Cartographic Scale Research Articles

Virtual reality in geoeducation: the case of the Lesvos Geopark

ABSTRACT The aim of this study is to investigate the contribution of cartographic results obtained from data acquired with Unmanned Aerial Vehicles to the management procedures of geoheritage monuments, specifically in geoeducation. 2D orthophotomaps and 3D textured meshes of a fossil site in the Lesvos Geopark, Greece, which has been monitored since 2018, were generated. The data recordings were collected using a UAV at different flight altitudes for three different cartographic scales. After acquiring UAV and Global Navigation Satellite Systems data, the resulting cartographic products were used to create educational material on geosites. This material was used to deliver lectures to students in various settings: (a) in situ at the Natural History Museum of the Lesvos Petrified Forest, (b) live in a traditional classroom, (c) remotely via e-class software, and (d) in a collaborative Virtual Reality environment. Feedback was provided by students through customized questionnaires, and their knowledge acquisition was assessed post-lecture with specially designed assignments. The final section of this work compares learning experiences and knowledge acquisition across these different environments. The results contribute to the debate on 2D and 3D cartography in geoeducation, quantifying the value of new materials in understanding spatial and geographic features and improving geoheritage management.

Multiscale Visualization of Surface Motion Point Measurements Associated with Persistent Scatterer Interferometry

Persistent scatterer interferometry (PSI) has been proven to be a robust method for studying complex and dynamic phenomena such as ground displacement over time. Proper visualization of PSI measurements is both crucial and challenging from a cartographic standpoint. This study focuses on the development of an interactive cartographic web map application, providing suitable visualization of PSI data, and exploring their geographic, cartographic, spatial, and temporal attributes. To this end, PSI datasets, generalized at different resolutions, are visualized in eight predefined cartographic scales. A multiscale generalization algorithm is proposed. The automation of this procedure, spurred by the development of a web application, offers users the flexibility to properly visualize PSI datasets according to the specific cartographic scale. Additionally, the web map application provides a toolset, offering state-of-the-art cartographic approaches for exploring PSI datasets. This toolset consists of exploration, measurement, filtering (based on the point’s spatial attributes), and exporting tools customized for PSI measurement. Furthermore, a graph tool, offering users the capability to interactively plot PSI time-series and investigate the evolution of ground deformation over time, has been developed and integrated into the web interface. This study reflects the need for appropriate visualization of PSI datasets at different cartographic scales. It is shown that each original PSI dataset possesses a suitable cartographic scale at which it should be visualized. Innovative cartographic approaches, such as web applications, can prove to be effective tools for users working in the domain of mapping and monitoring the dynamic behavior of surface motion.

What Do Children Draw When Asked to Draw a Map? Results of a Mental Map Experiment

When asked to draw a map reflecting on their experience, what do children draw? The authors offer possible answers through the eyes of children aged 6 to 14 who visited the Meadows Center for Water and the Environment on the campus of Texas State University; the 332 maps children were asked to draw after their visit are the focus. Results indicate that according to children, a map can be qualitatively understood as a graphic representation of the child’s experience that includes people and animals, places, and events, and natural and built environments. Children use both mimetic and abstract symbols that vary in shape, are often used repeatedly to create texture or patterns, and can vary in colour that often—but not always—abide by traditional colour denotations. Cartographic scales, legends, or north arrows are rarely used. The abundant use of written labels or descriptive words on their maps suggests that children understand maps as an expressive form that blends symbols and text. In efforts to contribute to the ultimate questioning of what makes a map a map, this study provides a strong empirical case for the what and how of children’s map-making processes concentrating on traditional cartographic conventions and elements.

A Self-Supervised Learning Approach for Extracting China Physical Urban Boundaries Based on Multi-Source Data

Physical urban boundaries (PUBs) are basic geographic information data for defining the spatial extent of urban landscapes with non-agricultural land and non-agricultural economic activities. Accurately mapping PUBs provides a spatiotemporal database for urban dynamic monitoring, territorial spatial planning, and ecological environment protection. However, traditional extraction methods often have problems, such as subjective parameter settings and inconsistent cartographic scales, making it difficult to identify PUBs objectively and accurately. To address these problems, we proposed a self-supervised learning approach for PUB extraction. First, we used nighttime light and OpenStreetMap road data to map the initial urban boundary for data preparation. Then, we designed a pretext task of self-supervised learning based on an unsupervised mutation detection algorithm to automatically mine supervised information in unlabeled data, which can avoid subjective human interference. Finally, a downstream task was designed as a supervised learning task in Google Earth Engine to classify urban and non-urban areas using impervious surface density and nighttime light data, which can solve the scale inconsistency problem. Based on the proposed method, we produced a 30 m resolution China PUB dataset containing six years (i.e., 1995, 2000, 2005, 2010, 2015, and 2020). Our PUBs show good agreement with existing products and accurately describe the spatial extent of urban areas, effectively distinguishing urban and non-urban areas. Moreover, we found that the gap between the national per capita GDP and the urban per capita GDP is gradually decreasing, but regional coordinated development and intensive development still need to be strengthened.

