Creativity, Community, and Growth: A Social Geography of Urban Craft Beer

To better understand the non-economic drivers of growth in emerging industries, this paper examines the craft beer industry. Specifically, the paper will review two examples - the Black Cloister Brewing Company in Toledo, OH and 3rd Turn Brewery, Louisville, KY - to understand how the values of entrepreneurs and local firms that are situated at the nexus of work, place, and creativity promote growth. Further, the paper will consider the socio-cultural meaning of creativity relative to the craft beer industry and the many ways in which the concept of innovation traditionally used by economic geographers to understand growth can be better understood within the context of creativity in some industries. In doing so, the paper represents a conceptual shift away from innovation towards creativity, as well as community

Importing Change: Canadian Competition and the U.S. Floriculture Industry

This article analyzes the shifting geography of production with respect to the U.S. floriculture industry

Research design and proposal writing in spatial science

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Creativity, Community, & Growth: A Social Geography of Urban Craft Beer

To better understand the non-economic drivers of growth in emerging industries, this paper examines the craft beer industry.  Specifically, the paper will review two examples—the Black Cloister Brewing Company in Toledo, OH and 3rd Turn Brewery, Louisville, KY—to understand how the values of entrepreneurs and local firms that are situated at the nexus of work, place, and creativity promote growth.  Further, the paper will consider the socio-cultural meaning of creativity relative to the craft beer industry and the many ways in which the concept of innovation traditionally used by economic geographers to understand growth can be better understood within the context of creativity in some industries.  In doing so, the paper represents a conceptual shift away from innovation towards creativity, as well as community

Optimizing land cover classification accuracy for change detection, a combined pixel-based and object-based approach in a mountainous area in Mexico

Inventories of past and present land cover changes form the basis of future conservation and landscape management strategies. Modern classification techniques can be applied to more efficiently extract information from traditional remote-sensing sources. Landsat ETM+ images of a mountainous area in Mexico form the input for a combined object-based and pixel-based land cover classification. The land cover categories with the highest individual classification accuracies determined based on these two methods are extracted and merged into combined land cover classifications. In total, seven common land cover categories were recognized and merged into single combined best-classification layers. A comparison of the overall classification accuracies for 1999 and 2006 of the pixel-based (0.74 and 0.81), object-based (0.77 and 0.71) and combined (0.88 and 0.87) classifications shows that the combination method produces the best results. These combined classifications then form the input for a change detection analysis between the two dates by applying post-classification, object-based change analysis using image differencing. It is concluded that the combined classification method together with the object-based change detection analysis leads to an improved classification accuracy and land cover change detection. This approach has the potential to be applied to land cover change analyses in similar mountainous areas using medium-resolution imagery

Collaborative Learning and Interinstitutional Partnerships: An Opportunity for Integrative Fieldwork in Geography

This article explores the contemporary function and value of field-oriented geography experiences for university-level students. The article details the design and delivery of an interinstitutional field course that partnered faculty and students-both graduate and undergraduate-from two geography programs with different curricular and research emphases. The article examines key aspects of the field course including strategies for obtaining and analyzing field data from both physical and human aspects of the discipline, the application and limitation of distance technologies within the context of field research, and the challenges and opportunities associated with field course experiences

Geo-spatial technologies in urban environments: policy, practice, and pixels

Using Geospatial Technologies in Urban Environments simultaneously fills two gaping vacuums in the scholarly literature on urban geography. The first is the clear and straightforward application of geospatial technologies to practical urban issues. By using remote sensing and statistical techniques (correlation-regression analysis, the expansion method, factor analysis, and analysis of variance), the - thors of these 12 chapters contribute significantly to our understanding of how geospatial methodologies enhance urban studies. For example, the GIS Specialty Group of the Association of American Geographers (AAG) has the largest m- bership of all the AAG specialty groups, followed by the Urban Geography S- cialty Group. Moreover, the Urban Geography Specialty Group has the largest number of cross-memberships with the GIS Specialty Group. This book advances this important geospatial and urban link. Second, the book fills a wide void in the urban-environment literature. Although the Annals of the Association of American Geographers has recently established an editorship devoted to human environmental issues ("Nature and Society"), re- tively few of the articles in this section of the journal have focused specifically on urban-environmental topics. Likewise, of the textbooks in urban geography p- lished over the past decade (Knox, 1994; Pacione, 2001; Kaplan, Wheeler, and Holloway, 2004), none has offered a single chapter on urban-environmental qu- tions, and only passing references to such topics as urban heat islands

Empty Spaces: Neighbourhood Change and the Greening of Detroit, 1975–2005

This paper investigates the disappearing residential geography of Detroit, Michigan, between 1975 and 2005 by examining the relationship between the ‘greenness’ of the urban landscape and the structural thinning of residential areas via satellite imagery and census data. The study uses normalized difference vegetation index (NDVI) and key housing variables as a proxy for observed changes in neighbourhood structure that correspond to the neighbourhood life cycle. Ordinary least squares and geographically weighted regression (GWR) were used to visualize the observed trends and performance of the models across space. Results from GWR analyses suggest the shifting residential geography of Detroit has changed from uniformly developed residential blocks to neighbourhoods that have experienced severe structural thinning across an urban landscape characterized by uneven development. The performance of the study models and parameters demonstrate how the relationships among NDVI and housing indicators, though significant, have diminished over time; this trend runs counter to green models applied to other urban landscapes, particularly those that follow the standard neighbourhood life cycle. Based on the empirical results, the study demonstrates the importance of understanding local histories and the broader socio-spatial context of cities when designing and implementing socio-spatial applications of remote sensing technologies