Socio-Spatial Variations in Commuting Patterns in Suburban Beijing

2019 ◽  
Vol 45 (4) ◽  
pp. 523-543 ◽  
Author(s):  
Wei Zheng ◽  
Cecilia Wong ◽  
Miao Qiao
Keyword(s):  
Cultural Context ◽  
Latent Class ◽  
Spatial Scales ◽  
Spatial Variations ◽  
Statistical Testing ◽  
Metropolitan Region ◽  
Gis Mapping ◽  
Rapid Urbanization ◽  
Time Distance ◽  
Commuting Patterns

With rapid urbanization and suburbanization in China, there is clear evidence of the decoupling of home-work locations in cities which is in contrast to the socialist danwei system where workers were housed in workplace compounds. This paper examines the diverse commuting patterns of suburban neighbourhoods in the Beijing metropolitan region. The research first examines the relationship between the characteristics of commutes in terms of time, distance, and mode, and the socio-economic attributes of residents. The analysis allows us to examine how different socio-economic groups, via latent class analysis, are often spatially concentrated in marginalized neighbourhoods, and further disadvantaged in their commuting experience. The socio-spatial variations in commuting patterns are analysed via GIS mapping analysis, statistical testing, and multiple regression analysis. Major variations were found in the commuting patterns in terms of time, distance and mode across different socioeconomic groups and across various suburban neighbourhood types. The results from regression models further suggest that personal resources have the strongest influence on commuting time but less so on distance, regardless of the type of neighbourhoods in which they live. The findings call for integrative planning and major transport measures, at different spatial scales, to shape commuting behaviour. Despite the unique institutional and cultural context of China, the lessons learnt from the need to have integrative strategic planning are relevant to other cities, and especially those in the developing world which are undergoing rapid urbanization.

scholarly journals Examination of Heterogeneous Societies

2016 ◽  
Vol 48 (1) ◽  
pp. 39-57 ◽  
Author(s):  
Fumiko Kano Glückstad ◽  
Mikkel N. Schmidt ◽  
Morten Mørup
Keyword(s):  
Cultural Context ◽  
Latent Class ◽  
Cultural Analysis ◽  
Cross Cultural ◽  
Relational Model ◽  
Response Patterns ◽  
World Value Survey ◽  
Applied Model ◽  
Similarities And Differences ◽  
Cultural Data

The recent development of data analytic tools rooted around the Multi-Group Latent Class Analysis (MGLCA) has enabled the examination of heterogeneous datasets in a cross-cultural context. Although the MGLCA is considered as an established and popular cross-cultural data analysis approach, the infinite relational model (IRM) is a new and disruptive type of unsupervised clustering approach that has been developed recently by cognitive psychologists and computer scientists. In this article, an extended version of the IRM coined the multinominal IRM—or mIRM in short—is applied to a cross-cultural analysis of survey data available from the World Value Survey organization. Specifically, the present work analyzes response patterns of the Portrait Value Questionnaire (PVQ) representing Schwartz’s 10 basic values of Japanese and Swedes. The applied model exposes heterogeneous structures of the two societies consisting of fine-grained response patterns expressed by the respective subpopulations and extracts latent typological structures contrasting and highlighting similarities and differences between these two societies. In the final section, we discuss similarities and differences identified between the MGLCA and the mIRM approaches, which indicate potential applications and contributions of the mIRM and the general IRM framework for future cross-cultural data analyses.

scholarly journals Understanding commuting patterns and changes: Counterfactual analysis in a planning support framework

2020 ◽  
Vol 47 (8) ◽  
pp. 1440-1455 ◽  
Author(s):  
Tianren Yang
Keyword(s):  
Travel Demand ◽  
Spatial Scales ◽  
Predictive Ability ◽  
Mobile Phone Data ◽  
City Centre ◽  
Planning Support ◽  
Economic Framework ◽  
City Regions ◽  
Commuting Patterns ◽  
Changes Over Time

In order to contain commuting distance growth and relieve traffic burden in mega-city regions, it is essential to understand journey-to-work patterns and changes in those patterns. This research develops a planning support model that integrates increasingly available mobile phone data and conventional statistics into a theoretical urban economic framework to reveal and explain commuting changes. Base-year calibration and cross-year validation were conducted first to test the model’s predictive ability. Counterfactual simulations were then applied to help local planners and policymakers understand which factors lead to differences in commuting patterns and how different policies influence various categorical zones (i.e. centre, near suburbs, sub-centres and far suburbs). The case study of Shanghai shows that jobs–housing co-location results in shorter commutes and that policymakers should be more cautious when determining workplace locations as they play a more significant role in mitigating excessive commutes and redistributing travel demand. Furthermore, land use and transport developments should be coordinated across spatial scales to achieve mutually beneficial outcomes for both the city centre and the suburbs. Coupled with empirical evidence explaining commuting changes over time, the proposed model can deliver timely and situation-cogent messages regarding the success or failure of planned policy initiatives.