Architecturologie et projet urbain

Based on the precise description of a design operation, whose economic relevance is part of the reference space constituted by the current ecological context of architectural design, we distinguish the design space, made up of the operations taking place there, from the resulting architectural space. These operations being the result of architectural scales, a second conceptual distinction operates between a " scale" in the current sense which is a binary relationship of corresponding measurements between map and territory, and the relevance of said relationship, which defines an architectural cartographic scale, of a completely different conceptual nature, ternary in essence.

Carbon estimation in an integrated crop-livestock system with imaging sensors aboard unmanned aerial platforms

Biomass and carbon estimates in integrated crop–livestock (iLP) systems remain scarce. Recently, sensors aboard an unmanned aerial vehicle (UAV) have been used for such estimation and can represent an efficient and low-cost method for acquiring accurate remote-sensing data. This study aimed to estimate the relationship between vegetation indices (VIs) and carbon stock in an upland rice field intercropped with Brachiaria, an exotic grass species in the savanna ecosystem of Brazil (Cerrado biome), using multispectral aerial imaging with a high cartographic scale. The research was conducted in an experimental iLP system located at the Brazilian Agricultural Research Corporation (Embrapa Arroz e Feijão), Goiás State. During the data collection stage, flights were conducted with a fixed-wing UAV (eBee Plus RTK) on the same day or close to collecting biomass samples in the field. In the processing step, a correlation was performed between the normalized difference vegetation index (NDVI), simple ratio (SR), soil-adjusted vegetation index (SAVI), and modified photochemical reflectance index (MPRI) VIs and the biomass measured in the field. The results indicated that the vegetation index (VI) that used the near-infrared (NIR) band showed a stronger correlation with biomass than the VI that used only the visible band information. All VIs were significantly correlated with the estimated field biomass (P < 0.05) using Pearson's correlation. The regression models were able to predict the biomass and carbon stock in Phase 1 (3.93 Mg ha−1, 1.66 Mg ha−1, R2 = 0.748) and Phase 2 (7.53 Mg ha−1, 3.19 Mg ha−1, R2 = 0.816). From the best model selected for each phase, maps with the spatial and temporal distribution of the biomass of the iLP system were plotted, demonstrating one of the advantages of employing remote sensing techniques based on drones and multispectral imaging sensors.

VR Multiscale Geovisualization Based on UAS Multitemporal Data: The Case of Geological Monuments

Technological progress in Virtual Reality (VR) and Unmanned Aerial Systems (UASs) offers great advantages in the field of cartography and particularly in the geovisualization of spatial data. This paper investigates the correlation between UAS flight characteristics for data acquisition and the quality of the derived maps and 3D models of geological monuments for VR geovisualization in different scales and timeframes. In this study, we develop a methodology for mapping geoheritage monuments based on different cartographic scales. Each cartographic scale results in diverse orthophotomaps and 3D models. All orthophotomaps and 3D models provide an optimal geovisualization, combining UAS and VR technologies and thus contributing to the multitemporal 3D geovisualization of geological heritage on different cartographic scales. The study area selected was a fossilite ferrous site located in Lesvos Geopark, UNESCO. The study area contains a fossil site surrounding various findings. The three distinct scales that occur are based on the object depicted: (i) the fossilite ferrous site (1:120), (ii) the fossil root system (1:20), and (iii) individual fossils (≥1:10). The methodology followed in the present research consists of three main sections: (a) scale-variant UAS data acquisition, (b) data processing and results (2D–3D maps and models), and (c) 3D geovisualization to VR integration. Each different mapping scale determines the UAS data acquisition parameters (flight pattern, camera orientation and inclination, height of flight) and defines the resolution of the 3D models to be embedded in the VR environment. Due to the intense excavation of the study area, the location was spatiotemporally monitored on the cartographic scale of 1:120. For the continuous monitoring of the study area, four different UASs were also used. Each of them was programmed to fly and acquire images with a constant ground sampling distance (GSD). The data were processed by image-based 3D modeling and computer vision algorithms from which the 3D models and orthophotomaps were created and used in the VR environment. As a result, a VR application visualizing multitemporal data of geoheritage monuments across three cartographic scales was developed.

