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Geography professors

Official title Geography Teachers, Postsecondary (SOC 25-1064)

Also called Geography teacher, GIS professor, Human geography professor, Physical geography professor, Urban geography professor

In brief

In May 2025, BLS counted 3,330 US geography professors, with median pay of $97,590 a year. Of the BLS counts since 2021, the highest was 3,480, in May 2023, close to the May 2025 count. The earliest figure here is an estimate of 500 from 1920, not measured the same way as today's count. The last full technology era for geography professors: Deep learning for remote sensing and spatial data science, 2015 to 2023.

What the sources say

Official outlook

BLS projects employment to grow 2.7% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend.

Last updated .

Cite this page
APA

Future History. (2026, October 11). Geography professors: jobs and pay since 1920 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/25-1064

Chicago

Future History. "Geography professors: jobs and pay since 1920." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/25-1064.

BibTeX

@misc{futurehistory_25_1064, author = {{Future History}}, title = {Geography professors: jobs and pay since 1920}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/25-1064}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }

The access date is today's date on your device.

drag to travel through time
1925195019752000now
2026
Known then as Professor of Geography / Geographer (AAG era, physical geography dominant)
Known then as Geography Professor (quantitative revolution era, systematic subdisciplines)
Known then as Geography Professor / GIS Instructor (GIS integration era)
Known then as Geography Teachers, Postsecondary (BLS SOC 25-1064)
Known today as Geography Teachers, Postsecondary (BLS SOC 25-1064)
Projected to still be called Geography Teachers, Postsecondary (BLS SOC 25-1064)
Data from the May 2025 survey
US Employment
3K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$97,590
Est.

≈ $95,088 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1904

December 29, 1904: William Morris Davis founds the Association of American Geographers at the University of Pennsylvania in Philadelphia, establishing professional standards for geography as an academic discipline. Membership required original published research, distinguishing the profession from the amateur geographic societies that preceded it. Davis had been teaching physical geography at Harvard since 1878 and had developed the "cycle of erosion" framework that gave American academic geography its theoretical core. The AAG founding is the moment geography teaching at the postsecondary level became a profession with formal standards rather than an incidental activity of natural philosophers and surveyors.

Beat · 1948

The American Society of Professional Geographers merges into the AAG in December 1948 in Madison, Wisconsin, doubling the organization's membership and broadening it to include government and applied geographers alongside the research-university faculty who had been the original AAG constituency. The merger came just three years before Harvard's geography department closure, signaling the discipline's contraction at elite private universities at the same moment its professional base was widening.

Beat · 1951

Harvard President James Conant formally closes Harvard's geography department, reportedly declaring that "geography is not a university subject." The closure, documented in a 1987 Annals of the AAG article as an "academic war," became a defining trauma for US academic geography: if the most prestigious university in the country could decide geography did not belong in a research university, any department could be vulnerable. Harvard's closure was followed by Penn (1963), Yale (near-closure through the 1960s), and Columbia (1986). Dartmouth remains the only Ivy League university with an independent geography department today.

Beat · 1972

Geography bachelor's degree production in the United States peaks at 4,300 in 1971-72, and PhD production peaks at 217 in 1973-74. The discipline is at its maximum academic footprint, driven by the quantitative revolution's transformation of geography into a rigorous analytical field and by the post-1964 National Defense Education Act amendments that boosted graduate enrollment. Within five years the peak will give way to a prolonged contraction as degree production declines faster than the overall university market, and hiring freezes at public universities begin to affect geography faculty demand.

Beat · 1986

Columbia University closes its geography department due to "insufficient popularity and funding" -- the last Ivy League closure of a geography program and one of the most symbolically significant. Columbia's department had been described as "easily the most prodigious of the Ivy League" at its peak. The 1986 closure coincides with geography's employment nadir: by 1987-88, new geographers entering the labor market are at two-thirds of their 1972 peak. The discipline will begin its recovery within five years, driven by GIS.

Beat · 1994

The National Research Council launches its "Rediscovering Geography" study (published 1997) in response to sustained concern about geography's institutional fragility. The study documents the 47% growth in geography undergraduate enrollments from 1986-87 to 1993-94 -- the GIS recovery -- but also notes that the discipline remains the only major academic field without dedicated national education funding in the United States. The report projects 617 AAG member retirements in the decade from 1994 to 2004 and recommends a sustained national effort to recruit and train new geography faculty to prevent a hiring gap.

