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We define quantitative map literacy (QML), a cross between map literacy and quantitative literacy (QL), as the concepts and skills required to accurately read, use, interpret, and understand the quantitative information embedded in a geospatial representation of data on a geographic background. Long used as tools in technical geographic fields, maps are now a common vehicle for communicating quantitative information to the public. As such, QML has potential to stand alongside health numeracy and financial literacy as an identifiable subdomain of transdisciplinary QL. What concepts and skills are crucial for QML? The obvious answer is, "It depends on the type of map." Therefore, our first task, and the subject of this paper, is to develop a framework to think and talk about the panoply of maps in a way that permits us to consider the range and distribution of QML content. We use an equilateral triangular plot to conceptualize maps in terms of locational information (L), thematic information (T), and generalization-distortion (G-D), and parameterize the plot with an L/T ratio (horizontal; reflecting the historical practice of cartographers to distinguish locational-reference maps from thematic maps) and G-D levels increasing from base to apex. We show positions for a wide variety of maps (e.g., topographic maps, weather maps, engineering-survey plots, subway maps, maps of air routes, a cartoon map of Orlando for tourists, driving-time maps, county-wide population maps, county-wide multivariable population and income maps, world political map, land use maps, and cartograms). The analysis of how these maps vary across the triangle allows us to proceed with an examination of how QML varies across the panoply of maps.

We define quantitative map literacy (QML), a cross between map literacy and quantitative literacy (QL), as the concepts and skills required to accurately read, use, interpret, and understand the quantitative information embedded in a geospatial representation of data on a geographic background. Long used as tools in technical geographic fields, maps are now a common vehicle for communicating quantitative information to the public. As such, QML has potential to stand alongside health numeracy and financial literacy as an identifiable subdomain of transdisciplinary QL. What concepts and skills are crucial for QML? The obvious answer is, "It depends on the type of map." Therefore, our first task, and the subject of this paper, is to develop a framework to think and talk about the panoply of maps in a way that permits us to consider the range and distribution of QML content. We use an equilateral triangular plot to conceptualize maps in terms of locational information (L), thematic information (T), and generalization-distortion (G-D), and parameterize the plot with an L/T ratio (horizontal; reflecting the historical practice of cartographers to distinguish locational-reference maps from thematic maps) and G-D levels increasing from base to apex. We show positions for a wide variety of maps (e.g., topographic maps, weather maps, engineering-survey plots, subway maps, maps of air routes, a cartoon map of Orlando for tourists, driving-time maps, county-wide population maps, county-wide multivariable population and income maps, world political map, land use maps, and cartograms). The analysis of how these maps vary across the triangle allows us to proceed with an examination of how QML varies across the panoply of maps.

Disaster-impacted communities are expected to experience a brief economic disruption, but less resilient communities are at risk for prolonged economic decline, increased unemployment, and shifts in industries and workforces. Florida is historically susceptible to hurricanes, having experienced six major hurricanes (> 110 mph winds) from 2000 to 2021, including Hurricane Michael, a rare Category 5 (> 157 mph winds) in October 2018 that devastated the already economically vulnerable Florida Panhandle. The area experienced a stagnant recovery, and it wasn't until 2021 that a state-funded economic revitalization program was implemented to aid business restoration. An analysis of unemployment and employment rate trends for all Florida counties that experienced a major hurricane between 2000 and 2021 was conducted to quantify Hurricane Michael's economic impact compared to the other major hurricanes. Using difference-in-differences analysis, results found that the coastal counties impacted by Hurricane Michael experienced up to 11 months of significantly increased unemployment compared to other major Florida storms, from which counties only experienced up to two months of increased unemployment. Additionally, to provide context to the results of Hurricane Michael, observations of the volume trend of employee counts by industry were used to show that during the post-storm year the area saw a reduction in the hospitality, retail, health care and social assistance, and educational services workforces, yet an increase in the construction sector. This study highlights the need for increased disaster resilience against economic disruptions, the anticipation of post-disaster workforce disruptions, as well as support services for workers in a longstanding disaster recovery area. Furthermore, while post-disaster revitalization programs can be beneficial, building economic resilience to support rapid adaptation and recovery is more sustainable.