PATTERNS AND PROBLEMS OF COMMUTING TO PERIPHERAL URBAN WORKPLACES IN SINGAPORE: CASE STUDY OF SINGAPORE AIRLINES' EMPLOYEES

This paper addresses the issue of commuting patterns and problems to workplaces in the urban periphery of Singapore. It is based on a case study of journey-to-work patterns of employees of Singapore Airlines Limited (SIA). The company's headquarters is in Airline House which is situated in the eastern comer of Singapore, a location which suffers from accessibility problems. The paper focuses on mode choice in the journey-to-work and, by means of a questionnaire survey, examines commuting patterns of a sample of Airline House workers in terms of first, the characteristics of the different modes of transportation used; and second, the socio-economic characteristics of workers including factors such as income, gender, occupational status and age. This is followed by a discussion of the problems faced in the daily commutes of workers. Many of these problems such as inconvenient public transport services, traffic congestion and long transit times are representative of those of other peripheral workplaces in Singapore. Based on the findings of the case study, the paper discusses some policy implications of the government's planning efforts to decentralise office activities from the CBD to suburban regions.     

Identification of temporal and spatial variations of water quality in Sanya Bay,China by three-way principal component analysis

A large data set obtained by a 1-year monthly determination of water quality from Sanya Bay, South China Sea, was treated by three-way principal component analysis aimed at exploring the spatial and temporal patterns of water quality in Sanya Bay. Tucker3 model of optimum complexity (2, 2, 1) explaining 33.18% of the data variance, allowed interpretation of the data information in three modes. The model explained spatial and temporal variation trends in terms of water quality variables during the study period. Water quality in sampling station (S2) Sanya River was mainly influenced by Sanya River, and water quality in other stations (S1, S3–S10) were mainly influenced by the waters in South China Sea. The results delineated the mouth of Sanya River as critical from pollution point of view. The dry season from October to the next April and rainy season from May to September have different influences on water quality in Sanya Bay. The information extracted by the three-way models would be very useful to regional agencies in developing a strategy to carry out scientific plans for resource use based on marine system functions.     

Complex adaptive blended learning for higher GIS education: A theory-driven pedagogy moving forward after the pandemic

None of the prior studies implementing blended learning (BL) for GIS education has explored pedagogical theories to support BL design, and none coupled blended GIS learning practice with theories. Based on the theoretical framework of complex adaptive blended learning system (CABLS), this article presents a holistic and systematic view of BL for higher GIS education (termed as CABLS-GIS), where its key components are tightly integrated as an integral whole. The framework was implemented for an introductory-level GIS course to empirically evaluate the effectiveness of a BL design from students' perspectives. Most students involved in the implementation agreed that the BL enhanced their learning outcomes. They were mostly positive about the BL and motivated to use the BL materials. Incorporating more BL materials, especially practical ones, and active learning activities were suggested by them. A few negative comments about the BL suggested a thorough consideration of individual learners' characteristics.     

Identification of coastal water quality by statistical analysis methods in Daya Bay, South China Sea

In this paper, cluster analysis (CA), principal component analysis (PCA) and the fuzzy logic approach were employed to evaluate the trophic status of water quality for 12 monitoring stations in Daya Bay in 2003. CA grouped the four seasons into four groups (winter, spring, summer and autumn) and the sampling sites into two groups (cluster DA: S1, S2, S4-S7, S9 and S12 and cluster DB: S3, S8, S10 and S11). PCA identified the temporal and spatial characteristics of trophic status in Daya Bay. Cluster DB, with higher concentrations of TP and DIN, is located in the western and northern parts of Daya Bay. Cluster DA, with the low Secchi, is located in the southern and eastern parts of Daya Bay. The fuzzy logic approach revealed more information about the temporal and spatial patterns of the trophic status of water quality. Chlorophyll a, TP and Secchi may be major factors for deteriorating water quality.     

Using chemometrics to evaluate anthropogenic effects in Daya Bay, China

In this work, we have monitored 12 stations to study the effects caused by natural, marine and anthropogenic activities on water quality in Daya Bay, China. Results show that the N:P ratios are 71.54, 41.29, 81.50 and 98.27 in winter, spring, summer and autumn, respectively. Compared with the data of the past 20 years, the atomic N:P ratios have increased, indicating increased potential for P limitation; the atomic Si:N ratios have decreased; the nutrient structure has substantially changed over a period of 20 years. These findings show that the nutrient structure may be related to anthropogenic influence. The data matrix has been built according to the results, which were analyzed by principal component analysis (PCA). This analysis extracted the first four principal components (PC), explaining 73.58% of the total variance of the raw data. PC1 (25.53% of the variance) is associated with temperature, salinity and nitrate. PC2 (21.64% of the variance) is characterized by dissolved oxygen and silicate. PC3 (15.91% of the variance) participates mainly by nitrite (NO₂-N) and ammonia (NH₄-N). PC4 explaining 10.50% of the variance is mainly contributed by parameters of organic pollution (dissolved oxygen, 5-day biochemical oxygen demand and chemical oxygen demand).PCA has found the important factors that can describe the natural, marine and anthropogenic influences. Temperature and salinity are important indicators of natural and marine characters in this bay. The northeast monsoons from October to April and southwest monsoons from May to September have important effects on the waters in Daya Bay. It has been demonstrated that anthropogenic activities have significant influence on nitrogen form character. In spatial pattern, a marine aquaculture area and a non-aquaculture area are widely identified by the scores of stations. In seasonal pattern, dry and wet season characters have been demonstrated.     

Identification of water quality and zooplankton characteristics in Daya Bay, China, from 2001 to 2004

Data collected from 12 marine monitoring stations in Daya Bay from 2001 to 2004 reveal a substantial change in ecological environment in this region. Cluster analysis based on water quality and zooplankton results divided stations into three clusters: Cluster I consisted of stations S1, S2 and S6 in the south part of Daya Bay; Cluster II consisted of stations S3, S8 and S11 in the cage culture areas in the southwest part, the northwest part near Aotou harbor and the northeast part near the Fanhe harbor of Daya Bay; Cluster III consisted of stations S4, S5, S7, S9, S10 and S12 that were in southwest, the middle and northeast parts of Daya Bay. Bivariate correlations between zooplankton biomass and the major physical and nutrient variables were evaluated for all stations. The zooplankton biomass in all stations correlated positively with salinity, pH, secchi, NO₃-N, NH₄-N, TIN/PO₄-P and SiO₃-Si/PO₄-P, and negatively correlated with temperature, DO, COD, NO₂-N and TIN, PO₄-P, SiO₃-Si and BOD₅. Factors analysis shows high positive loading salinity, secchi and NH₄-N of three clusters, which indicates that all stations of the three clusters were primarily grouped according to their respective nutrient conditions. The results of multivariate statistical analysis revealed that temperature, DO, TIN and BOD₅ could also play an important role in determining the biomass of the zooplankton in Daya Bay, especially in the stations near the nuclear power plants and in the cage culture areas.     

上海市区浅层土粘土矿物、微结构与地面沉降

本文从微观角度出发,以X—光衍射为主,配合差热、红外光谱、透射电镜和扫描电镜手段,对上海市区浅层粘性土进行了岩矿鉴定和微结构分析,探讨了粘土矿物、微结构与地面沉降的关系。