Geographical Transfer Research Articles

Context Dependence: A Conceptual Approach for Understanding the Habitat Relationships of Coastal Marine Fauna

Abstract Coastal habitats, such as seagrasses, mangroves, rocky and coral reefs, salt marshes, and kelp forests, sustain many key fish and invertebrate populations around the globe. Our understanding of how animals use these broadly defined habitat types is typically derived from a few well-studied regions and is often extrapolated to similar habitats elsewhere. As a result, a working understanding of their habitat importance is often based on information derived from other regions and environmental contexts. Contexts such as tidal range, rainfall, and local geomorphology may fundamentally alter animal–habitat relationships, and there is growing evidence that broadly defined habitat types such as “mangroves” or “salt marsh” may show predictable spatial and temporal variation in habitat function in relation to these environmental drivers. In the present article, we develop a framework for systematically examining contextual predictability to define the geographic transferability of animal–habitat relationships, to guide ongoing research, conservation, and management actions in these systems.

Changes in Health Care Following COVID-19

Changes in Health Care Following COVID-19

Addiction, Ground Rents, and Urban Casino Development

Casino development has become a favoured urban development strategy in a number of post-industrialising western economies (Hannigan, 2007). These developments are often justified on the basis that casinos attract reputedly rich and super-rich consumers from other places in what amounts to a rather convenient geographical transfer of value. These wealthy consumers, so the mercantilist argument goes, enrich both the casino owners and the broader public through taxes and license fees. Moreover, these gambling dollars are imported, while the effects and responsibility for problem gambling, one of the key arguments against gambling developments, are conveniently exported. A second argument, particularly favoured by the gambling industry and other casino proponents, is the creation of local jobs, both in construction and subsequent casino operations. For example, the Canadian casino operator Gateway Casino and Entertainment has organised its new casino proposal for London, Canada, around the creation of 700 local jobs. More generally, neoclassical economists suggest that casinos tend to increase economic growth in the longer-term (e.g. Walker, 2007). A third argument is that casinos bring a certain symbolic value to a city, particularly if they take the form of large towers such as Barangaroo, Sydney, or its proposed competitor in Star City Casino located across the harbour in Pyrmont.

Descriptive analysis of World Health Organization-recommended second-line antiretroviral treatment: A retrospective cohort data analysis.

World Health Organization guidelines recommend that HIV patients who do not achieve viral suppression on efavirenz-based first-line antiretroviral therapy (ART) should be changed to a protease inhibitor (PI)-based regimen. In South Africa (SA), ~200000 people are on second-line treatment, but little is known about these patients. To describe second-line black African patients in a large urban area. A quantitative retrospective study of 825 second-line patients in central Johannesburg, SA (subdistrict F), was performed with data extracted from government databases. Demographic characteristics, treatment status and laboratory information were gathered, then analysed with CD4+ cell count, viral load (VL) and retention-in-care data as outcome variables. The average recorded time to VL measurement after the switch to a PI-based ART regimen was 20 months, and 83.1% (570/686) of patients with a recent VL achieved viral suppression while on second-line treatment. The most recent median CD4+ cell count for the cohort was 286cells/µL (interquartile range 160 - 478), which represented a 177 cells/µL increase from the baseline count at the start of first-line ART. Slightly less than three-quarters (72.4%) of the population remained active in care in the study clinics from initiation on first-line ART. Demographic characteristics such as being <25 years of age, male sex and geographical transfer (started initial treatment in a different region) independently predicted low CD4+ cell counts and virological failure on second-line treatment. Patients with virological failure were most likely (odds ratio (OR) 3.13, 95% confidence interval (CI) 1.50 - 6.56) to be lost to follow-up after the switch, while patients from Hillbrow Community Health Centre (OR 0.27, 95% CI 0.16 - 0.44), South Rand Hospital (OR 0.24, 95% CI 0.12 - 0.47) and Jeppe Clinic (OR 0.38, 95% CI 0.16 - 0.88), three larger sites, were most likely to remain active in care. VL suppression was high in patients on second-line treatment, but one-fifth of patients were lost to follow-up. Younger age, male sex and transfer from other treatment sites predicted poor treatment outcomes, highlighting opportunities for prioritisation of adherence interventions.

