Adv Geographic Info Syste

Prerequisite: Successful completion of URBS UN2200 Introduction to GIS Methods, or equivalent with instructor permission. With the veritable explosion of urban data alongside the continued proliferation of new tools for its consideration, this course allows students to develop specialized approaches to spatial analysis while introducing a series of common advanced techniques and nuanced methodological questions. Aimed at covering a variety of topics with immediate relevance to urbanism in practice and in research, the course operates with a two-fold mission: (1) to critically discuss the theories, concepts, and research methods involved in spatial analysis and (2) to learn the techniques necessary for engaging those theories and deploying those methods. The class will work to meet this mission with a dedicated focus on the urban environment and the spatial particularities and relationships that arise from the urban context. Among others, this course takes as a foundational premise that spatial analysis within geographic information systems is an incredibly powerful and double-edged weapon: it provides both the methods for answering complex spatial questions and the means for effectively communicating the results. Like any other weapon it can serve many ends, and as such an advanced course in spatial analysis must frame its use within the developing discourse on professional practice and responsibility. The course is designed with a combination format. Early weeks are predominantly lecture-style presentations supplemented with discussion and technical demonstration and exercises. Students are expected to complete these exercises outside of class (as homework), bringing their questions to our discussion. The latter half of the course is a project-based seminar. Seminar-style presentation and discussion will rely heavily on student participation and preparation to consider the variety of spatial methods available and their implications on urban research and intervention. Woven throughout the semester is the development of a self-driven research project, through which students will engage and compare the methodological advantages and disadvantages of several assumptions, approaches, analyses, and datasets