Beat · 2016

The Association of American Geographers changes its name from the "Association of American Geographers" to the "American Association of Geographers" to better reflect its international membership, which had reached one-third international by 2013. AAG membership peaks at nearly 12,500 around this time. The name change reflects the discipline's increasingly global research community; geography faculty in the US now routinely collaborate with colleagues in the UK (Royal Geographical Society), Australia (Institute of Australian Geographers), and across Europe -- facilitated by GIS data standards, shared satellite imagery platforms, and open-source spatial software that make international spatial research collaboration routine.

How to read this number

OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.

Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.

Official statistic: Copied by a script from a statistics agency table or a published study's table, not retyped by hand. BLS figures and the forecast and exposure tables are also re-checked against that table on every data run. Researched context: Researched from the cited source rather than copied from it by a script, so it is not machine-checked yet. Spot a mistake? Each figure has a “Report an error” link.

Cited forecasts · present → 2035

Will AI replace geography professors? What the research says

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.

What published forecasts say
Forecast change in the number of people doing this work, as published by each named source. Bars share one scale on every role, centred on zero and reaching the end at ±30%. Grey marks a small change, 3% or less either way.
BLS Employment Projections 2025-35
→ 2035
+2.7%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 25-1064 (Geography teachers, postsecondary): 4.1 thousand jobs in 2025, projected 4.2 thousand in 2035, a change of +0.1 thousand (+2.7%). Matrix employment counts all jobs in the occupation, including self-employed workers. The average for all occupations in this cycle is +3.5%.
Official statisticReport an error
How exposed is this work to AI (research measures)
Scores as published by each study. Each row says what it measures. These measure what AI could technically do, not forecasts of jobs lost.
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
46.6%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 25-1064.00 Geography Teachers, Postsecondary. Shown: human-rated β = 0.466, the share of the occupation's tasks an LLM could do in at least half the time at equal quality, counting tasks that need LLM-powered software at half weight (β = E1 + 0.5 × E2). Other published measures for this occupation: human-rated α (LLM alone) 0.25 and γ (all LLM-assisted) 0.682; GPT-4-rated β 0.477. This measures how much of the work an LLM could touch, not how many jobs disappear.

Official statisticReport an error
Today, in this role

What's changing day to day for geography professors

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereDesign and teach cartography and map design courses, integrating Mapbox AI-assisted map design tools (natural-language styling, automated choropleth generation from CSV data) and AI label placement to show students how professional-grade maps are now produced faster and with higher visual quality, while building critical cartographic literacy around what makes an AI-generated map misleading, how data classification choices shape choropleth interpretation, and the design decisions AI cannot make without understanding the intended audience and argument.

Design and teach cartography and map design courses, integrating Mapbox AI-assisted map design tools (natural-language styling, automated choropleth generation from CSV data) and AI label placement to show students how professional-grade maps are now produced faster and with higher visual quality, while building critical cartographic literacy around what makes an AI-generated map misleading, how data classification choices shape choropleth interpretation, and the design decisions AI cannot make without understanding the intended audience and argument.[10],[8]

Where your edge is

Cartography is the sub-discipline most directly disrupted by AI in 2025–2026. Mapbox AI Map Studio accepts natural-language styling commands and generates publishable choropleth maps from CSV uploads in minutes: tasks that required weeks of manual QGIS, PostGIS, and CSS styling. The pedagogical response documented in AAG 2025 cartography sessions: build the AI cartography workflow into the course explicitly, then build the critical cartographic literacy around it. Teach students to classify the same choropleth dataset using equal intervals, quantile, natural breaks, and Jenks, and have them explain how each AI-generated map supports a different political argument about the phenomenon being mapped. That critical exercise, using Mapbox AI to produce four different maps and then identifying which one is "least misleading" given a specific communication purpose, teaches cartographic judgment that AI cannot itself supply and that employers in GIS, journalism, and policy increasingly demand.

AI is sitting alongside you hereCompile, administer, and grade examinations: using Gradescope AI-assisted answer grouping for high-volume introductory geography and GIS courses (map interpretation questions, region identification, physical geography processes), and designing map-making and spatial analysis projects that require students to submit and defend original fieldwork data or spatial analytical choices that AI cannot generate on their behalf.