Structural Building Damage Detection with Deep Learning: Assessment of a State-of-the-Art CNN in Operational Conditions

Remotely sensed data can provide the basis for timely and efficient building damage maps that are of fundamental importance to support the response activities following disaster events. However, the generation of these maps continues to be mainly based on the manual extraction of relevant information in operational frameworks. Considering the identification of visible structural damages caused by earthquakes and explosions, several recent works have shown that Convolutional Neural Networks (CNN) outperform traditional methods. However, the limited availability of publicly available image datasets depicting structural disaster damages, and the wide variety of sensors and spatial resolution used for these acquisitions (from space, aerial and UAV platforms), have limited the clarity of how these networks can effectively serve First Responder needs and emergency mapping service requirements. In this paper, an advanced CNN for visible structural damage detection is tested to shed some light on what deep learning networks can currently deliver, and its adoption in realistic operational conditions after earthquakes and explosions is critically discussed. The heterogeneous and large datasets collected by the authors covering different locations, spatial resolutions and platforms were used to assess the network performances in terms of transfer learning with specific regard to geographical transferability of the trained network to imagery acquired in different locations. The computational time needed to deliver these maps is also assessed. Results show that quality metrics are influenced by the composition of training samples used in the network. To promote their wider use, three pre-trained networks—optimized for satellite, airborne and UAV image spatial resolutions and viewing angles—are made freely available to the scientific community.

The Geographer Marx

In celebration of Marx's 200th birth anniversary, this symposium revisits how Marx has influenced geography research and pedagogy. Capital, capitalism, commodity, use value, surplus value, labor theory of value, class, exploitation, class struggle, dialectics, dialectical materialism are now ubiquitous in critical human geography research. Theories inspired by Marxism like critical theories of imperialism, geographic transfer of value, dependency has been the mainstay for envisioning relationship between Global North and Global South. Theories inspired by class, class-consciousness and ideology have inspired geographies of labor, labor unionism and social movements. Commodity, commodification of nature, production, and accumulation has also inspired post-structural and feminist research on social reproduction, feminization of poverty and informality, environmental degradation, climate change, and consumption landscape. In this symposium, authors self-select concepts, ideas, theories, and metaphors from Marx and discuss how, and in what ways, these influenced their work (research and teaching), and also how their Marxist geography influences Marxism and society.

Multi-Resolution Feature Fusion for Image Classification of Building Damages with Convolutional Neural Networks

Remote sensing images have long been preferred to perform building damage assessments. The recently proposed methods to extract damaged regions from remote sensing imagery rely on convolutional neural networks (CNN). The common approach is to train a CNN independently considering each of the different resolution levels (satellite, aerial, and terrestrial) in a binary classification approach. In this regard, an ever-growing amount of multi-resolution imagery are being collected, but the current approaches use one single resolution as their input. The use of up/down-sampled images for training has been reported as beneficial for the image classification accuracy both in the computer vision and remote sensing domains. However, it is still unclear if such multi-resolution information can also be captured from images with different spatial resolutions such as imagery of the satellite and airborne (from both manned and unmanned platforms) resolutions. In this paper, three multi-resolution CNN feature fusion approaches are proposed and tested against two baseline (mono-resolution) methods to perform the image classification of building damages. Overall, the results show better accuracy and localization capabilities when fusing multi-resolution feature maps, specifically when these feature maps are merged and consider feature information from the intermediate layers of each of the resolution level networks. Nonetheless, these multi-resolution feature fusion approaches behaved differently considering each level of resolution. In the satellite and aerial (unmanned) cases, the improvements in the accuracy reached 2% while the accuracy improvements for the airborne (manned) case was marginal. The results were further confirmed by testing the approach for geographical transferability, in which the improvements between the baseline and multi-resolution experiments were overall maintained.

