Sanborn fire insurance maps contain a wealth of information about the historical built environment for thousands of cities and towns across the United States. In combination with geographic information systems (GIS) and other computational approaches, Sanborn maps have been used for various purposes and across a broad range of academic disciplines. This paper begins with a literature review that highlights representative examples of the use of Sanborn maps for visualization, spatial analysis, and 3D modeling and reconstruction, and summarizes the current state of the art for preparing Sanborn maps for use in GIS and deriving data from them. Next, a case study is presented that integrates several of these methods, namely using data derived from Sanborn maps through semi-automated approaches to create realistic 3D models of Poindexter Village, Ohio's first public housing development. The paper closes with a discussion of how demonstrated use cases of Sanborn maps relate to a "collections as data" framework and can inform future research directions for map and geography libraries. This work will benefit scholars using Sanborn maps to study diverse aspects of urban history, as well as the library professionals who curate physical and digital collections of historical maps to support such uses.
Artificial intelligence (AI) is rapidly transforming industries worldwide, yet AI literacy remains significantly underdeveloped, particularly in fields like urban planning and design. While the influence of GenAI and GeoAI is expanding across academic disciplines and programs, a noticeable gap exists in the literature regarding how urban planning and design education can effectively integrate these technologies. Historically, urban planning has been cautious about embracing new technologies, largely due to the inherent complexity of both the field and the urban systems it seeks to shape. However, GenAI and GeoAI hold immense potential to enhance planning and design practices by enabling more informed decision-making. It is essential to equip students with the skills and confidence to engage critically and creatively with these tools. This paper addresses the current educational shortfall by proposing course structures and pedagogical strategies that lay the groundwork for GenAI and GeoAI integration in planning curricula. By doing so, we aim to empower students, especially those who have traditionally struggled with or distrusted advanced technologies, to overcome barriers in data collection and analysis. Ultimately, this framework fosters not only technical proficiency but also a more open and innovative mindset toward the role of technology in shaping the development and growth of cities.
The John R. Borchert Map Library at the University of Minnesota developed a K-12 Summer Teacher Fellowship in 2023. The program was modeled on programs at other map libraries through research and conversation. This article explores how the program is related to the continuing relevance of map libraries and map librarianship, the impetus for exploring a K-12 program, and the process of developing the program. The article then examines the program alongside three similar initiatives around the country. These four case studies offer a set of common elements of success that could inform the development of similar programs elsewhere, as well as justification for funding such a program. The article highlights how a collaborative approach builds a strong community of teacher fellows and demonstrates how map libraries can function as intersectional hubs with the ability to bridge the gap between the University's extensive academic research resources and the practical needs of K-12 educators. The article includes an appendix with example calls for proposals, acceptance and rejection letters, lesson plan templates, and follow up surveys.
The Hermitage Plantation Guest Register project demonstrates how AI-assisted transcription can unlock geospatial data embedded in difficult-to-transcribe historical documents. Using a customized large language model and a field-based transcription platform in combination with traditional humanistic research methods, the authors transformed a 159-page handwritten register of plantation tourists from the 1930s into a structured dataset, enabling analysis of visitor origins and travel patterns. The resulting workflow offered new insights into the history of early plantation tourism and models a replicable, low-barrier method for extracting geospatial data from handwritten archival materials.
This article examines the implementation and evolution of Geographic Information Systems (GIS) instruction within a culturally responsive science, technology, engineering, and mathematics (STEM) outreach program for Native American high school students over a three-year period. Through detailed case studies and comparative analysis, we explore how different GIS platforms can support place-based learning and digital storytelling while addressing the unique educational needs of Native American students. The StoryMaps implementation emphasized individual creative expression and multimedia narrative development, enabling students to create sophisticated digital stories connecting personal experiences to geographic spaces. The Survey123 implementation focused on collaborative data collection and shared knowledge construction through campus mapping activities. Student outcomes demonstrate high levels of engagement and technical skill development across both platforms, with Survey123 showing particular effectiveness in accessibility and sustained participation. Our findings highlight the importance of technology selection that prioritizes pedagogical objectives over technical sophistication, the value of place-based learning approaches that honor Indigenous spatial knowledge traditions, and the potential for GIS integration to support both STEM skill development and cultural identity expression. This work contributes to understanding how digital mapping technologies can be implemented within culturally responsive educational frameworks while providing practical guidance for educators seeking to integrate spatial thinking into diverse STEM programming.
In early 2025, the Editorial Board of the Journal of Map and Geography Libraries formed a working group to develop strategies to increase the rate of Open Access (OA) publication in the journal. In addition to the option for Gold OA, the journal has a zero-embargo policy that allows authors to post their articles in a repository immediately upon publication, i.e., Green OA. To assess the current status of OA publication in the journal, the working group began by inventorying all peer-reviewed reports and articles published from 2011 (Volume 7, Issue 1) to 2025 (Volume 21, Issue 1-2). This report shares our findings that 45.4% of peer-reviewed publications in JMGL are available OA and have a significant citation advantage over toll-access publications. We also report on the deliverables created for the editors to use when communicating about OA publishing options, including email templates and a "Gold vs. Green OA" comparison table. The discussion explores future directions that might be taken to better understand the context of OA publishing within and beyond this journal and summarizes the benefits of OA publishing for strengthening the profession of map librarianship.
Much of the spatial data held within geospatial library collections exists only in analog form. So long as the processes of georeferencing and feature digitization remain labor-intensive and slow, this will remain the case. Recent years have seen substantial advances in AI-driven automated recognition of map text. This paper introduces a project designed to leverage these advances to speed the creation of digital orthomosaics using historical aerial photographs. The project utilizes the mapKurator system for text recognition as well as a Mask R-CNN model for further text detection. These tools serve as part of a workflow to create center points and attendant metadata for individual aerial photos, which are necessary for creating orthomosaics using ArcGIS Pro software. The results gesture toward a future where Historical GeoAI methods enable more efficient digitization of the analog spatial data contained within maps and aerial photographs.