Scale issues for geoheritage 3D mapping: The case of Lesvos Geopark, Greece

A geopark can be composed of many individual geosites of various geographical scales, thus, categorization according to cartographic scale is crucial for their 3D mapping. The UNESCO Global Geopark of the island of Lesvos in the north-east Aegean, Greece, is a distinctive example of this type of geopark as it contains many unique geosites that vary in geographical scale. The geographical scale is interconnected with the cartographic scale in which the geosite is visualized. The desired cartographic scale is an essential user requirement within an unmanned aerial vehicle's (UAVs) 3D mapping project as the basis for the data acquisition strategy. This research investigates the scale issues in 3D mapping of geosites. Furthermore, it contributes to the incorporation of the geographic and cartographical scales in association with UAV flight parameters such as Ground Sample Distance (GSD), altitude, gimbal pitch, orientation, and front and side overlapping. A total of 132 geosites located in Lesvos Geopark are being studied to determine the flight parameters of three different UAVs and their camera characteristics. The methodology followed to collect very high-resolution images suitable for 3D mapping consists of five main stages: i) determining the geographical scale of each geosite, ii) defining the cartographic scale of all geosites, iii) calculation of the GSD based on cartographic scale, iv) calculation of UAV flight altitude and flight characteristics, and v) classification of geosites based on the flight characteristics for their 3D mapping. Five geographic (G1: < 0.1 ha, G2: 0.1–1 ha, G3: 1–10 ha, G4: 10–100 ha, G5: >100 ha) and five cartographic (C1: > 1:50, C2: 1:50–1:100, C3: 1:100–1:250, C4: 1:250–1:500, C5: < 1:500) categories were defined based on the geosites' size and extent. The combination of the two scales determines the most efficient flight characteristics and optimally acquires very high-resolution images required for the 3D mapping of the selected geosites. Finally, the categorization and characteristics of flights for data collection for high-resolution 3D mapping are collected and presented in a web application. The web application is addressed to the management board of Lesvos Geopark and supports the decision-making processes on mapping geosites using UAVs.

Digital soil mapping outputs on soil classification and sugarcane production in Brazil

Soil maps at regional and farm levels are vital for the best management agricultural practices (BMAP). The soil is the substrate for plant growth and essential to ensure food security. In this context, soil maps require a detailed cartographic scale for BMAP. This study (i) investigated the use of digital soil mapping (DSM) products, such as soil chemical and physical attributes, indices, mineralogy, and properties to extrapolate late soil survey maps at 1:20,000 scale; (ii) created the digital yield environment for sugarcane based on the DSM products; and (iii) evaluated qualitatively the predict soil maps and relationship with previous studies and the predicted yield environment. The region of interest covers eight municipalities and almost 2598 km2 in São Paulo State, Brazil. The soil survey at farm level conducted covered almost 86.52 km2, ∼3.33% of the total area (96.67% of the unmapped area). We created a point grid (centroid) with the same spatial resolution (30 m) of the rasters used as covariates for soil mapping unit (SMU) predictions. This grid intended to retrieve the representative soil mapping unit of each geometric polygon. It was retrieved 117,413 points representing 27 SMU of seven soil orders at a first categorical level, according to the Brazilian Classification System, and seven yield environment for sugarcane production. SMU predictions and their respective soil orders were performed using the random forest machine learning regression method. The level of association between SMU and yield environments was 0.34 (α = 0.01) by the Cramer's V coefficient with a very strong relationship. Our approach could provide the first digital yield environment for sugarcane based on the DSM products. Furthermore, a qualitative evaluation of our framework was substantiated with previous research in the same study site. This framework could be replicated and fulfil the need for DSM at regional and farm levels for policy-makers and farmers.