Modeling domestic geographical transfers of toxic substances in WEEE: A case study of spent lead-acid batteries in China

Abstract This study models previously unknown domestic geographical transfers of toxic substances in waste electrical and electronic equipment (WEEE) by using the minimum distance and maximum flow (MDMF) algorithm. Using lead scrap as a typical case, the results present a complete picture of domestic geographical transfers in China: (1) the total interprovincial transfer of lead scrap is 996 k tonnes, accounting for 63% of total lead recycled; (2) lead scrap transfers between 4 pairs of provinces are more than 100 k tonnes with an average distance per k tonne of lead scrap transferred of 967 km; and (3) using outdated processing technology, national pollutant emissions of lead, CO2 and SO2 resulting from these transfers can reach 50, 497, and 105 k tonnes, respectively. In addition, if provinces recycle locally generated and imported LAB at a ratio below 1:1, or 50% imported LAB, using the advanced process, emissions can be reduced. The domestic geographical transfer model has the following advantages: (1) it is helpful for the geographic distribution and capacity planning of WEEE recycling plants; and (2) it provides a method that may be less time-consuming in estimating the external quantified environmental responsibility of the WEEE generating provinces.

A Nonparametric Ensemble Postprocessing Approach for Short-Range Visibility Predictions in Data-Sparse Areas

Abstract This work develops and tests the viability of obtaining skillful short-range (<20 h) visibility predictions using statistical postprocessing of a 4-km, 10-member Weather Research and Forecasting (WRF) ensemble configured to closely match the U.S. Air Force Mesoscale Ensemble Forecast System. The raw WRF predictions produce excessive forecasts of zero cloud water, which is simultaneously predicted by all ensemble members in 62% of observed fog cases, leading to zero ensemble dispersion and no skill in these cases. Adding dispersion to the clear cases by making upward adjustments to cloud water predictions from individual members not predicting fog on their own provides the best chance to increase the resolution and reliability of the ensemble. The technique leverages traits of a joint parameter space in the predictions and is generally most effective when the space is defined with a moisture parameter and a low-level stability parameter. Cross-validation shows that the method adds significant overnight skill to predictions in valley and coastal regions compared to the raw WRF forecasts, with modest skill increases after sunrise. Postprocessing does not improve the highly skillful raw WRF predictions at the mountain test sites. Since the framework addresses only systematic WRF deficiencies and identifies parameter pairs with a clear, non-site-specific physical mechanism of predictive power, it has geographical transferability with less need for recalibration or observational record compared to other statistical postprocessing approaches.

Reterritorialization and aesthetic transformations: the case of Tony Harrison’s Phaedra Britannica and The Misanthrope

ABSTRACTThis article analyses the impact of reterritorialization on classics of the stage. After reflecting on some particularities of classical works, the article focuses on The Misanthrope and Phaedra Britannica by British poet Tony Harrison, the first and rare successes of Molière, and particularly Racine on the Anglo-Saxon stage. It compares the main aesthetic features of Molière’s and Racine’s works with the modernizations operated by Harrison, and comments on the relevance of the historical and geographical transfer as a domestication strategy. While reterritorialization strategically includes the spectator, it does so not without a major impact on certain characteristics of seventeenth-century French theatre. The fact that the plays have a strong aesthetic identity makes the transformations striking. Indeed, what makes up the identity of classical French theatre, namely the unity of action, characterization, passions and, more generally, the nature of comedy and tragedy, is transformed by reterritorialization. Also dependent on reterritorialization, dramatic language, notably rhythm, semantics and versification, is metamorphosed. These two case studies on the impact of historical and geographical transfer shed light on the points of disparity between classical French theatre and expectations of the modern English audience, and help to address other reterritorialized adaptations of classics.

