Conceptual Decolonization of Space: Worldview and Language in Anishinaabe Akiing

This dissertation examines the role of worldview and language in the cultural framework of American Indian people. In it I develop a theory of worldview which can be defined as an interrelated set of logics that orients a culture to space (land), time, the rest of life, and provides a prescription for understanding that life. Considering the strong links between language and worldview, it is methodologically necessary to focus on a particular language and culture to decolonize concepts of and relationships to land. In particular, this dissertation focuses on an Anishinaabe worldview as consisting of four components, which are; (1) an intimate relationship to a localized space; (2) a cyclical understanding of time; (3) living in a web of relatedness with all life, and (4) understanding the world around us in terms of balance. The methodological approach draws from Anishinaabemowin, the traditional Anishinaabe language, as a starting place for negotiating a linguistic-conceptual analysis of these logics to decolonize the understandings of land, time, relatedness and balance. This dissertation helps to demonstrate that the religious language as codified in the 1st Amendment to the United States Constitution as religious freedom is unable to carry the meaning of the fundamental relationships to land that are embedded in Anishinaabemowin and culture. I compare the above Anishinaabe worldview to that of the eurowestern culture in America, which is; (1) the domination of space; (2) a linear progression of time; (3) a hierarchical organization of life; and (4) understanding the world as a Manichean battle of good versus evil. This dissertation seeks to decolonize American Indian translational methodologies and undermine the assumptions of eurowestern cultural universality.

Identification of geostationary satellites using polarization data from unresolved images

In order to protect critical military and commercial space assets, the United States Space Surveillance Network must have the ability to positively identify and characterize all space objects. Unfortunately, positive identification and characterization of space objects is a manual and labor intensive process today since even large telescopes cannot provide resolved images of most space objects. Since resolved images of geosynchronous satellites are not technically feasible with current technology, another method of distinguishing space objects was explored that exploits the polarization signature from unresolved images. The objective of this study was to collect and analyze visible-spectrum polarization data from unresolved images of geosynchronous satellites taken over various solar phase angles. Different collection geometries were used to evaluate the polarization contribution of solar arrays, thermal control materials, antennas, and the satellite bus as the solar phase angle changed. Since materials on space objects age due to the space environment, it was postulated that their polarization signature may change enough to allow discrimination of identical satellites launched at different times. The instrumentation used in this experiment was a United States Air Force Academy (USAFA) Department of Physics system that consists of a 20-inch Ritchey-Chrétien telescope and a dual focal plane optical train fed with a polarizing beam splitter. A rigorous calibration of the system was performed that included corrections for pixel bias, dark current, and response. Additionally, the two channel polarimeter was calibrated by experimentally determining the Mueller matrix for the system and relating image intensity at the two cameras to Stokes parameters S0 and S1. After the system calibration, polarization data was collected during three nights on eight geosynchronous satellites built by various manufacturers and launched several years apart. Three pairs of the eight satellites were identical buses to determine if identical buses could be correctly differentiated. When Stokes parameters were plotted against time and solar phase angle, the data indicates that there were distinguishing features in S0 (total intensity) and S1 (linear polarization) that may lead to positive identification or classification of each satellite.