Scale-Variant Flight Planning for the Creation of 3D Geovisualization and Augmented Reality Maps of Geosites: The Case of Voulgaris Gorge, Lesvos, Greece

The purpose of this paper was to study the influence of cartographic scale and flight design on data acquisition using unmanned aerial systems (UASs) to create augmented reality 3D geovisualization of geosites. The relationship between geographical and cartographic scales, the spatial resolution of UAS-acquired images, along with their relationship with the produced 3D models of geosites, were investigated. Additionally, the lighting of the produced 3D models was examined as a key visual variable in the 3D space. Furthermore, the adaptation of the 360° panoramas as environmental lighting parameters was considered. The geosite selected as a case study was the gorge of the river Voulgaris in the western part of the island of Lesvos, which is located in the northeastern part of the Aegean Sea in Greece. The methodology applied consisted of four pillars: (i) scale-variant flight planning, (ii) data acquisition, (iii) data processing, (iv) AR, 3D geovisualization. Based on the geographic and cartographic scales, the flight design calculates the most appropriate flight parameters (height, speed, and image overlaps) to achieve the desired spatial resolution (3 cm) capable of illustrating all the scale-variant details of the geosite when mapped in 3D. High-resolution oblique aerial images and 360° panoramic aerial images were acquired using scale-variant flight plans. The data were processed using image processing algorithms to produce 3D models and create mosaic panoramas. The 3D geovisualization of the geosite selected was created using the textured 3D model produced from the aerial images. The panoramic images were converted to high-dynamic-range image (HDRI) panoramas and used as a background to the 3D model. The geovisualization was transferred and displayed in the virtual space where the panoramas were used as a light source, thus enlightening the model. Data acquisition and flight planning were crucial scale-variant steps in the 3D geovisualization. These two processes comprised the most important factors in 3D geovisualization creation embedded in the virtual space as they designated the geometry of the 3D model. The use of panoramas as the illumination parameter of an outdoor 3D scene of a geosite contributed significantly to its photorealistic performance into the 3D augmented reality and virtual space.

Unified Scale Theorem: A Mathematical Formulation of Scale in the Frame of Earth Observation Image Classification

In this research, the geographic, observational, functional, and cartographic scale is unified into a single mathematical formulation for the purposes of earth observation image classification. Fractal analysis is used to define functional scales, which then are linked to the other concepts of scale using common equations and conditions. The proposed formulation is called Unified Scale Theorem (UST), and was assessed with Sentinel-2 image covering a variety of land uses from the broad area of Thessaloniki, Greece. Provided as an interactive excel spreadsheet, UST promotes objectivity, rapidity, and accuracy, thus facilitating optimal scale selection for image classification purposes.

INTEGRATION BETWEEN BUILDING INFORMATION MODELING AND GEOGRAPHIC INFORMATION SYSTEM FOR HISTORIC BUILDINGS AND SITES: HISTORIC-BIM-GIS

Abstract. The paper presents a novel prototype of integrated Historic BIM-GIS able to deal with multi-source, -scale, and -temporal information. It combines elements from the cartographic scale to a more detailed level of detail towards the building. It can be defined as a 3D virtual environment with an associate (geo)database able to encapsulate heterogeneous data not limited to products derived from the geometric survey, notwithstanding digital recording and its deliverables play a fundamental role. The system also provides a good interoperability level so that BIM and GIS software can exchange information, avoiding the implementation of functions and tools already available in other software packages. The example proposed in this contribution is related to the system of fortified structures around the city of Sondrio. Here, a single 3D environment was developed to encapsulate information from the cartographic level in an area of more than 135 km2 to the scale of 1:1 for specific architectural elements.

A comparison between three legacy soil maps of Zambia at national scale: The spatial patterns of legend units and their relation to soil properties

We examined three soil maps of Zambia, two published at scales of 1:1 million – the Exploratory Soil Map of Zambia (ESMZ) and the Vegetation–Soil Map produced by Trapnell and colleagues in 1947 – and one at 1:3 million, the Soil Atlas of Africa (SAA). We estimated components of variance for measurements of clay, sand and organic carbon content and bulk density of the soil across the country using models which included different mean values for soil map units as random effects. For all but organic carbon content there was significant variation accounted for by differences between legend units for two of the maps, ESMZ with legend units based on the FAO-Unesco and SAA with legend units based on the World Reference Base respectively. This was despite their small cartographic scale. For the Vegetation–Soil Map, we examined differences between broad soil physiographic units. These did not account for significant variation in the soil properties. There were clear similarities between the soil physiographic units of the Soil–Vegetation Map and broader physiographic units into which the legend units of the ESMZ are grouped. The spatial pattern of soil units of the SAA was the most spatially heterogeneous, as measured by the sum of indicator variograms, despite being at the smallest published scale. It was apparent that some of the soil variation within the largest physiographic unit of the Soil–Vegetation Map, the Plateau Soils, as expressed by the map units of the SAA was significantly associated with the different vegetation units mapped in 1947. These studies show how quantitative assessment of legacy soil information may help us understand its potential and limitations.