Compile, administer, and grade examinations: using Gradescope AI-assisted answer grouping for high-volume introductory geography and GIS courses (map interpretation questions, region identification, physical geography processes), and designing map-making and spatial analysis projects that require students to submit and defend original fieldwork data or spatial analytical choices that AI cannot generate on their behalf.[11],[8]

Tools picking this up
Where your edge is

Gradescope's AI answer grouping handles short-answer and identification-style geography assessments efficiently (map region identification, process-explanation questions, and multiple-choice physical geography content) deployed at thousands of institutions including programs with large-enrollment introductory geography courses. Turnitin AI detection provides a flag for essay-style assignments. The high-value assessment redesign response documented in AAG 2025 teaching sessions: replace take-home written regional geography essays (highly AI-generatable) with submitted original spatial analysis projects using real field data or site-specific GIS analysis. A student who submits a map produced from GPS tracks they collected in a local field exercise, accompanied by a written interpretation defended in an office-hours oral check, has demonstrated geographic skills AI cannot have generated for them. That combination (real spatial data, original analysis, oral defense) is currently the gold standard for AI-resilient geography assessment.

AI is sitting alongside you herePrepare course materials (syllabi, GIS lab instructions, lecture slides, and reading guides) using ChatGPT Edu to generate first-draft content for introductory regional geography, physical geography, and environmental geography courses, then editing with geographic expertise to ensure theoretical accuracy, update with current data (population statistics, climate projections, geopolitical boundaries) that AI training data does not include, and incorporate a course AI-use policy aligned with the institution's academic integrity framework.

Prepare course materials (syllabi, GIS lab instructions, lecture slides, and reading guides) using ChatGPT Edu to generate first-draft content for introductory regional geography, physical geography, and environmental geography courses, then editing with geographic expertise to ensure theoretical accuracy, update with current data (population statistics, climate projections, geopolitical boundaries) that AI training data does not include, and incorporate a course AI-use policy aligned with the institution's academic integrity framework.[1],[8]

Where your edge is

ChatGPT Edu can generate a reasonable physical geography syllabus, draft GIS lab instructions for a geodata projections exercise, or produce a regional geography reading guide for a South Asia unit in minutes. The expert editing step addresses geography-specific failure modes: AI generates geographically plausible but often outdated regional data (population figures, territorial boundary claims, climate statistics), conflates physical and political geography at inappropriate scales, and cannot incorporate discipline-specific theoretical frameworks (world-systems theory, political ecology, critical cartography) into course content without expert steering. Use NotebookLM to synthesize the journal articles in a new course unit into a structured themes document. Invest the recaptured prep time in updating regional statistics and current-events examples: the content geography courses most urgently need and that AI alone cannot supply.

Where geography professors go next

Natural next steps for someone with your foundation: not exits, evolutions.

What each move takes

A direction you could grow

Geographic Information Systems Technologists and Technicians

Geography faculty with strong GIS backgrounds (particularly those who teach GIS courses, have proficiency in ArcGIS, QGIS, and Python-based spatial analysis, and have supervised GIS research projects) are natural candidates for GIS Analyst, GIS Specialist, and Spatial Data Scientist roles in government agencies (USGS, Census Bureau, EPA, state GIS offices), environmental consulting firms, urban planning departments, and tech companies deploying geospatial AI. The GIS professional market is growing faster than geography faculty supply, driven by geospatial AI adoption (autonomous vehicles, precision agriculture, logistics optimization, climate monitoring). Geography faculty who have incorporated ArcGIS GeoAI, Google Earth Engine, and Python spatial libraries into their teaching have the applied skill set that GIS employers value directly. The CRI delta is positive: GIS roles at the intersection of spatial analysis and AI are among the more resilient technical positions, as the interpretive geographic judgment that validates AI spatial outputs is harder to automate than the spatial analysis itself.

What you'd add
  • · Python geospatial stack: GeoPandas, Shapely, Rasterio, PyQGIS, and spatial data science libraries (spatialpandas, pysal) for production GIS workflows beyond teaching contexts
  • · Cloud GIS infrastructure: Google Earth Engine scripting (JavaScript/Python APIs), AWS Location Service, Microsoft Azure Maps for scalable spatial data processing and deployment
  • · Spatial database management: PostGIS and PostgreSQL for enterprise GIS; spatial query optimization; topology validation for production data pipelines
  • · ArcGIS Pro deep learning for production: model training and deployment for feature extraction, change detection, and object classification using Esri ArcPy and deep learning frameworks (TensorFlow, PyTorch integration)
  • · Geospatial project delivery: translating geographic research questions into scoped deliverables, documenting metadata to FGDC/ISO 19115 standards, and communicating spatial analysis results to non-GIS stakeholders in environmental consulting and government contexts
What it takesMost of your skills carry over
Tools of the era

How has the work of geography professors changed since 1904?

