Life-patterns on the periphery : a humanities base for development imperatives and their application in the Chicago city-region

Life-Patterns on the Periphery: A Humanities Base for Development Imperatives and their Application in the Chicago City-Region is informed by the need to bring diverse fields together in order to tackle issues related to the contemporary city-region. By honouring the long-term economic, social, political, and ecological imperatives that form the fabric of healthy, productive, sustainable communities, it becomes possible to setup political structures and citizen will to develop distinct places that result in the overlapping of citizen life patterns, setting the stage for citizen action and interaction. Based in humanities scholarship, the four imperatives act as checks on each other so that no one imperative is solely honoured in development. Informed by Heidegger, Arendt, deCerteau, Casey, and others, their foundation in the humanities underlines their importance, while at the same time creating a stage where all fields can contribute to actualizing this balance in practice. For this project, theoretical assistance has been greatly borrowed from architecture, planning theory, urban theory, and landscape urbanism, including scholarship from Saskia Sassen, John Friedmann, William Cronon, Jane Jacobs, Joel Garreau, Alan Berger, and many others. This project uses the Chicago city-region as a site, specifically the Interstate 80 and 88 corridors extending west from Chicago. Both transportation corridors are divided into study regions, providing the opportunity to examine a broad variety of population and development densities. Through observational research, a picture of each study region can be extrapolated, analyzed, and understood with respect to the four imperatives. This is put to use in this project by studying region-specific suggestions for future development moves, culminating in some universal steps that can be taken to develop stronger communities and set both the research site specifically and North American city-regions in general on a path towards healthy, productive, sustainable development.

Climatological study of transport to the PICO-NARE site using atmospheric backward trajectories

This study developed a transport climatology to the PICO-NARE station, in the central North Atlantic Ocean, using a 40-year set of atmospheric back trajectories. The trajectory set was subjected to a cluster analysis in order to group trajectories into six flow patterns, or clusters. An air flow probability analysis was conducted in conjunction with the cluster analysis in order to determine the source regions for flow to the site. Seasonal differences in the flow patterns were found, which included enhanced westerly flow in the winter, decreased westerly flow in the summer, and spring and fall having moderate westerly flow. The North Atlantic Oscillation had a significant impact on the winter and fall seasons and less significant impacts during spring and summer. The results of the climatology can be used in conjunction with measurements of ozone, CO, NOx, and NOy, which are currently being measured at the site, to develop a long-term, seasonal climatology of transport of pollutants to the central North Atlantic.

MULTIMODAL PERFORMANCE AND RELIABILITY ANALYSIS OF THE PIERRE AUGER OBSERVATORY NORTH SITE

The Pierre Auger Cosmic Ray Observatory North site employs a large array of surface detector stations (tanks) to detect the secondary particle showers generated by ultra-high energy cosmic rays. Due to the rare nature of ultra-high energy cosmic rays, it is important to have a high reliability on tank communications, ensuring no valuable data is lost. The Auger North site employs a peer-to-peer paradigm, the Wireless Architecture for Hard Real-Time Embedded Networks (WAHREN), designed specifically for highly reliable message delivery over fixed networks, under hard real-time deadlines. The WAHREN design included two retransmission protocols, Micro- and Macro- retransmission. To fully understand how each retransmission protocol increased the reliability of communications, this analysis evaluated the system without using either retransmission protocol (Case-0), both Micro- and Macro-retransmission individually (Micro and Macro), and Micro- and Macro-retransmission combined. This thesis used a multimodal modeling methodology to prove that a performance and reliability analysis of WAHREN was possible, and provided the results of the analysis. A multimodal approach was necessary because these processes were driven by different mathematical models. The results from this analysis can be used as a framework for making design decisions for the Auger North communication system.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.