In tourism studies, new means of data collection are opening up opportunities for disclosing hidden mobility patterns. This paper aims to analyze and model the tourist flow networks for different lengths of trip on urban scale, using user generated content (UGC) data collated from an open tourism web service. The textual UGC data, with high spatial and temporal resolution, is utilized to construct three tourist flow networks in response to length of trips. Social network analysis and a revised spatial interaction model are deployed for exploring the temporal heterogeneity in the tourist movements. This empirical study from Nanjing City has further confirmed the power law of distance decay in intraurban tourist mobility. Furthermore, the research reveals temporal variations with length of trip. The paper highlights the role of time in the tourism study through incorporating a temporal dimension into the analyses and taking advantage of the availability of new data.

The inequities in healthcare services between regions, urban and rural, age groups and diverse income groups have been growing rapidly in China. Equal access to basic medical and healthcare services has been recognized as “a basic right of the people” by Chinese government. Spatial accessibility to healthcare facilities has received huge attention in Chinese case studies but been less studied particularly at a county level due to limited availability of high-resolution spatial data. This study is focused on measuring spatial accessibility to healthcare facilities in Deqing County. The spatial inequity between the urban (town) and rural is assessed and three scenarios are designed and built to examine which scenario is instrumental for better reducing the spatial inequity. This study utilizes highway network data, Digital Elevation Model (DEM), location of hospitals and clinics, 2010 census data at the finest level – village committee, residential building footprint and building height. Areal weighting method is used to disaggregate population data from village committee level to residential building cell level. Least cost path analysis is applied to calculate the travel time from each building cell to its closest healthcare facility. Then an integral accessibility will be calculated through weighting the travel time to the closest facility between three levels. The spatial inequity in healthcare accessibility between the town and rural areas is examined based on the coverages of areas and populations. The same method is used to compare three scenarios aimed at reducing such spatial inequity – relocation of hospitals, updates of weighting values, and the combination of both. 50.03 % of residents can reach a county hospital within 15 min by driving, 95.77 % and 100 % within 30 and 60 min respectively. 55.14 % of residents can reach a town hospital within 5 min, 98.04 % and 100 % within 15 and 30 min respectively. 57.86 % of residential building areas can reach a village clinic within 5 min, 92.65 % and 99.22 % within 10 and 15 min. After weighting the travel time between the three-level facilities, 30.87 % of residents can reach a facility within 5 min, 80.46 %% and 99.88 % within 15 and 30 min respectively. The healthcare accessibility pattern of Deqing County has exhibited spatial inequity between the town and rural areas, with the best accessibility in the capital of the county and poorest in the West of the county. There is a high negative correlation between population ageing and healthcare accessibility. Allocation of more advanced medical and healthcare equipment and highly skillful doctors and nurses to village clinics will be an efficient means of reducing the spatial inequity and further consolidating the national medical security system. GIS (Geographical Information Systems) methods have proven successful method of providing quantitative evidence for policy analysis although the data sets and methods could be further improved.

Due to the emergence of new big data technology, mobility data such as flows between origin and destination areas have increasingly become more available, cheaper, and faster. These improvements to data infrastructure have boosted spatial and temporal modeling of OD (origin-destination) flows, which require the consideration of spatial dependence and heterogeneity. Both ordinary least square (OLS) and negative binomial (NB) regression methods have been used extensively to calibrate OD flow models by processing flow data as different types of dependent variables. This paper aims to compare both global and local spatial interaction modeling of OD flows between traditional and geographically weighted OLS (GWOLSR) and NB (GWNBR) modeling methods. From this study with empirical data it is concluded that GWNBR outperforms GWOLSR in reducing spatial autocorrelation and in detecting spatial non-stationarity. Although, it is noted that both local modeling methods show improvement when compared against the equivalent global models.

The data regarding resources and environmental carrying capacities (RECC) are not only the basis for realizing regional sustainable development, but also the core links for major function-oriented zoning practices, which include specific partitioning schemes of spatial units with various geographical functions. Previously, relevant studies were mainly based on the evaluations of single factors. However, the realization of regional function-oriented spatial zoning practices based on comprehensive assessments of RECC has been neglected. This study presented an evaluation index system for RECC based on nine aspects, in accordance with the evaluation elements of the major function-oriented zoning programs which were in place and the characteristics of the study area. Then, by using subjective and objective comprehensive weighting methods, the basic elements were finally integrated, and an accurate spatial distribution pattern of the RECC in China’s Fengxian County was obtained. In addition, based on the construction of a three-dimensional spatial conceptual model, this study was able to finally obtain four specific types of functional partitions in the study areas, and proposed specific development proposals according to the different types of functional zoning from a systemic perspective. It was observed that the RECC had been decreasing from a central built-up area to the surrounding townships, and the spatial distribution patterns were distinctly scattered. In addition, the townships with smaller land scales had more obvious advantages in the RECC. However, fluctuating upward trends were observed after the lowest thresholds had been reached as for the medium or above medium scales. At the same time, in terms of the correlations between the population levels, and gross values and the RECC, fluctuating characteristics were observed. The correlations with the latter had presented S-shape curves and inverted U-shape curves, respectively. Finally, the optimized expansion zone located in the north-central region had taken the greatest percentage among functional zoning classifications, followed by the basic competitive zone in the southwestern section. However, the main construction zone accounted for the smallest proportion, at only 2.065%. Therefore, based on these results, it was concluded that there were certain fluctuating correlations between the RECC and total population levels, economic levels, and land scales. Moreover, the RECC evaluation results were found to gradually decrease after rising to the thresholds under the comprehensive effects of the various factors. This study combined the data of the conceptual model with the RECC evaluation results, in order to obtain a potential geographical functional zoning program for the study area. The results of this study are expected to provide a new analysis perspective for the scientific and sustainable development of small-scale geographic units. Moreover, on the basis of this study’s comprehensive evaluations of the RECC, the directions of regional development can be further clarified.

In this paper, we measured the amount of urban green space (UGS), defined here as park greenery and street greenery, in the Guangzhou Beltway region using remote sensing image data and the green view index (GVI) based on human visual images. We also evaluated the benefits of UGS comprehensively considering park greenery and street greenery within the Guangzhou Beltway region. We then calculated the urban green space score (UGSS) by assessing the amount of street greenery and park greenery and then juxtaposing the score with the population distribution of the region. The results show inequities in the spatial distribution of UGSS values within the Guangzhou Beltway region. The benefit score of street greenery is low. The service area of parks can’t cover the whole study area. The comprehensive benefit score of UGS is composed of two parts, the park greenery score and the street greenery score, but the spatial distribution of UGSS values remains uneven. The UGS benefits enjoyed by one-half of the population of the study area are low, and the UGSS values of the more densely populated areas are not high.

Scale is a fundamental geographical concept and its role in different geographical contexts has been widely documented. The increasing availability of transport mobility data, in the form of big datasets, enables further incorporation of spatial dependencies and non-stationarity into spatial interaction modeling of transport flows. In this paper a newly developed multiscale flow-focused geographically weighted regression (MFGWR) approach has been applied, in addition to global and local Moran I indices of flow data, to model multiscale socio-economic determinants of regional transport flows between counties across the Jiangsu Province in China. The results have confirmed the power of local Moran I of flow data for identifying urban agglomerations and the effectiveness of MFGWR in exploring multiscale processes of spatial interactions. A comparison between MFGWR and flow-focused geographically weighted regression (FGWR) showed that the MFGWR approach can better interpret the heterogeneous processes of spatial interaction.