The tools that defined the work, one line per era. Select an era to see how it reshaped the work.

  • Topographic maps, field notebooks, and lantern slides (pre-quantitative era)

    The geography professor of the early 20th century taught with topographic maps, relief models, and -- after about 1910 -- photographic lantern slides projected onto lecture screens. The intellectual content of the job was dominated by Davisian physical geography: the cycle of erosion, landform classification, and the relationship between physical environment and human settlement. Fieldwork was central; Davis famously led student excursions to document landform sequences. There were no statistical or computational tools. The map was the primary analytical instrument, and reading it required training in surveying conventions, map projections, and the relationship between two-dimensional representation and three-dimensional terrain. This era ended as the quantitative revolution began reaching geography departments in the mid-1950s.

    Effect on the work

    The pre-quantitative geography faculty produced a relatively small cohort of graduates annually -- most US geography students were at land-grant universities training for secondary school teaching or government survey work. The discipline's reach into the broader university curriculum was limited; geography was often housed with geology or earth science departments rather than as a standalone faculty.

  • Statistical methods, aerial photography, and remote sensing (quantitative revolution)

    The quantitative revolution arrived in US geography through a handful of doctoral programs -- notably at the University of Washington, Northwestern, and the University of Chicago -- in the late 1950s and spread rapidly through the next decade. Geography faculty now needed to teach inferential statistics, spatial autocorrelation, and regression modeling alongside the traditional regional survey. Aerial photography, available to academic researchers through declassified World War II imagery collections, enabled systematic land-use mapping at scales previously impossible. The first satellite remote sensing data arrived with Landsat-1 in 1972, creating a new subdiscipline (remote sensing) and requiring geography faculty to develop technical competencies in image interpretation, radiometric correction, and spectral analysis that had no precedent in the pre-quantitative curriculum.

    Effect on the work

    The quantitative revolution drove the discipline's growth peak: bachelor's degree production grew through 1960 at its 1971-72 peak, and PhD production tripled. Faculty demand grew correspondingly. But the same revolution created the curricular complexity that eventually strained smaller departments: a geography faculty of three or four could no longer span physical geography, human geography, quantitative methods, and the new subdisciplines simultaneously.

  • Geographic Information Systems (ESRI ArcInfo, desktop GIS)

    Esri's ArcInfo debuted in 1982 as a mainframe system; its desktop migration through ARC/INFO and later ArcView 2 (1993) brought GIS into the standard geography curriculum during the late 1980s and 1990s. The transformation was profound: a discipline that had defined itself through field observation and statistical modeling now had a spatial data management and analysis platform that connected it directly to government agencies, urban planning departments, environmental consultants, and the emerging technology industry. Geography faculty who could teach GIS became among the most employable postsecondary instructors in the social sciences. Esri established a formal schools and universities program in 1992, providing institutional site licenses at reduced cost to academic departments and producing a generation of undergraduates who graduated with ArcGIS proficiency as a job-market credential.

    Effect on the work

    The GIS era reversed the discipline's employment decline: geography undergraduate enrollments grew 47% between 1986-87 and 1993-94 (NRC 1997). Departments that had been contracting added GIS lab positions and, at larger universities, dedicated GIS faculty lines. The GIS credential created a direct pipeline from geography BA to government GIS analyst or environmental consulting GIS specialist, transforming the discipline's career narrative.

  • Web GIS, spatial databases, and Python spatial stack (ArcGIS Online, PostGIS, GeoPandas)

    The 2000s brought web-based GIS into the curriculum: Google Earth launched in 2005 and gave geography students their first intuitive mental model of satellite imagery at planetary scale; ArcGIS Online arrived as an Esri product in 2010 and made collaborative spatial analysis browser-accessible without desktop software installation. PostgreSQL with the PostGIS spatial extension became the standard for spatial database instruction, and the Python geospatial stack (Shapely, GeoPandas, Rasterio, PyQGIS) emerged as the programming environment connecting geography to the broader data science ecosystem. Geography faculty had to develop and teach programming skills -- Python, SQL, JavaScript for web maps -- that required continuous professional development. The era also saw Google Earth Engine's debut in 2010, eventually putting petabytes of satellite data into a browser-based IDE accessible to any enrolled student.

