Stephen C. Sanders

This study applied the Appalachian Regional Commission’s Distressed Areas Classification System at the census block group level across New York’s 14-county Southern Tier to examine localized socioeconomic vulnerability. Using a generalized linear mixed model (GLMM) via glmmTMB, the analysis incorporated demographic, economic, and spatial predictors to assess distress risk and evaluate the adequacy of the ARC’s distressed areas classification framework. Results revealed that unemployment (local and neighboring), urban development, and population density were strong predictors of distress, although a low sensitivity (27%) and random effect analysis depict a highly cautious predictive model and significant geographic variation in unexplained risk. The study highlights the limitations of county-level classifications and the need for fine-scaled, spatially aware policy targeting.

Inspired by final project completed for GEO 511 - Spatial Data Science during the Fall 2024 semester at the University at Buffalo, and included in Competency Portfolio in partial fulfillment of the M.A. in Geography.

This essay investigates how the Western-imposed treaty port system in China — initially a product of coercive diplomacy and military conflict — laid the groundwork for China’s later emergence as a global economic power. The study begins by examining the Confucian-informed tributary system that structured pre-modern Chinese foreign relations and trade hierarchies. It then details the Opium Wars and the subsequent unequal treaties that opened over 100 port cities to foreign control. The essay explores the spatial and infrastructural transformation of treaty ports, especially through the development of “bunds” and foreign-managed municipal councils. A critical focus is placed on the evolution of multi-modal transport networks, including the construction of railway systems under foreign and domestic control, and their role in deepening China’s integration into global trade flows. The final sections assess how containerization and port reconfiguration in the 20th century, alongside China's Belt and Road Initiative, reflect a reversal of roles; where China, once subject to external imposition, now exerts global maritime influence. The essay argues that the treaty port era, while marked by subjugation and exploitation, inadvertently catalyzed infrastructural and institutional developments that enabled China’s later economic ascendancy.

A systematic review of the city's centerline (road) GIS layer in relation to other datasets (e.g., Right of Way, parcels, County road data, aerial imagery) to flag issues or areas that need additional clarification. The main issues that needed to be marked are those concerning spatial accuracy, topology, dangles/gaps, missing data, and attribution. Any issue or anomaly was marked up using the provided mark-up layers with an issue type and comment, or they are identified in other output layers that would necessitate looking at certain attribution values to determine which features have certain issues (e.g., dangles/gaps, address continuity issues, railroad intersection points). The final deliverables will help the city assess the QA/QC after it has been delivered and make appropriate data changes to the Centerline layer.

Included is a Python script called Intersect_By_Attribute_Merge.py. The script allows the user to intersect an input layer based on a specified field and attribution values with a polygon layer. An example usage is to figure out which City Local or Private roads intersect with the parcel data as a means of pinpointing issues pertaining to "Maintained By" attribution issues in the Centerline master layer. This is a fairly limited script that requires specifying the field (e.g., MAINTAS) and target attribution values of the field (e.g., City Local, Private) from the input layer (e.g., the Centerline layer) that are to be intersected in relation to a polygon layer (e.g., Parcels). If more than 1 attribution value is targeted, then the script will merge the resulting intersect layers into a single merge layer. You can then change the symbology of the merge layer to a graduated color scheme to visualize the features based on the targeted field values. This script may be converted into an ArcGIS Pro toolbox at some point in the future.

This was my capstone experience/internship through Monroe Community College in collaboration with the City of Traverse City, Michigan.

This study examines the spatial and socioeconomic determinants of violent crime in Buffalo, New York, from 2010 to 2023 using a Generalized Linear Mixed Model (GLMM). Incorporating both fixed effects including per capita income, educational attainment, local and neighboring racial composition, and police surveillance camera presence, as well as random effects for census block groups, the model assesses how neighborhood characteristics influence violent crime occurrence.

Search Twitter for Tweets containing a keyword, then write results to a CSV/XLSX file and/or map the results using ArcGIS Pro or GeoPandas. Tweet data can be imported from a CSV file/XLSX, with support for pulling data for multiple keywords in the same session. You can append your count results to shapefiles (ArcGIS Pro & GeoPandas) and feature classes within geodatabases (ArcGIS Pro). Written entirely in Python (Pandas/GeoPandas, ArcPy, Matplotlib).

Explores food insecurity in the City of Buffalo based on each census tract's poverty level and walking distance proximity to a grocery or corner store. Includes a chloropleth map that showcases the relationship between the above variables. Used a color scheme generated by Paletton.com. Data obtained, analyzed, and displayed using QGIS, Google Sheets, Google Earth Pro, and Google Maps.

Investigates any vegetation changes between 1989 and 2019 around the Western Aral Sea that have occurred due to the shrinkage of the Aral Sea, and how past and present restoration projects may have influenced these changes since they began. Also displays the extent of the shrinkage that the Aral Sea has undergone. Uses Landsat data from GLOVIS. Data analyzed in ArcGIS Pro.

Determines potential sites for new public WiFi locations in the City of Rochester based on which census tracts are most in need. Considers percentage of households without internet access, proximity to a preexisting free WiFi location, and population density of school-aged people. Data analyzed in ArcGIS Pro.

Investigates if there is a correlation between homicide rate, median household income level, and the number of parks, playgrounds, and other publicly accessible areas within census tracts of the City of Rochester. Data analyzed using ArcGIS Pro and Google Sheets.

An opinion editorial about the importance of indigenous Sámi reindeer herders in Norway's climate change mitigation strategy. Written for GEO 503 - Environmental Governance at the University at Buffalo.

The website for the Buffalo Firefighters (Local 282) was developed by me in mid-to-late-2017 in collaboration with e3communications, and was still used by them as their main source of communication with matters that concern the general public until around 2023. The website was built using WordPress and was hosted by GoDaddy.