The paper examines the relationship between urban form, socio-economic status, ethnicity, accessibility and pedestrian activity in the Lansing Capital Region, Michigan. This research explores the burdens of urban environments through a study of accessibility and travel behaviour in an urban region characterized by rapid suburbanization and urban decline. Specifically, the study seeks to answer how socio-economic and ethnic status affect accessibility and travel behaviour in urban environments that have traditionally been viewed as promoting walking; built environments characterized by higher densities, mixed land uses and greater connectivity. The research shows that the traditional relationship between higher densities, mixed land uses, higher connectivity, greater accessibility and pedestrian activity is not as strong in declining inner cities.

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BackgroundCommunity hospital placement is dictated by a diverse set of geographical factors and historical contingency. In the summer of 2004, a multi-organizational committee headed by the State of Michigan's Department of Community Health approached the authors of this paper with questions about how spatial analyses might be employed to develop a revised community hospital approval procedure. Three objectives were set. First, the committee needed visualizations of both the spatial pattern of Michigan's population and its 139 community hospitals. Second, the committee required a clear, defensible assessment methodology to quantify access to existing hospitals statewide, taking into account factors such as distance to nearest hospital and road network density to estimate travel time. Third, the committee wanted to contrast the spatial distribution of existing community hospitals with a theoretical configuration that best met statewide demand. This paper presents our efforts to first describe the distribution of Michigan's current community hospital pattern and its people, and second, develop two models, access-based and demand-based, to identify areas with inadequate access to existing hospitals.ResultsUsing the product from the access-based model and contiguity and population criteria, two areas were identified as being "under-served." The lower area, located north/northeast of Detroit, contained the greater total land area and population of the two areas. The upper area was centered north of Grand Rapids. A demand-based model was applied to evaluate the existing facility arrangement by allocating daily bed demand in each ZIP code to the closest facility. We found 1,887 beds per day were demanded by ZIP centroids more than 16.1 kilometers from the nearest existing hospital. This represented 12.7% of the average statewide daily bed demand. If a 32.3 kilometer radius was employed, unmet demand dropped to 160 beds per day (1.1%).ConclusionBoth modeling approaches enable policymakers to identify under-served areas. Ultimately this paper is concerned with the intersection of spatial analysis and policymaking. Using the best scientific practice to identify locations of under-served populations based on many factors provides policymakers with a powerful tool for making good decisions.

The research explores the impact of socioeconomic and racial variables on accessibility to urban amenities and travel in compact urban built environments that have traditionally been viewed as improving access to daily destinations and promoting nonmotorized travel: urban environments characterized by high densities, mixed land uses, and high connectivity. The study focuses on six neighborhoods in the Detroit region. Two neighborhoods are within the city itself, and predominantly poor and Black, and four of the neighborhoods are in the region surrounding the city, and they are predominantly wealthy and White. This study at the neighborhood scale enables an analysis into how class and race affect accessibility and travel in neighborhoods experiencing urban disinvestment and decline. The research shows that the traditional relationship between high densities, mixed land uses, high connectivity, greater accessibility, and pedestrian activity is significantly weaker in declining inner cities.

This study investigated the spatiotemporal dynamics of tropical deciduous forest including dry dipterocarp forest (DDF) and mixed deciduous forest (MDF) and its phenological changes in responses to El Niño and La Niña during 2001–2016. Based on time series of Normalized Difference Vegetation Index (NDVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS), the start of growing season (SOS), the end of growing season (EOS), and length of growing season (LOS) were derived. In absence of climatic fluctuation, the SOS of DDF commonly started on 106 ± 7 DOY, delayed to 132 DOY in El Niño year (2010) and advanced to 87 DOY in La Niña year (2011). Thus, there was a delay of about 19 to 33 days in El Niño and an earlier onset of about 13 to 27 days in La Niña year. The SOS of MDF started almost same time as of DDF on the 107 ± 7 DOY during the neutral years and delayed to 127 DOY during El Niño, advanced to 92 DOY in La Niña year. The SOS of MDF was delayed by about 12 to 28 days in El Niño and was earlier about 8 to 22 days in La Niña. Corresponding to these shifts in SOS and LOS of both DDF and MDF were also induced by the El Niño–Southern Oscillation (ENSO).