Everywhere different? Globalisation and the impact of international migration on Sydney and Melbourne

Using a new approach to classifying migrant group concentrations, we test for evidence of the effects of globalisation, associated by some with ‘protopostmodernity’, on two Australian cities. Sydney is characterised as an emergent world city and a focus of ‘new economy’ activities. Melbourne is associated with ‘old economy’ activities, dominated by manufacturing. In the Australian context, the onset of globalisation also coincided with significant changes to immigration policy: the end of a ‘white Australia’ policy in the early 1970s in favour of a skills-based policy, regardless of race or ethnicity. We argue that the evidence of the spatial behaviour of ethnic groups for these two cities highlights the essential continuity of ethnic segregation and spatial assimilation processes in two cities where segregation levels and experience are fundamentally different from many overseas examples. We further argue for a need to recognise that context, and the ethnic experience, are everywhere different, both intra- and internationally.     

Making our neighborhoods,making our selves

In this paper, we explore a “grassroots” neighborhood revitalization effort engendered at the national scale without regard to local geographies of race and class. Specifically, we examine the Harambee Great Neighborhood Initiative, convened by the well-known nonprofit Habitat for Humanity together with Milwaukee’s Local Initiatives Support Corporation, in Milwaukee, Wisconsin. Drawing from participant observation, analysis of print and digital media, volunteer surveys, and interviews with area residents and local nonprofit representatives, we demonstrate the ways in which the six-year program of planning and neighborhood development was conceived and driven by an extra-local nonprofit with significant blind spots to local and organizational politics of race and without sufficient collaboration with the Harambee community. Our analysis points to the importance of race in nonprofit governance and community revitalization efforts. Moreover, we contribute to urban geographic scholarship on nonprofit governance by examining the dynamics of privilege, inclusion, and exclusion as they relate to practices of engagement and volunteerism in nonlocal “grassroots” projects.     

Migration velocity analysis using a genetic algorithm

Migration velocity analysis, a method for determining long wavelength velocity structure, is a critical step in prestack imaging. Solution of this inverse problem is made difficult by a multimodal objective function; a parameter space often vast in extent; and an evaluation procedure for candidate solutions, involving the calculation of depth-migrated image gathers, that can be prohibitively expensive. Recognizing the global nature of the problem, we employ a genetic algorithm (GA) in the search for the optimum velocity model. In order to describe a model efficiently, regions of smooth variation are identified and sparsely parametrized. Region boundaries are obtained via map migration of events picked on the zero-offset time section. Within a region, which may contain several reflectors, separate components describe long and short wavelength variations, eliminating from the parameter space, models with large velocity fluctuations. Vital to the success of the method is rapid model evaluation, achieved by generating image gathers only in the neighbourhood of specific reflectors. Probability of a model, which we seek to maximize, is derived from the flatness of imaged events. Except for an initial interpretation of the zero-offset time section, our method is automatic in that it requires no picking of residual moveout on migrated gathers. Using an example data set from the North Sea, we show that it is feasible to solve for all velocity parameters in the model simultaneously: the method is global in this respect also.     

3-D Shoreline Extraction from IKONOS Satellite Imagery

Shorelines are recognized as unique features on Earth. They have valuable properties for a diverse user community. At present, photogrammetry is the most popular technique used to capture a shoreline. With improved resolution and accuracy, commercial high-resolution satellite imagery is demonstrating a great potential in the photogrammetry application domain. One example is the utilization of IKONOS satellite imagery in shoreline extraction. IKONOS panchromatic imagery has a resolution of approximately one meter as well as the capabilities of stereo imaging. This article presents the results of an experiment in which we attempted to improve IKONOS Rational Functions (RF) for a better ground accuracy and to employ the improved RF for 3-D shoreline extraction using 1-meter panchromatic stereo images in a Lake Erie coastal area. Two approaches were investigated. One was to rectify the ground coordinates derived from vendor-provided RF coefficients using ground control points (GCPs). The other was to refine the RF coefficients using the GCPs. We compare the results from these two approaches. An assessment of the shoreline extracted from IKONOS images compared with the existing shoreline is also conducted to demonstrate the potential of the IKONOS imagery for shoreline mapping.     

Possibilities of soil spectroscopy for the classification of contaminated areas in river floodplains

During the past decades, large amounts of diffuse contaminated soil material have been deposited in the floodplains of the river Rhine in the Netherlands. The dynamic character of this river causes a large spatial variability in the contamination level of its floodplain soils. Characterisation of the spatial variability exclusively based on soil sampling and analysis is often insufficient and expensive. Hyperspectral images can provide additional spatial information for a proper characterisation of the contamination situation of river floodplains. This paper describes the possible application of soil spectroscopy to estimate metal concentration levels in river floodplains. Soil reflectance spectra in the visible-near infrared region (VNIR) were measured in the laboratory for soil samples taken from two river floodplains along the river Waal, the main tributary of the river Rhine in the Netherlands. A multivariate calibration procedure using partial least squares (PLS) regression was applied to establish a relationship between reflectance spectra in the visible-near infrared (VNIR) region and spectrally active soil characteristics (organic matter and clay content) that are intercorrelated with concentration levels of Cd and Zn. Results of the analysis of two river floodplains are summarised and the influence of scale-level and sub soil material on the prediction capability is discussed.