected for research to analyze their spatial distribution pattern, spatial autocorrelation, and Han subgroup characteristics through the spatial analysis with GIS. The results showed that the traditional villages in Guangdong were distributed compactly, which was similar to that in other provinces; on the prefecture-level city scale, they were mainly distributed in Meizhou, Qingyuan, Zhanjiang, and Zhaoqing, showing a central distribution; on the regional scale, they were mainly distributed in northern Guangdong and the Pearl River Delta, indicating an unbalanced distribution; their density of spatial distribution showed a significant difference with a provincial distribution density of 0.59 per thousand km^2 and the highest distribution density of 2.14 per thousand km^2; there were four gathering areas accommodating many traditional villages, namely Meizhou-Chaoshan area, Guangfo-Dongguan area, Leizhou in Zhanjiang, and Lianzhou in Qingyuan; the spatial distribution of traditional villages, which presented a pattern of hot spot—sub-hot spot—sub-cold spot—cold spot, had a significant global spatial autocorrelation, and areas in similar sizes were tending towards gathering; traditional villages in Guangdong belonged to the Cantonese-speaking group and Hakka-speaking group with a density of 0.59 per thousand km^2 and 0.48 per thousand km^2 respectively, and Han subgroup with the highest distribution density was the minority areas of 1.31 per thousand km^2, followed by Shaozhou dialect area with a density of 1.00 per thousand km^2.

THE HOLOCENE ALONG THE COAST OF HAINAN ISLAND, CHINA

Based on the new data of the Quaternary along the coast of Hainan Island, China, this paper puts forward that the Holocene in Hainan Island can be divided into four formations: Wanning formation (Q41), Sanya formation (Q42-1), Qiongshan formation (Q42-2) and Ledong formation (Q43). Spore-pollen analysis shows that there are 6 spore-pollen zones existed, reflecting two cycles of climatic fluctuation from warm-dry to hot-humid. The climax of hot-humid period occurred 6,000-5,000 years B.P.. Based on the 14C dating data of the 38 samples representing the positions of ancient sea level, a breakthrough curve representing the sea level change during the Holocone is obtained, in which , a sea level change caused by tectonic movement is subtracted. Two cycles of rise-drop of sea level with three periods of high sea level were found. The period with the highest sea level is some 6,000-5,000 years B.P.. According to the rise-drop rate of sea level, four periods of the sea level change can be distinguished in

The Quaternary climate records of coral reef in the tropical zone of China

The analysis results of oxygen isotopes, carbon isotopes, geochemistry and the growth belt of reef coral etc. for some profiles of coral reef show that the basic pattern of climatic fluctuation during the Quaternary period can be reflected by coral reef. The trend of climate change was from cooling to warming during the Early Pleistocene with at least four cycles, and from warming to cooling with at least seven cycles during the Middle Pleistocene. The late Pleistocene is a period of the Quaternary which shows the most frequent variation of climate but generally two main cycles of warming–cooling can be seen. During the Holocene the climate went through a process of warming-rise in temperature-drop in temperature. During the historical period there were four cycles of cooling-warming at 1700 a BP. During the last 200 years climate change is characterized by two stages; a positive deviation in the former 100 years, and a negative deviation in the latter 100 years with general warming trend.

High-efficiency calculation method for watershed rainfallrunoff routing using one-dimensional dynamic wave equations

Efficiency in solving the Saint-Venant equations for watershed rainfall-runoff routing is important in flood hydrology. This paper presents a high-efficiency numerical solution of one-dimensional dynamic wave equations(HEDWE) for watershed rainfall-runoff routing, in which the full momentum equation is written as a quadratic equation with only one unknown variable Q, water depth is derived from the continuity equation using the two-step predictorcorrector method, and the discrete scheme is the explicit upwind scheme. The results of numerical tests showed the HEDWE approach has several major advantages. 1) It is a stable numerical method, even for an initially dry area. 2) Its computational efficiency is higher than 4.76E+05 times/s. 3) It can be used for overland flow, river flow, and combinations thereof. The primary disadvantages of the HEDWE approach are its unsuitability for rapidly varying flow, such as dam-break floods.