Developing the use of convolutional neural networking in benthic habitat classification and species distribution modelling

2020 ◽  
Author(s):  
Jennifer I Fincham ◽  
Christian Wilson ◽  
Jon Barry ◽  
Stefan Bolam ◽  
Geoffrey French
Keyword(s):  
Species Distribution ◽  
Spatial Scales ◽  
Species Distribution Modelling ◽  
Statistical Testing ◽  
Training Dataset ◽  
Benthic Habitat ◽  
Distribution Modelling ◽  
Habitat Classification ◽  
Fish And Shellfish ◽  
Multibeam Data

Abstract Management of the marine environment is increasingly being conducted in accordance with an ecosystem-based approach, which requires an integrated approach to monitoring. Simultaneous acquisition of the different data types needed is often difficult, largely due to specific gear requirements (grabs, trawls, and video and acoustic approaches) and mismatches in their spatial and temporal scales. We present an example to resolve this using a convolutional neural network (CNN), using ad hoc multibeam data collected during multi-disciplinary surveys to predict the distribution of seabed habitats across the western English Channel. We adopted a habitat classification system, based on seabed morphology and sediment dynamics, and trained a CNN to label images generated from the multibeam data. The probability of the correct classification by the CNN varied per habitat, with accuracy above 60% for 85% of habitats in a training dataset. Statistical testing revealed that the spatial distribution of 57 of the 100 demersal fish and shellfish species sampled across the region during the surveys possessed a non-random relationship with the multibeam-derived habitats using CNN. CNNs, therefore, offer the potential to aid habitat mapping and facilitate species distribution modelling at the large spatial scales required under an ecosystem-based management framework.

scholarly journals Scale and spatial representation: Restructuring of administrative boundary and GIS mapping in Bajhang district, Nepal

2019 ◽  
Vol 12 ◽  
pp. 25-40
Author(s):  
Shobha Shrestha
Keyword(s):  
Spatial Scale ◽  
Data Aggregation ◽  
Spatial Representation ◽  
Census Data ◽  
Spatial Scales ◽  
Data Classification ◽  
Analysis Data ◽  
Gis Mapping ◽  
Classification Methods ◽  
Administrative Boundary

 Census and other socio-economic survey data collected at household and settlement level are aggregated and results are presented for specific administrative units. The wide and increasing availability of census and socio-economic data, tools like GIS with an ease to use and advances in methodology has allowed increasing and refined GIS mapping of census variables. However, it is less emphasized that the result of analysis and presentation is always dependent on the unit of analysis. Data aggregation, choice of data classification method and spatial scale all have effect on mapping result. When administrative boundaries are restructured, it necessitates the aggregation of census data of one administrative level to another. In this context, the current paper explores the scale and zoning effect (changing boundary, changing number of units and data aggregation) on mapping census data. It explores the effect of four data classification methods at two spatial scales. Secondary data sources like local administrative boundary of Bajhang district and economically active population in agriculture is selected as representative census variable for mapping. GIS tool is applied for data mapping and analysis. The study found the higher calculated correlation value (0.88) for the restructured spatial units. The distribution of number of spatial units varied significantly between four data classification methods while plotted against the old boundary but there was not much variation in case of newly restructured boundary. The study found that zoning particularly, from smaller to larger units has blurred the spatial pattern visualization leading to a loss of the preferential information. The study concludes that the restructuring of administrative boundaries into larger unit has simplified the detail for spatial representation and has introduced additional generalization. For policy level analysis, use of data available at one level of the spatial unit when aggregated to higher level should be analyzed carefully using different data classification methods and visualization tools because scaled spatial representation matters in planning and policy aspect. It is meaningful to analyze data at different spatial scale to visualize and identify spatial variation.

scholarly journals A critical look at spatial scale choices in satellite-based aerosol indirect effect studies

