The uptake of machine learning (ML) algorithms in digital soil map** (DSM) is
transforming the way soil scientists produce their maps. Within the past two decades, soil …

Visual analytics systems combine machine learning or other analytic techniques with
interactive data visualization to promote sensemaking and analytical reasoning. It is through …

Learning to Think Spatially examines how spatial thinking might be incorporated into
existing standards-based instruction across the school curriculum. Spatial thinking must be …

The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and
Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data …

Geospatial big data present a new set of challenges and opportunities for cartographic
researchers in technical, methodological and artistic realms. New computational and …

We have access to an unprecedented amount of fine‐grained data on cities, transportation,
economies, and societies, much of these data referenced in geo‐space and time. There is a …

The possibility of digital interactivity requires us to reenvision the map reader as the map
user, and to address the perceptual, cognitive, cultural, and practical considerations that …

The fundamental goal of the GeoVISTA Studio project is to improve geoscientific analysis by
providing an environment that operationally integrates a wide range of analysis activities …

In recent years we have seen information visualization technology move from an advanced
research topic to mainstream adoption in both commercial and personal use. This move is in …

This article introduces a special issue of the International Journal of Cartography that
envisions the future of cartographic research. Following a process of collaborative ideation …