Research on the materiality of Spanish Colonial artistic heritage contributes to our knowledge about culture, society, and artistic practices of the Spanish Americas. This article presents the results of an interdisciplinary and multi-analytical investigation on the Manuscript Map of the Dagua River Region, a large and vibrantly colored cartographic work produced in Cali, Colombia in 1764 and held today in the Library of Congress' Geography and Map Division. To date, material analysis studies have identified colorants used in Mesoamerican codices and pigments used in the creation of manuscripts, paintings, and sculpture from the Spanish colonial Andes (Argentina, Bolivia, Chile, Peru). Less analysis has been undertaken on Spanish colonial manuscript maps from South America. This article aims to address this gap in the scholarship and provides some of the first information available on pigments used in eighteenth-century manuscript maps produced in the Spanish Americas. Noninvasive techniques including multispectral imaging, X-ray fluorescence spectroscopy, fiber optic reflectance spectroscopy, and Fourier-transform infrared spectroscopy reveal that the map was made of imported paper and regionally mined minerals.
Large language models (LLMs) have gained rapid prominence for their perceived utility for various workflows. At the University of Colorado Boulder, we tested incorporating these technologies into a metadata workflow involving the identification of geographic landmarks to measure their rate of success in this task. We tested three of the most popular LLMS-Chat-GPT, Claude, and Gemini-on a corpus of images and analyzed the results to determine whether or not they were appropriate tools for this task. Our analysis concludes that while these tools may be good for general descriptive work, they are currently unsuitable for precise geographic identification.
Placenames, which link maps to historical records are vital for understanding spatiotemporal societal changes. Traditional workflows require scanned historical maps to be georeferenced before publishing in GIS-readable formats or web map services. Querying, however, typically remains limited to layer metadata, hindering historical placename identification across periods. This paper presents a complete pipeline that integrates batched placename extraction and large language models (LLMs) to enable smart spatial search. Using mapKurator, we batch-extracted text from 20th-century Web Map Tile Service format maps with simultaneous geolocation capture. Indexed placenames were stored in an Elasticsearch database integrated with OpenAI's LLMs to extract spatiotemporal information from free-text user queries. An elastic, fuzzy-search engine retrieved relevant results exportable for GIS applications. By merging LLMs with mapKurator, a smart spatial search system was developed that efficiently compiles, visualizes, and overlays historical map layers on a Web GIS platform, significantly enhancing the searchability and analysis of historical maps.
Mapping Chicagoland is a National Endowment for the Humanities (NEH)-funded project to make openly available over 5,000 georeferenced historical maps of Chicago from three institutions: The Chicago History Museum, the Newberry Library, and the University of Chicago Library. Mapping Chicagoland strategically deployed collaboration at phases that benefited most - such as map selection, staffing, metadata creation, and user engagement - while leveraging centralized coordination for digital workflows. This paper presents the processes and decision points shaped by partnership, explores where collaboration enabled broader coverage and continuity, and discusses lessons learned in choosing when to collaborate and when to streamline. This model of collaboration resulted in a more diverse digital collection, deeper institutional memory, and an increased public impact. The resulting open-access, georeferenced map images enable scholars worldwide to pursue broad research goals and incorporate maps and spatial data into their teaching.
Digital tools for humanistic inquiry (digital humanities) have become important parts of how people engage with historical collections. For map and geography library workers, developments in open data, resource digitization, frameworks for discovery portals, and proliferation of new spatial data standards all factor into how the digital humanities have become ubiquitous aspects of contemporary librarianship. This comment describes the Allmaps software ecosystem and how this set of technologies for annotating and curating maps has developed as an open tool with diverse stakeholders and fluctuating funding streams. With an eye to sustainability and equitable access, the authors examine the social infrastructure that is necessary to inform and sustain tools that advance the spatial humanities and access to historical map collections.
Historic orthomosaics of aerial photography have numerous research and public uses. As such, academic libraries in the USA are increasingly interested in orthorectifying their historic aerial photography collections for use in geographic information systems. How much effort this requires, and which collections constitute good candidates for processing remain unanswered, but important questions. The present study produced 11 historic orthomosaics of library collections using both ArcPro and Metashape software. Nine of these collections met a 10-m positional accuracy target using between 0.19 and 1.20 ground control points per photograph. More recently captured collections of several hundred photographs and good image quality that depicted largely urban landscapes produced the best results with the least effort. Whether a collection used fiducial markings in its alignment or the number of tie-points used per photograph in the orthorectification workflow were not found to affect results. Although limited in its scope, the present study was a first step for the library geospatial community to better understand which historic aerial photography collections are good candidates for orthorectification and how much effort it would take to perform this service.
This study aims to provide detailed information on the geospatial data management practices of Canadian academic libraries as they relate to providing a quality user experience. In the summer of 2024, the researchers conducted six semi-structured interviews with library staff members at six Canadian institutions (Carleton University, Dalhousie University, University of Alberta, University of British Columbia, University of Manitoba, and the University of Toronto) about their geospatial data management practices and priorities. This research outlines the systems, strategies, and approaches taken at these institutions related to the tasks of curating, managing, distributing, or supporting the use of geospatial data. Analysis of the interview transcripts revealed common challenges among the institutions, such as accounting for a variety of expertise levels among users, as well as insufficient data discovery infrastructure, funding, and staff capacity. The data also suggests that the demand for geospatial data is growing, that staff providing these services are currently under-resourced, and that there may be significant advantages to consortium models for data access and management.