As escalas da Geografia: Pontes entre os conceitos de escala cartográfica e escala geográfica

Na Geografia, o entendimento e a utilização dos conceitos de escala cartográfica e escala geográfica auxiliam no delineamento da investigação científica. Partindo de textos clássicos que tratam do assunto, objetiva-se verificar a pertinência das críticas à escala cartográfica e sua contraposição a uma concepção de escala “verdadeiramente” geográfica, além de apresentar um aporte a essa problemática, com a definição das diferenças, semelhanças, limites e possibilidades de cada conceito. Assim, as etapas desta pesquisa consistiram em pesquisa bibliográfica exploratória de artigos e livros, em bases digitais de livre acesso na Internet, ancorada na técnica de investigação retrospectiva, a partir de uma obra de referência (CASTRO, 1995). Por meio da análise, sobressai-se a ideia de que ainda há uma indefinição conceitual quanto à ideia do que seja uma escala geográfica, daí advindo a adoção ou, por vezes, a confusão com sua congênere cartográfica. Também se destaca a incompreensão do alcance da cartografia como linguagem, tomando-se o mapa apenas pelos limites impostos por sua escala, e menosprezando suas reais possibilidades de contribuição à análise geográfica.

USO DA GEOTECNOLOGIA PARA O MAPEAMENTO DA CAFEICULTURA NO CAPARAÓ CAPIXABA

Em virtude da importância no papel socioeconômico da cultura cafeeira para a região, o estudo teve como objetivo mapear a cafeicultura do Território do Caparaó Capixaba e avaliar a dinâmica de ocupação do cultivo de café no período de 2007 a 2015. Foram utilizadas fotos do ortofotomosaico do estado do Espírito Santo, recorte para o Território, com resolução espacial de 1 m para 2007 e 0,25 m para 2015, na escala cartográfica de 1:35.000. A fotointerpretação foi realizada aplicativo computacional na escala de 1:2.000, com checagem do erro pelo Índice Kappa. A fim de posicionar a área de cultivo ao tipo de café entre arábica e conilon, foi realizado o zoneamento de aptidão, restrição e inaptidão Agroclimática, e posteriormente envolvendo a altitude, conforme critérios adotados pelo órgão estadual. De pose do zoneamento, foi interpolada a fotointerpretação da área de cultivo de 2007 e 2015, possibilitando sua comparação. Detectou-se que a área total de ocupação do foi de 16,37% (2007), 15,82% (2015), sendo 8,78% de área comum. Em relação a área de plantio total de conilon e arábica, verificou-se redução no cultivo de ambas as espécies de 14,59 e 6,72 km², respectivamente. A geotecnologia foi de grande relevância para o presente trabalho, na atividade de planejamento e administração do agronegócio.

Cartographic Scale in Immersive Virtual Environments

Scale has been a defining criterion of mapmaking for centuries. However, this criterion is fundamentally questioned by highly immersive virtual reality (VR) systems able to represent geographic environments at a high level of detail and, thus, providing the user with a feeling of being present in VR space. In this paper, we will use the concept of scale as a vehicle for discussing some of the main differences between immersive VR and non-immersive geovisualization products. Based on a short review of diverging meanings of scale we will propose possible approaches to the issue of both spatial and temporal scale in immersive VR. Our considerations shall encourage a more detailed treatment of the specific characteristics of immersive geovisualization to facilitate deeper conceptual integration of immersive and non-immersive visualization in the realm of cartography.

Digital mapping of soil parent material in a heterogeneous tropical area

Parent material is one of the five factors in soil formation. Studies on parent material allow interpreting soil genesis processes and improve our knowledge of specific soil attributes. However, soil parent material maps at detailed cartographic scale (finer than 1:100,000) are rare in tropical areas and it is usually inferred from poorly detailed geological data, which generally group different lithologies into single units. Thus, we propose a methodology to map soil parent material based on remote sensing and machine learning in a geologically very complex area. The study site covers 1378 km2 in São Paulo State, Brazil. Prediction models used data from 280 geological observation points, a digital elevation model (spatial resolution of 5 m, upscale to 30 m) and multitemporal Landsat images in a range of 30 years. We evaluated six classification algorithms, namely random forest, decision tree, support vector machine, multinomial logistic regression, K-means (unsupervised classification), and object-based image analysis with maximum likelihood classification. Environmental covariates were grouped to create different scenarios combining terrain derivatives, hydrologic covariates, topsoil spectral reflectance, and spatial coordinates. A bare soil image, elaborated using 30 years of Landsat data, was evaluated as a covariate to predict soil parent material. Predictions were validated using three different strategies: cross-validation, separate validation dataset (20%), and comparison with legacy geological maps (information from two areas with geological maps at fine scale). We also assessed the correspondence between the map of predicted soil parent material and data of soil particle size from 571 soil sampling points. Random forest algorithm presented the best validation performance, whereas the group of terrain derivatives and hydrologic covariates explained most of model variation. The produced parent material map was coherent with the spatial distribution of soil particle size across the study area.