Modelling the distribution and compositional variation of plant communities at the continental scale

AbstractAimWe investigate whether (1) environmental predictors allow to delineate the distribution of discrete community types at the continental scale and (2) how data completeness influences model generalization in relation to the compositional variation of the modelled entities.LocationEurope.MethodsWe used comprehensive datasets of two community types of conservation concern in Europe: acidophilous beech forests and base‐rich fens. We computed community distribution models (CDMs) calibrated with environmental predictors to predict the occurrence of both community types, evaluating geographical transferability, interpolation and extrapolation under different scenarios of sampling bias. We used generalized dissimilarity modelling (GDM) to assess the role of geographical and environmental drivers in compositional variation within the predicted distributions.ResultsFor the two community types, CDMs computed for the whole study area provided good performance when evaluated by random cross‐validation and external validation. Geographical transferability provided lower but relatively good performance, while model extrapolation performed poorly when compared with interpolation. Generalized dissimilarity modelling showed a predominant effect of geographical distance on compositional variation, complemented with the environmental predictors that also influenced habitat suitability.Main conclusionsCorrelative approaches typically used for modelling the distribution of individual species are also useful for delineating the potential area of occupancy of community types at the continental scale, when using consistent definitions of the modelled entity and high data completeness. The combination of CDMs with GDM further improves the understanding of diversity patterns of plant communities, providing spatially explicit information for mapping vegetation diversity and related habitat types at large scales.

From Ambridge to the world? Class returns to rural population geographies

Smith and Phillips make a powerful case both for investigating rural population change within much of the Global North from a class-foregrounded gentrification perspective and for undertaking this investigation in an internationally comparative manner. Neither aspect has been sufficiently developed within scholarship to date. While endorsing such a call, this commentary briefly presents three additional contextual framings: describing and explaining the very late coming of age of explicit ‘rural gentrification’ research; reiterating the challenge that geographical transferability of concepts and terminology presents; and insisting on the central but not exclusive role class must play within critical discourse on populations in the contemporary countryside.

Global cities and the geographical transfer of value

The central argument of this article is that global cities are, due to their clustering of producer service firms, critical governance nodes in global production networks. More in particular, the article scrutinises the role of producer service firms in uneven development and, especially, in the geographical transfer of value (Hadjimichalis, 1984). Because the direct as well as the indirect mechanisms through which value is transferred geographically require the intervention of producer service firms, global cities can be theorised as governance nodes for centripetal wealth transfers along global commodity chains. Moreover, and in the context of the persisting criticism that the global city concept has a bias towards Northern/Western cities, the article argues that the claim that global cities are critical places for the organisation of uneven development also holds for cities beyond ‘the usual suspects’. Referring to cases of how producer service firms in Hamburg and Mexico City erect entry barriers to protect their clients from competition and of how they shape labour relations at the expense of employees, I have maintained that governance is, as Sassen (2010: 158) has argued, indeed ‘embedded’ into the services provided. From that follows that even ‘minor’ global cities are strategic governance places from where the transfer of wealth towards the centres of the world economy is organised.

Transferability of bioassessment indices among water body types and ecoregions: A California experiment in wetland assessment

Biological assessment of aquatic resources requires the availability of bioassessment tools that work in all waterbody types and regions of interest. Developing new assessment tools may require several years of data collection and substantial investment of resources, which may not be an option for some aquatic resource managers. Adapting tools developed for different regions or wetland types may be an attractive alternative to developing new indices, provided they work well in the novel setting. In this study, we explore the transferability of two bioassessment indices for application to depressional wetlands in California, which are wetland type of management concern but for which bioassessment tools don’t currently exist. We tested the applicability of a depressional wetland invertebrate index of biotic integrity (IBI) developed in the San Francisco Bay region of northern California for application in the drier regions of southern California (i.e. geographic transferability), and the ability to apply a riverine benthic diatom IBI to benthic diatoms in depressional wetlands (i.e. water body type transferability). We evaluated the accuracy and responsiveness of the existing Indices for use in depressional wetlands and refined reference definitions and recalibrated thresholds relative to stressor gradients to maximize index performance. Performance of the adapted indices was compared to that of an existing habitat assessment tool (the California Rapid Assessment Method; CRAM) that has been developed for statewide application of depressional wetlands. Finally, we demonstrate application of the revised indices for ambient assessment of depressional wetland condition in southern California. Recalibrating both the macroinvertebrate and diatom indices to reference thresholds based on nutrient concentrations resulted in lower coefficient of variation among reference sites, greater differentiation between reference and non-reference and stronger relationship with stressors than when reference thresholds were based on landscape disturbance. Overall, the simple adjustment of the reference definition allowed us to transfer the indices with no structural changes to the metrics. This approach can facilitate future index adaptations that allow practitioners to include waterbody types for which there is no current index into routine biomonitoring programs.