2010 ◽  
Vol 10 (23) ◽  
pp. 11459-11470 ◽  
Author(s):  
B. S. Grandey ◽  
P. Stier
Keyword(s):  
Radiative Forcing ◽  
Spatial Scales ◽  
Cloud Droplet ◽  
Spatial Variations ◽  
Opposite Pattern ◽  
Cloud Properties ◽  
Methodological Errors ◽  
Albedo Effect ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Analysing satellite datasets over large regions may introduce spurious relationships between aerosol and cloud properties due to spatial variations in aerosol type, cloud regime and synoptic regime climatologies. Using MODerate resolution Imaging Spectroradiometer data, we calculate relationships between aerosol optical depth τa derived liquid cloud droplet effective number concentration Ne and liquid cloud droplet effective radius re at different spatial scales. Generally, positive values of dlnNedlnτa are found for ocean regions, whilst negative values occur for many land regions. The spatial distribution of dlnredlnτa shows approximately the opposite pattern, with generally postive values for land regions and negative values for ocean regions. We find that for region sizes larger than 4° × 4°, spurious spatial variations in retrieved cloud and aerosol properties can introduce widespread significant errors to calculations of dlnNedlnτa and dlnredlnτa. For regions on the scale of 60° × 60°, these methodological errors may lead to an overestimate in global cloud albedo effect radiative forcing of order 80% relative to that calculated for regions on the scale of 1° × 1°.

A Novel Indicator for Assessing the Spatial Sustainability of Cities in Developing Countries - A Case Study of Xi’an City

2012 ◽  
Vol 616-618 ◽  
pp. 1335-1342 ◽  
Author(s):  
Xiao Hui Ding ◽  
Shuo Xin Zhang ◽  
Wei Zhou Zhong ◽  
Yu Jiang
Keyword(s):  
Landscape Ecology ◽  
Spatial Scales ◽  
Urban Expansion ◽  
Negative Effects ◽  
Rapid Urbanization ◽  
Social Ecological Systems ◽  
Sensing Technology ◽  
The City ◽  
Geographical Dimension

The geographical dimension of urbanization is of major importance in depicting the influences of urbanization on the development of a city, since complex social-ecological systems interact in a multitude of ways at many spatial scales across time. This research introduced an indicator for assessing the spatial sustainability of a city from the perspective of landscape ecology, to provide a reasonable way for quantifying the spatial dynamic of the urban area of a city and how close the pattern of urban expansion close to a ‘compact’ way. A case study has been done in Xi’an. With the application of remote sensing technology, landscape ecology and other necessary software, the spacial sustainability of Xi’an from 1988 to 2010 were calculated, the rapid urbanization in Xi’an has significantly promoted the spatial sustainability of city from 1988 to 2000 and 2006 to 2010, whereas exerted negative effects on the spatial sustainability of the city from 2000 to 2006.

scholarly journals Household Level Consumption and Ecological Stress in an Urban Area

Urban Science ◽  
2018 ◽  
Vol 2 (3) ◽  
pp. 56 ◽  
Author(s):  
Md. Khan ◽  
Muhammad Uddin
Keyword(s):  
Natural Environment ◽  
Ecological Footprint ◽  
Direct Method ◽  
Household Consumption ◽  
Policy Formulation ◽  
Gis Mapping ◽  
Mapping Technique ◽  
Human Consumption ◽  
Rapid Urbanization ◽  
Household Level

Rapid urbanization and human consumption are continuously threatening the balances of natural environmental systems. This study investigated the increasing stress on the natural environment from household consumption at the neighborhood level. We collected and analyzed household-level data of Ward 24 of the Khulna City Corporation (KCC) area to quantify and represent household consumption and entrenching stresses on the natural environment. We followed the component and direct method to determine the ecological footprint (demand). We also derived the biocapacity (supply) from the available bioproductive lands of the study area. Thus, the gap between demand and supply was identified and represented as a stress area through a Geographic Information System (GIS) mapping technique. We found that the per capita ecological footprint accounts for Ward 24 were about 0.7161 gha/capita for the year 2015. Moreover, the biocapacity for the same year was determined as 0.0144 gha/capita for Ward 24. The ecological demand for the household-based consumption of Ward 24 exceeded its ecological capacity by 49.73 times. We found that Ward 24 would require an area that was 162 times larger in order to support the present level of resource demand and waste sequestration. These study findings can play an essential role in policy formulation, ensuring the practices of environmental justice at the local scale.

scholarly journals The Trade-Offs between Supply and Demand Dynamics of Ecosystem Services in the Bay Areas of Metropolitan Regions: A Case Study in Quanzhou, China

Land ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 22
Author(s):  
Wei Shui ◽  
Kexin Wu ◽  
Yong Du ◽  
Haifeng Yang
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Supply And Demand ◽  
Metropolitan Region ◽  
Ecological Security ◽  
Rapid Urbanization ◽  
Bay Area ◽  
Trade Offs ◽  
Supply Capacity ◽  
Consumption Demand

