A new deal for lone parents? Training lone parents for work in West London

In this paper we explore the impacts of the training programmes offered to lone mothers with young children on the Government's 'New Deal for Lone Parents' in one local labour market: West London. Our research suggests that regulatory workfare policies are (re)producing and reinforcing gendered inequalities in the labour market by encouraging lone mothers to undertake training in feminised occupational areas such as childcare. We will argue that in a local economy such as West London where more childcare workers are desperately needed to enable other more highly skilled workers to take up employment opportunities, such training programmes may be doing little more than exacerbating the already gendered and class-based polarisation of the labour market – embedding low-skilled, poorly qualified lone mothers into low-paid jobs.     

Three‐dimensional maps for archipelagoes

Ethical dilemmas involving issues of harm-benefit, privacy, deception, and sponsor relations are encountered frequently in geographical research. Geographers have not always been sensitive to ethical issues, nor have they always been able to reconcile their obligations to understanding and knowledge with those of respecting the dignity and integrity of research subjects. This paper reviews these fundamental ethical concerns. Four strategies for handling ethical difficulties are reviewed: individual self-regulation, disciplinary responses, institutional controls, and external controls. Individual self-regulation is recommended.     

Back to the Future? Planning for environmental outcomes and the new Caring for our Country program

The Australian government Caring for our Country (CfoC) program, first announced in 2008, has sought to build on and enhance previous experience with Australian natural resource management policy. This paper critically examines the initial design, planned delivery, and first round of competitive funding outcomes of the new program. This analysis shows that the initial design and delivery of the CfoC model was ad hoc, politicised, and lacking in transparency. The paper concludes that a more systematic and transparent approach for achieving sustainable environmental outcomes is required in order for this new program to achieve its intended objectives. These implications are of interest to Australian and international geographers, natural resource planners, scientists and policy makers concerned with the design, delivery and outcomes of large natural resource and environmental management programs.     

A proposed framework for feature‐level geospatial data sharing: a case study for transportation network data

Current data sharing in the Internet environment is supported using metadata at the file level. This approach has three fundamental shortcomings. First, sharing data from different sources with different semantics, data models, and acquisition methods usually requires data conversion and/or integration like data conflation. This can be tedious and error‐prone. Second, data updated from one source cannot be automatically propagated to other related data or applications. Finally, data sharing at the file level makes it difficult to provide feature‐level data for searching, accessing, and exchanging in real time over the Internet. This paper addresses these three issues by proposing a standards‐based framework for sharing geospatial data in the transportation application domain. The proposed framework uses a standard data model—geospatial data model proposed by the Geospatial One‐Stop initiative to harmonize the semantics and data models without the use of data integration methods. It uses Geography Markup Language (GML) for geospatial data coding and feature relationship, which provides a basis to propagate the data update from one source to related other sources and applications, and to search and extract data at the feature level. The framework uses the Web Feature Service (WFS) to search, access and extract data at the feature level from distributed sources. Finally, the Scalable Vector Graphics (SVG) standard was used for data display on the Web browser. Two transportation network datasets are used in the prototype case study to implement the proposed framework. The prototype allows the user to access and extract data at the feature level on the Web from distributed sources without downloading the full data file. It shows that the proposed standards‐based feature‐level data‐sharing system is capable of sharing data without data conflation, accessing, and exchanging data in real time at the feature level. The prototype also shows that changes in one database can be automatically reflected or propagated in another related database without data downloading.     

Ceremony for Establishing SFU-NOAA Joint Center for Ocean Remote Sensing and Living Marine Resources Management Held in Shanghai

A ceremony for establishing SFU-NOAA Joint Center for Ocean Remote Sensing and Living Marine Resources Management was held in Shanghai Fisheries University on December 6, 2006. The Center, supported by High Level Featured Project of Shanghai Municipal Education Commission, will provide a platform for exchanges of scientific information between scientists of different countries and multidisciplines and for global collaborations in research areas related to fish stock assessment and management.[第一段]     

International Conference on Water Security for Future Generations

The International Conference on Water Security for Future Generations will be held at theNortheast Institute of Geography and Agricultural Ecology (NEIGAE), Chinese Academy ofSciences in Changchun, Jilin Province, P.R. China, from 26 - 31 July 2004. Expansion in agricultural activity throughout the world in order to sustain an ever-increasingpopulation, together with the more frequent droughts caused by climate variability, has resulted inmajor water shortages, which is the essence of main concern to all Governments and individuals.     

‘Big data’ for pedestrian volume: Exploring the use of Google Street View images for pedestrian counts

New sources of data such as ‘big data’ and computational analytics have stimulated innovative pedestrian oriented research. Current studies, however, are still limited and subjective with regard to the use of Google Street View and other online sources for environment audits or pedestrian counts because of the manual information extraction and compilation, especially for large areas. This study aims to provide future research an alternative method to conduct large scale data collection more consistently and objectively on pedestrian counts and possibly for environment audits and stimulate discussion of the use of ‘big data’ and recent computational advances for planning and design. We explore and report information needed to automatically download and assemble Google Street View images, as well as other image parameters for a wide range of analysis and visualization, and explore extracting pedestrian count data based on these images using machine vision and learning technology. The reliability tests results based on pedestrian information collected from over 200 street segments in Buffalo, NY, Washington, D.C., and Boston, MA respectively suggested that the image detection method used in this study are capable of determining the presence of pedestrian with a reasonable level of accuracy. The limitation and potential improvement of the proposed method is also discussed.     

GIS and ANN model for landslide susceptibility mapping

1 IntroductionThe population growth and the expansion of settlements and life-lines over hazardous areas exert increasingly great impact of natural disasters both in the developed and developing countries. In many countries, the economic losses and casualties due to landslides are greater than commonly recognized and generate a yearly loss of property larger than that from any other natural disasters, including earthquakes, floods and windstorms. Landslides in mountainous terrain often occur a…