The study of estimation method of broadband emissivity from EOS/MODIS data

The broadband emissivity is an important parameter for estimating the energy balance of the Earth.This study focuses on estimating the window(8-12 |xm) emissivity from the MODIS(moderate-resolution imaging spectroradiometer) data,and two methods are built.The regression method obtains the broadband emissivity from MOD11B1 5KM product,whose coefficient is developed by using 128 spectra,and the standard deviation of error is about 0.0118 and the mean error is about0.0084.Although the estimation accuracy is very high while the broadband emissivity is estimated from the emissivity of bands 29,31 and 32 obtained from MOD11B1 5KM product,the standard deviations of errors of single emissivity in bands 29,31,32 are about 0.009 for MOD11B1_5KM product,so the total error is about 0.02 and resolution is about 5km×5km.A combined radiative transfer model with dynamic learning neural network method is used to estimate the broadband emissivity from MODIS 1B data.The standard deviation of error is about 0.016,the mean error is about0.01,and the resolution is about 1km ×1km.The validation and application analysis indicates that the regression is simpler and more practical,and estimation accuracy of the dynamic learning neural network method is higher.Considering the needs for accuracy and practicalities in application,one of them can be chosen to estimate the broadband emissivity from MODIS data.

Analysis of Design Rainstorm Hydrograph Based on Asymmetrical Extreme Value Copula

In this paper,the maximum 1-hour rainfall( rain peak),the maximum 6-hour rainfall and the maximum 24-hour rainfall in the Caojiang River basin from 1967 to 2013 were taken as samples. The typical typhoon rainstorm hydrograph of joint distribution of rainfall in three periods was constructed based on the asymmetric Archimedean Gumbel-Hougaard extreme value Copula. The main conclusions were as follows:( 1) the design rainstorm value in the Caojiang River basin calculated by using the joint distribution of rainfall in three periods was larger than the design rainstorm value of the joint distribution in two periods and that of a single period. The design rainstorm process hydrograph amplified at the same frequency had the optimal overall effect,which provided a new idea and method for studying the design rainfall patterns.( 2) According to the maximum 24-hour rainfall,the risk rate of the multi-peak rainstorm process that the main peak was in the back was the highest,and the constructed typical design rainstorm process hydrograph was the most representative.( 3) " OR" joint return period of rainfall combination in three periods as the design criteria of a watershed was applicable to responding to the risk of rainfall and flood in this watershed.

A Neural Network Method for Monitoring Snowstorm: A Case Study in Southern China

It has been observed that low temperature, rainfall, snowfall, frost have never occurred over the past 50 years in the southern China, and weather in this area is very complex, so the monitoring equipments are few. Optical and thermal infrared remote sensing is influenced much by clouds, so the passive microwave Advanced Microwave Scanning Radiometer-Earth Observing System(AMSR-E) data are the best choice to monitor and analyze the development of disaster. In order to improve estimation accuracy, the dynamic learning neural network was used to retrieve snow depth. The difference of brightness temperatures of TB18.7V and TB36.5V, TB18.7H and TB36.5H, TB23.8V and TB89 V, TB23.8H and TB89 H are made as four main input nodes and the snow depth is the only one output node of neural network. The mean and the standard deviation of retrieval errors are about 4.8 cm and 6.7 cm relative to the test data of ground measurements. The application analysis indicated that the neural network can be utilized to monitor the change of snow intensity distribution through passive microwave data in the complex weather of the southern China.

THE OPEN ECONOMIC COASTAL ZONE IN EASTERN CHINA:ITS FORMATION CONDITIONS,AREAL DIFFERENTIATION AND DEVELOPMENT ORIENTATION

The advantages of the eastern coastal economic zone and its role in the country’s economic construction as well as its relationship with the western zone are discussed.