Analysis of the Temporal and Geographical Transferability of Disaggregate Hurricane Evacuation Demand Models of Different Model Specification

Analysis of the Temporal and Geographical Transferability of Disaggregate Hurricane Evacuation Demand Models of Different Model Specification

Estimation of wet aggregation indices using soil properties and diffuse reflectance near infrared spectroscopy: An application of classification and regression tree analysis

Soil aggregation is critical for assessing soil health; however, conventional aggregation measurement is laborious and expensive. The performance of near infrared diffuse reflectance spectroscopy (NIR) and basic soil properties for estimation of wet aggregation indices was investigated. Two samples sets representing different soils from across Lake Victoria Basin in Kenya were used for the study. A model calibration set ( n = 136) was obtained following a conditioned Latin hypercube sampling, and validation set ( n = 120) using a spatially stratified random sampling strategy. Spectral measurements were obtained for air-dried ( RPD (ratio of prediction deviation) of 1.4–2.0. Independent testing of NIR PLS gave RPD = 1.4 for macro and RPD = 1.2–1.0 for unstable and soil predictors. NIR could estimate macro and unstable fractions with moderate reliability, and; NIR was superior over soil properties for stability pedotransfer purposes. Further efforts should widely test performance for a wider range of soil types and calibration strategies for improved geographic transferability of models.

Building Types’ Classification Using Shape-Based Features and Linear Discriminant Functions

In this paper, the applicability and performance of linear discriminant analysis (LDA) for building types’ classification are investigated. Building models at a level of detail 1 (LoD1) are derived from real estate cadastral building footprints and digital surface models from stereoscopic airborne images. In several experiments for two cities in Germany (Berlin and Munich), we first evaluate the discriminatory power of 26 different shape-based features which describe the physiognomy of individual buildings in terms of 1-D (e.g., length), 2-D (e.g., area), and 3-D (e.g., volume) features. While 1-D features show low contributions to the discrimination of the five building types, we observe high contributions of the 3-D shape index and 2-D measures of compactness. In a second group of experiments, the size of training samples for the classification process is investigated with the outcome that a size of 10% of the total number of labeled features is practicable in terms of size and accuracy. In a third battery of experiments, the selected features and training sample size are used for the classification of building types resulting in kappa values of 0.94 for both cities. In the final experiments, the geographical transfer between the two cities is investigated reaching kappa values of 0.93 and 0.91, respectively. The tests show that a simple linear classifier like LDA can handle building types’ classification without much user interaction compared to more complex classification methods but is limited when similar building types (e.g., perimeter block development and block development ) are to be discriminated.

Transferibilidad geográfica de modelos de generación de viajes urbanos: comparación de modelos de regresión y tasas de viajes para algunas ciudades colombianas

Transferibilidad geográfica de modelos de generación de viajes urbanos: comparación de modelos de regresión y tasas de viajes para algunas ciudades colombianas

Water Security for Agriculture: Introduction to the Water Security Task Force Symposium

Published in Agron. J. 107:1524–1525 (2015) doi:10.2134/agronj15.0909 Available freely online through the author-supported open access option. Copyright © 2015 by the American Society of Agronomy, 5585 Guilford Road, Madison, WI 53711. All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. F.F. Vocasek, Servi-Tech Laboratories, Dodge City, KS 67801; G.A. Peterson (retired), Soil and Crop Sciences Dep., 301 University Ave., Colorado State Univ., Ft. Collins, CO 80523. Received 5 May 2015. Accepted 5 May 2015. *Corresponding author (Gary.Peterson@ colostate.edu). The American Society of Agronomy (ASA) created the Water Security for Agriculture Task Force at its annual meeting in San Antonio, TX, in 2011. The “Task Force” was proposed by the ASA Science Policy Committee as follows:

Editorial

Editorial