Alex Michels

Selected Publications

1. CEUS

   Customized decision-making support per location’s characteristics of spatial accessibility: A case study of emergency healthcare in New York City

   Park, Jinwoo, Lyu, Fangzheng, Michels, Alexander, Zhang, Ian, and Wang, Shaowen

   Computers, Environment and Urban Systems, 2026

   Abs DOI

   Dynamic spatial accessibility, incorporating temporal dimension into spatial accessibility measurements, is in the spotlight because of significant temporal variations in urban phenomena (e.g., traffic congestion or floating population). Despite its importance, there are two significant gaps, particularly in existing healthcare access literature: 1) limited consideration of the dynamic nature in healthcare accessibility, and 2) limited support of dynamic spatial accessibility for practical policymaking. Our study aims to improve spatial accessibility measurement using time-dependent data and to summarize temporal sequences to support effective decision-making. Specifically, we measure hourly changes in spatial accessibility to emergency healthcare resources in New York City with a Gaussian two-step floating catchment area (G2SFCA) method. We then employ sequence analysis to detect and cluster unique temporal changes in accessibility measures. Our results reveal that each location provides distinct temporal changes in its healthcare accessibility owing to the dynamic urban phenomena. In addition, we find that census tracts can be grouped into 14 clusters based on combinations of temporal changes (i.e., stationary versus non-stationary) and accessibility levels (i.e., high, moderate, or low). Therefore, our findings can inform flexible policy responses to the diverse needs of locations. For example, to improve accessibility, certain areas could extend the operating hours of existing healthcare resources, or additional hospitals could be established in other locations. Given that decision-making is often constrained by limited resources, our study sheds light on how to make optimal allocations of healthcare resources to effectively reduce inequality in access.

2. Geog Analysis

   An Areal Approach to Spatial Accessibility Analysis

   Michels, Alexander, Park, Jinwoo, Kang, Jeon-Young, and Wang, Shaowen

   Geographical Analysis, 2024

   Abs DOI Code Data

   Place-based spatial accessibility quantifies the distribution of access to goods and services across space. The Two-Step Floating Catchment Area (2SFCA) family of methods have become a default tool for spatial accessibility analysis in part due to their intuitive approach and interpretability. This family of methods relies on calculating catchment areas around supply locations to estimate the area and population that may utilize them. However, these “catchment areas” are generally defined by origin-destination matrices of travel-time, giving us point-to-point distances and not polygons with actual area. This means that population geographies (census tracts, blocks, etc.) are binarily included or excluded, with no room for partial inclusion. When using nongranular data, which is often the case due to data privacy restrictions, this has the potential to cause significant errors in accessibility measurements. In this article, we propose Areal 2SFCA: a new approach that considers the area of overlap between travel-time polygons and population geographies. We demonstrate the effectiveness of the Areal 2SFCA method using a case study that compares the Enhanced Two-Step Floating Catchment Area (E2SFCA) and Areal E2SFCA for the state of Illinois in the USA using multiple population granularities.

3. SoftwareX

   CyberGIS-Compute: Middleware for democratizing scalable geocomputation

   Michels, Alexander C., Padmanabhan, Anand, Xiao, Zimo, Kotak, Mit, Baig, Furqan, and Wang, Shaowen

   SoftwareX, 2024

   Abs DOI Code

   CyberGIS—geographic information science and systems (GIS) based on advanced cyberinfrastructure—is becoming increasingly important to tackling a variety of socio-environmental problems like climate change, disaster management, and water security. While recent advances in high-performance computing (HPC) have the potential to help address these problems, the technical knowledge required to use HPC has posed challenges to many domain experts. In this paper, we present CyberGIS-Compute: a geospatial middleware tool designed to democratize HPC access for solving diverse socio-environmental problems. CyberGIS-Compute does this by providing a simple user interface in Jupyter, streamlining the process of integrating domain-specific models with HPC, and establishing a suite of APIs friendly to domain experts.