Geovisualization of the Excavation Process in the Lesvos Petrified Forest, Greece Using Augmented Reality

Augmented reality (AR), in conjunction with 3D geovisualization methods, can provide significant support in monitoring geoconservation activities in protected geosites, such as the excavation process in fossil sites. The excavation process requires a monitoring methodology that will provide a complete and accurate overview of the fossils, their dimensions, and location within the different pyroclastic horizons, and the progress of the excavation works. The main purpose of this paper is the development of a user-friendly augmented map application, specifically designed for tracking the position of petrified tree trunks, providing information for their geometric features, and mapping the spatiotemporal changes occurring in the surrounding space. It also aims to probe whether the rapid acquisition of a 4K video can generate cartographic derivatives of petrified findings during a geosite excavation. A database accumulated 2D and 3D cartographic information, while the geovisualization environment displayed the surface alterations, at two scales: a) 1:500 (excavation area) and b) 1:50 (trench level). Unmanned aerial systems (UASs), used for data acquisition in three excavation periods, consisted of two flights at two different altitudes: one to record changes throughout the study area and the other to provide information on trunks at trench level, via a high-resolution (4K) video. Image-based 3D modeling followed, in which image georeferencing was conducted with ground control points (GCPs). Finally, 2D and 3D geovisualizations were created to depict the excavation changes through time. The cartographic products generated at two cartographic scales depicted the spatiotemporal changes of the excavation.

Towards knowledge-based geovisualisation using Semantic Web technologies: a knowledge representation approach coupling ontologies and rules

ABSTRACT Geovisualisation is a knowledge-intensive art in which both providers and users need to possess a wide range of knowledge. Current syntactic approaches to presenting visualisation information lack semantics on the one hand, and on the other hand are too bespoke. Such limitations impede the transfer, interpretation, and reuse of the geovisualisation knowledge. In this paper, we propose a knowledge-based approach to formally represent geovisualisation knowledge in a semantically-enriched and machine-readable manner using Semantic Web technologies. Specifically, we represent knowledge regarding cartographic scale, data portrayal and geometry source, which are three key aspects of geovisualisation in the contemporary web mapping era, coupling ontologies and semantic rules. The knowledge base enables inference for deriving the corresponding geometries and portrayals for visualisation under different conditions. A prototype system is developed in which geospatial linked data are used as underlying data, and some geovisualisation knowledge is formalised into a knowledge base to visualise the data and provide rich semantics to users. The proposed approach can partially form the foundation for the vision of web of knowledge for geovisualisation.

A Virtual Globe Using a Discrete Global Grid System to Illustrate the Modifiable Areal Unit Problem

In the same way that discrete global grid systems (DGGS) are used to index data on the spherical Earth, they can aggregate point data, with their spherical polygons serving as bins. DGGS are particularly useful at multiple map scales because they are spatially hierarchical and exist on the sphere or ellipsoid, allowing large or small scale binning without projection distortion. We use DGGS in a free and open-source pedagogical tool for teaching students about the modifiable areal unit problem (MAUP). Our software application uses Dutton’s quaternary triangular mesh (QTM) to bin global data points geodesically with counts or measures of any theme at multiple levels. Users can interactively select the level to which the data are binned by the QTM, as well as translate the whole tessellation east or west so that points fall into and out of different bins. These two functions illustrate the scaling and zoning aspects of the MAUP with dynamically-drawn choropleths on the surface of a virtual globe that the user can zoom and rotate, allowing visualization at virtually any cartographic scale. Users may also select various quantile classifications to further explore issues in visualizing aggregate data. In addition to presenting this new tool, we highlight the importance, especially at smaller scales, of using geodesic point-in-polygon intersection detection, rather than the projected 2D methods typically used by geographic information systems.