ArcAtlas: Our Earth

ArcAtlas in the Classroom: Pattern Identification, Description, and Explanation

Michael N. DeMers; Jeffrey S. Vincent · 2008

This article examines how geographic information systems (GIS) and the ArcAtlas: Our Earth database can support inquiry-based geography education by developing students’ ability to identify, describe, explain, and predict spatial patterns. A central obstacle to integrating GIS into K–12 and introductory college courses is the limited availability of affordable, accessible, and thematically diverse spatial data, particularly for teachers without specialist GIS training or sufficient time to construct databases. ArcAtlas addresses this problem by providing more than forty digital thematic maps and one hundred satellite images covering human and physical topics, including climate, hydrology, geology, soils, vegetation, wildlife, population, economics, land use, and land cover. Although the database and some of its formats are dated, its continental-scale coverage and compatibility with GIS software make it a practical resource for educational activities. The article presents a lesson designed primarily for students in grades 10–12, community colleges, and introductory non-GIS university courses. Implemented in ArcGIS 9.x but adaptable to other platforms, the lesson emphasizes a simple graphical interface, advance teacher preparation, demonstrations, sequenced screenshots, and focused data selection so that students attend to geographic reasoning rather than software manipulation. The model exercise investigates historical and current lion distributions by overlaying range maps with vegetation and other physical or socioeconomic layers. Students classify vegetation zones, observe spatial correspondences, consider discrepancies caused by mapping scale, classification, and multiple interacting variables, and propose additional factors that may explain the contraction of lion habitat. They then produce maps and a final report explaining relationships among lion ranges, vegetation, soils, prey, land use, population, and other influences; predicting future distributions under continuing trends; and recommending strategies that balance wildlife conservation with human needs. The activity progresses from observation and description to analysis, explanation, prediction, and evaluation, and is explicitly connected to Bloom’s Taxonomy through stated learning objectives and an assessment rubric. It also addresses numerous National Geography Standards, especially the use of maps and geospatial technologies, analysis of spatial organization, understanding of ecosystems and human–environment interaction, and application of geography to interpret the past, assess the present, and plan for the future. Suggested extensions include intersection overlays to isolate areas of range loss, analysis of land-use and socioeconomic change, and comparison with prey-species distributions. Overall, the article argues that ArcAtlas can reduce the data and preparation barriers facing educators while enabling flexible, problem-based GIS lessons. Its educational value lies less in teaching advanced GIS operations than in using visual display and spatial overlay to cultivate geographic inquiry, critical thinking, independent hypothesis formation, and evidence-based environmental decision making.