The Cutting Room Floor: Ideas in Progress… or ones that Finally Made It to the Big Time
The documents on this page come straight from the classrooms of the UMBC GIS Program where our ideas hit ground. These working papers, assignment guides, and supporting materials aren’t all polished for journals or wrapped in academic jargon. They’re practical, grounded, and built for impact on regular work and tasks that GIS jockeys and spatial analysts encounter every day. Whether you’re curious about the mechanics of spatial measurement, wrangle geographic data in various programming languages, creating distinguished maps, the internal workings of GIS, or how we integrate GenAI into coursework this is where we share the work as it’s happening… rough edges and all.
Click on a topic for all materials related to a class or theme.
Mapping & Cartography – Cool Stuff for Better Maps: The supporting materials for the Just Maps course are designed to deepen students’ understanding of the cartographic process through the lens of analytical purpose and graphic design principles. The resources included here are guides students for students in refining their maps not simply as visual aids, but as analytical tools that must communicate complex spatial information with clarity and precision. Topics covered include how to identify and articulate analytical goals, how to select appropriate visual variables like color and classification schemes, and how to apply graphic design principles such as visual hierarchy, ink efficiency, and clutter reduction. The materials encourage students to think critically about every element of map construction and to make deliberate design decisions grounded in analytical reasoning.
The Data to Ink Ratio with Mapping – An Editor’s Perspective offers a critical reflection on how cartographers can improve the effectiveness of their maps by prioritizing the visual display of data over decorative or redundant elements. Drawing from graphic design theory and practical mapping examples, it encourages analysts to evaluate every visual component of a map through the lens of necessity and clarity. The document promotes a disciplined, editor-like mindset when designing maps, where less ink used for non-data elements leads to more powerful and trustworthy visual communication.
GIS Mechanics – Tinkering Under the Hood: Ever wonder what really goes on under the hood of your GIS? This section pops the hood to the engine that drives geographic data management and analysis, covering topics like how datasets are structured, how coordinate systems and spatial references influence map output, how things like ObjectIDs keep track of geo-processed records, spatial and attribute indexing, topology rules, and data‑type constraints shape what is possible (and reliable) in the data, or how storage formats affect performance, integrity, and interoperability. The goal of this section is to give students and practitioners not just an “at-a-glance’ understanding of how the system operates tools, but a deeper appreciation of the structural and technical mechanics that underpin every GIS, because good analysis and maps depend as much on good data management.
This technical paper The Use and Limits of the Object/Feature ID in Geo-Processing explores the technical, often misunderstood role of the ObjectID or FeatureID in GIS software like ArcGIS Pro and QGIS. It explains that these IDs are a system-managed row counters, not a stable feature identifier and not be used for managing data relationships. The document highlights valid use cases, such as when doing a Spatial Join or Near Identification where feature lineage is preserved for traceback. But outside of these narrow cases, though, substantive IDs should be used for joins, summaries, and other mapping tasks. Misuse of the internal IDs can introduce critical errors into data integrity.
Spatial Analysis Issues – The Trouble Beneath the Surface: Maps lie. Or at least, they mislead, if you don’t know what to watch for when putting data together or assess the analysis framework. This section dives into the gritty edge of spatial analysis, i.e. the stuff they don’t always cover in textbooks or mediocre classes. Here, we unpack articles that explore the unseen forces that can wreck your results, such as aspects of the Modifiable Areal Unit Problem (MAUP) not covered, Simpson’s Paradox, Ecological Fallacy, Regression to the Mean, Spatial Autocorrelation gone rogue, and other statistical pitfalls that can quietly sabotage otherwise clean analysis. These aren’t just quirks that you can get by with, they’re structural problems that contort geography and data like a yoga class gone wrong. Understanding them is what separates a technician from a spatial thinker.
This paper, Changing Geographic Units and the Analytical Consequences, explores how changing the geographic unit of analysis—from census tracts to police divisions—in Charlotte, NC dramatically alters the statistical relationship between residential foreclosure density and violent crime. At the finer tract level, the relationship appears negative, while at the coarser division level it flips to positive, illustrating a classic case of Simpson’s Paradox. The analysis highlights how not using the correct scale misleads pattern interpretations when spatial aggregation masks local variation. The paper serves as a cautionary tale policy makers relying on aggregate data for decision-making without fully considering the modifiable areal unit problem (MAUP) and scale effects.
Spatial Analysis that Hits the Pavement: This section features applied spatial analysis in the wild, not theoretical debates or idealized data, but real-world work tackling concrete problems society faces on a daily basis. These papers show how GIS and spatial methods are used to answer practical questions about cities, neighborhoods, environmental conditions, and human behavior. Whether it’s mapping urban vulnerability, evaluating equity in service delivery, or analyzing patterns in environmental risk, these studies walk the line between method and mission — showing exactly how spatial analysis drives insight, not just maps. If you’re looking to see how classroom skills translate to field-ready solutions, this is where the work gets down in the dirt and provides guidance for use in the field.
In The Ground Rent Machine by Dr. Dillon Mahmoudi, the paper unpacks how a centuries-old legal structure, a.k.a. ground rent, has contributed to racialized dispossession in Baltimore. Through a detailed spatial analysis of property records, eviction data, and racial demographics, the authors reveal how this mechanism disproportionately burdens Black homeowners, feeding systemic inequality. The study bridges archival research with modern GIS tools to track dispossession spatially, exposing how private profit and public neglect converge. It’s a vivid demonstration of spatial analysis used not just to map problems, but to trace the historical and structural forces behind those problems.