Bay areas are endowed with unique sea and land resources, location advantages, and high environmental carrying capacities. The rapid urbanization process has intensified the demand for limited natural resources, leading to a series of problems in coastal zones such as land use conflicts and the degradation of ecosystem services. Taking Quanzhou, a bay city in a metropolitan region, as an example, this paper established an accounting model of ecosystem services supply and consumption demand based on multisource data (meteorological site data, land use data and statistical data). We estimated the supply capacity and consumption demand of provisioning services, regulating services, and cultural services in Quanzhou from 2005 to 2015. In addition, the supply and demand of ecosystem services were simulated for 2030 under different scenarios. The results showed that the supply capacity of ecosystem services in Quanzhou was greater than the demand in general, but the supply-demand difference showed a gradual decrease. The high-value areas of supply capacity were concentrated in the upstream basin in the non-bay area, while the high-value areas of consumption demand were located downstream of the river basin in the bay area. The supply-demand difference in the bay area was negative, indicating that it was in a state of supply-demand imbalance and that the ecological security was under threat. Among the three simulated scenarios in 2030, the balance between supply and demand declined compared with the results of 2015, with the most serious decline in the natural scenario. The method to quantify the evolution of spatial and temporal patterns in supply and demand of ecosystem services could provide a decision-making reference for natural resource management in Quanzhou. This is conducive to the improvement and establishment of urban ecological security research systems, especially in bay areas that are lacking research.

scholarly journals Urban expansion and neighbourhood commuting patterns in the Beijing metropolitan region: A multilevel analysis

Urban Studies ◽  
2019 ◽  
Vol 57 (13) ◽  
pp. 2773-2793
Author(s):  
Cecilia Wong ◽  
Wei Zheng ◽  
Miao Qiao
Keyword(s):  
Urban Expansion ◽  
Explanatory Power ◽  
Multilevel Modelling ◽  
Interactive Effects ◽  
Metropolitan Region ◽  
The Novel ◽  
Commuting Flows ◽  
Home Work ◽  
Commuting Patterns ◽  
Modelling Approach

This study adopts a spatial perspective to analyse the complex commuting patterns of the Beijing metropolitan region. By combining measures of the built environment, neighbourhood characteristics and development time periods, a four-fold neighbourhood classification was derived by cluster analysis to reflect different urbanisation contexts. Commuting flows were mapped to illustrate the spatial mismatch of home–work locations during the rampant urbanisation process. The novel use of a multilevel modelling approach shows how individual socio-economic attributes and neighbourhood factors, and their interactive effects, explain the varied commuting patterns. The cross-level interactions of variables highlight the predominant influence of individual attributes, which also interact with locational conditions of neighbourhood with differential explanatory power, on commuting patterns.

scholarly journals Observations on spatial variations of the Sr I 4607 Å scattering polarization signals at different limb distances with ZIMPOL

2019 ◽  
Vol 630 ◽  
pp. A67 ◽  
Author(s):  
Sajal Kumar Dhara ◽  
Emilia Capozzi ◽  
Daniel Gisler ◽  
Michele Bianda ◽  
Renzo Ramelli ◽  
...  
Keyword(s):  
Spectral Line ◽  
Spatial Scales ◽  
Solar Spectrum ◽  
Spatial Variations ◽  
Stokes Parameters ◽  
Small Scale ◽  
Solar Photosphere ◽  
Local Anisotropy ◽  
Polarization Signal ◽  
The Continuum

Context. The Sr I 4607 Å spectral line shows one of the strongest scattering polarization signals in the visible solar spectrum. The amplitude of this polarization signal is expected to vary at granular spatial scales, due to the combined action of the Hanle effect and the local anisotropy of the radiation field. Observing these variations would be of great interest because it would provide precious information on the small-scale activity of the solar photosphere. At present, few detections of such spatial variations have been reported. This is due to the difficulty of these measurements, which require combining high spatial (∼0.1″), spectral (≤20 mÅ), and temporal resolution (< 1 min) with increased polarimetric sensitivity (∼10−4). Aims. We aim to detect spatial variations at granular scales of the scattering polarization peak of the Sr I 4607 Å line at different limb distances, and to study the correlation with the continuum intensity. Methods. Using the Zurich IMaging POLarimeter (ZIMPOL) system mounted at the GREGOR telescope and spectrograph in Tenerife, Spain, we carried out spectro-polarimetric measurements to obtain the four Stokes parameters in the Sr I line at different limb distances, from μ = 0.2 to μ = 0.8, on the solar disk. Results. Spatial variations of the scattering polarization signal in the Sr I 4607 Å line, with a spatial resolution of about 0.66″, are clearly observed at every μ. The spatial scale of these variations is comparable to the granular size. A statistical analysis reveals that the linear scattering polarization amplitude in this Sr I spectral line is positively correlated with the intensity in the continuum, corresponding to the granules, at every μ.

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