  • Deep learning for remote sensing and spatial data science (ArcGIS Pro ML, TensorFlow, PyTorch spatial)

    Deep learning arrived in geography teaching through remote sensing: ArcGIS Pro 3.x introduced pretrained deep learning models for land cover classification from satellite imagery, object detection in aerial photography, and building footprint extraction -- tasks that had previously required semester-long manual digitizing projects. Google Earth Engine added built-in Random Forest and convolutional neural network classifiers. Geography faculty who taught remote sensing had to rebuild their lab curricula around machine learning workflows: the question shifted from "how do you manually digitize land cover categories?" to "how do you evaluate whether the AI model misclassified wetland as agricultural, and why?" Janowicz et al. (2023) in the Annals of the AAG described this as the defining GeoAI transition: from teaching GIS syntax to teaching spatial AI judgment.

    Effect on the work

    The ML-in-GIS transformation increased demand for geography faculty with deep learning and spatial data science skills, creating a wage premium for candidates who could teach Python-ML pipelines alongside traditional geographic methods. At the same time, the automation of semester-long manual classification exercises compressed the time required to teach certain technical skills, raising questions about how departments should use the recaptured instructional hours.

  • GeoAI and generative tools (ArcGIS AI assistants, Mapbox Location AI, ChatGPT Edu, Google Earth Engine LLM integration)

    Esri's ArcGIS AI assistants for ArcGIS Online (2025) accept natural-language queries and return spatial analysis results without requiring knowledge of GIS tool syntax -- making tasks like parcel proximity queries and land-cover classification accessible through conversational interfaces. Mapbox's Location AI platform (2025) enables natural-language geospatial queries and AI-powered map styling via MCP server integrations, compressing multi-step QGIS and API workflows into conversational interactions. ChatGPT Edu and NotebookLM entered geography course preparation workflows; faculty began integrating generative AI tools for lecture drafting, literature synthesis, and assignment design alongside the GIS automation tools. The defining pedagogical response: build AI tools into the curriculum explicitly, then build critical evaluation skills around them -- teaching students when to trust AI spatial outputs and when the model's training data or classification scheme is the wrong tool for the geographic question at hand.

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Geography Teachers, Postsecondary employment and pay by year

On record since1904
Latest US employment3,330 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$97,590 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+2.7% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 30 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
1920500n/aEst., American Association of Geographers Researched contextReport
1956n/a$5,200Est., University of Missouri Libraries Researched contextReport
19602,800n/aEst., National Academies Press Researched contextReport
19724,800n/aEst., National Academies Press Researched contextReport
1975n/a$16,200Est., AAUP Annual Report on the Economic… Researched contextReport
19883,200n/aEst., National Academies Press Researched contextReport
20004,200$54,080Est., O*NET 25-1064.00 (employment) Researched contextBLS OEWS 2000 (pay) Official statisticReport
20033,910$55,930BLS OEWS May 2003 Official statisticReport
20044,180$57,510BLS OEWS May 2004 Official statisticReport
20054,250$57,870BLS OEWS May 2005 Official statisticReport
20064,070$59,000BLS OEWS May 2006 Official statisticReport
20074,050$61,310BLS OEWS May 2007 Official statisticReport
20084,030$62,880BLS OEWS May 2008 Official statisticReport
20093,930$65,420BLS OEWS May 2009 Official statisticReport
20104,250$66,700BLS OEWS May 2010 Official statisticReport
20114,280$68,510BLS OEWS May 2011 Official statisticReport
20124,460$67,820BLS OEWS May 2012 Official statisticReport
20134,400$70,500BLS OEWS May 2013 Official statisticReport
20144,440$71,320BLS OEWS May 2014 Official statisticReport
20154,350$75,400BLS OEWS May 2015 Official statisticReport
20164,140$76,810BLS OEWS May 2016 Official statisticReport
20173,980$78,040BLS OEWS May 2017 Official statisticReport
20183,960$80,350BLS OEWS May 2018 Official statisticReport
20193,970$80,520BLS OEWS May 2019 Official statisticReport
20203,720$82,330BLS OEWS May 2020 Official statisticReport
20213,440$81,440BLS OEWS May 2021 Official statisticReport
20223,340$81,920BLS OEWS May 2022 Official statisticReport
20233,480$85,600BLS OEWS May 2023 Official statisticReport
20243,290$86,730BLS OEWS May 2024 Official statisticReport
20253,330$97,590BLS OEWS May 2025 Official statisticReport
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