Steven Manson

University of Minnesota Twin Cities | UMN · Department of Geography, Environment and Society

Transformation of the Earth's social and ecological systems is occurring at a rate and magnitude unparalleled in human experience. Data science is a revolutionary new way to understand human-environment relationships at the heart of pressing challenges like climate change and sustainable development. However, data science faces serious shortcomings...

Data science holds extraordinary promise for better policymaking for humans and the environment while at the same time posing myriad harms. Data science helps draft solutions to many human-environment problems, including climate change, environmental degradation, and sustainable development. It also has many troubling aspects. It is reshaping many...

Transformation of the Earth's social and ecological systems is occurring at a rate and magnitude unparalleled in human experience. Data science is a revolutionary new way to understand human-environment relationships at the heart of pressing challenges like climate change and sustainable development. However, data science faces serious shortcomings...

Many of the challenges with human-environment data are exacerbated by critical methodological shortcomings. Many of the core tasks of data science, such as data manipulation, machine learning, or artificial intelligence, are made more difficult by the complex nature of human-environment data. Data science and cognate fields are the loci of exciting...

Data science plays an increasingly prominent role in examining and addressing human–environment dynamics. The growing role of data-intensive inquiry is apparent to many researchers, policymakers, and others. At the same time, however, there is mounting awareness of the interplay between the perils and promise of big data for human-environment syste...

Transformation of the Earth’s social and environmental systems is happening at an incredible pace. The global population has more than doubled over the last five decades, while food and water consumption has tripled and fossil-fuel use quadrupled. Attendant benefits such as longer lifespans and economic growth are increasingly joined by correspondi...

Data science proponents sometimes contend that their approach augurs the “end of theory” because we are on the threshold of a new scientific paradigm. Big data is seen as a powerful “black box” into which users shovel large and messy data collections and, in return, get deep insights into any domain people care to investigate. The essence of black...

For all the potential of big data and data science, scholars wanting to untangle human–environment interactions face many gaps in big data. Human-environment data handily exemplify many of the characteristics of big data. They have high volumes, orders of magnitudes more extensive than commonly used in most research fields, resulting from repeated...

Transformation of the Earth's social and ecological systems is occurring at a rate and magnitude unparalleled in human experience. Data science is a revolutionary new way to understand human-environment relationships at the heart of pressing challenges like climate change and sustainable development. However, data science faces serious shortcomings...

This article addresses the challenge of sharing finer scale protected health information (PHI) while maintaining patient privacy by using regionalization to create higher resolution Health Insurance Portability and Accountability Act (HIPAA)-compliant geographical aggregations. We compare four regionalization approaches in terms of their fitness fo...

UNSTRUCTURED The Health Insurance Portability and Accountability Act (HIPAA) was an important milestone in protecting the privacy of patient data, but the HIPAA provisions specific to geographic data remain so vague as to hinder the ways in which epidemiologists and geographers use and share spatial health data. The literature on spatial health and...

The Health Insurance Portability and Accountability Act (HIPAA) was an important milestone in protecting the privacy of patient data; however, the HIPAA provisions specific to geographic data remain vague and hinder the ways in which epidemiologists and geographers use and share spatial health data. The literature on spatial health and select legal...

The spatial university foregrounds the spatiotemporal nature of people, places, and processes in meeting its core missions of scholarship, teaching, and service. The university works across scales by advancing macro efforts that capture the imagination of people on and off campus, developing meso themes that translate macro ideas in specific ways,...

U-Spatial is the spatial science infrastructure that is integral to making the University of Minnesota a spatial university. At its core is a team of geospatial professionals who advance the mission of the modern land grant university and operate a new kind of infrastructure that encompasses people, places, and tools. It took over a decade to secur...

The spatial university aims to help students learn to think spatially. This chapter outlines the many different ways in which spatial thinking presents throughout the University of Minnesota, beginning with an overview of the history of spatial science on campus and a discussion of how the curriculum has evolved over time. A description of the curr...

We describe the use of network modeling to capture the shifting spatiotemporal nature of the COVID-19 pandemic. The most common approach to tracking COVID-19 cases over time and space is to examine a series of maps that provide snapshots of the pandemic. A series of snapshots can convey the spatial nature of cases but often rely on subjective inter...

Agent based modeling (ABM) is a standard tool that is useful across many disciplines. Despite widespread and mounting interest in ABM, even broader adoption has been hindered by a set of methodological challenges that run from issues around basic tools to the need for a more complete conceptual foundation for the approach. After several decades of...

Generating replicable and empirically valid models of human decision-making is crucial for the scientific accuracy and reproducibility of agent-based models. A two-fold challenge in developing models of decision-making is a lack of high resolution and high quality behavioral data and the need for more transparent means of translating these data int...

Background Group-randomized trials of communities often rely on the convenience of pre-existing administrative divisions, such as school district boundaries or census entities, to divide the study area into intervention and control sites. However, these boundaries may include substantial heterogeneity between regions, introducing unmeasured confoun...

Big Geo Data promises tremendous benefits to the GIS Science community in particular and the broader scientific community in general, but has been primarily of use to the relatively small body of GIScientists who possess the specialized knowledge and methods necessary for working with this class of data. Much of the greater scientific community is...

There is much interest in using big data for research on rapid social and environmental change. For all the excitement about big data, however, there are “deserts in the deluge” of these data because there is surprisingly little detailed information about human–environment systems for much of the globe, especially for before the year 2000 and for m...

Fine resolution spatial variability in pneumonia hospitalization may identify correlates with socioeconomic, demographic and environmental factors. We performed a retrospective study within the Fairview Health System network of Minnesota. Patients 2 months of age and older hospitalized with pneumonia between 2011 and 2015 were geocoded to their cen...

Big geospatial data is an emerging sub-area of geographic information science, big data, and cyberinfrastructure. Big geospatial data poses two unique challenges. First, raster and vector data structures and analyses have developed on largely separate paths for the last 20 years. This is creating an impediment to geospatial researchers seeking to u...

Big geospatial data have unique challenges not associated with the greater big data community, namely, that raster and vector analytical approaches have evolved along two separate paths. Terra Populus is a next-generation spatial database repository that focuses on the integration of heterogeneous big data. When accessing Terra Populus through a we...

We describe a strategy for regionalizing subnational administrative units in conjunction with harmonizing changes in unit boundaries over time that can be applied to provide small-area geographic identifiers for census microdata. The availability of small-area identifiers blends the flexibility of individual microdata with the spatial specificity o...

Terra Populus, or TerraPop, is a cyberinfrastructure project that integrates, preserves, and disseminates massive data collections describing characteristics of the human population and environment over the last six decades. TerraPop has made a number of GIScience advances in the handling of big spatial data to make information interoperable betwee...

Remote sensing and geographic information systems (GIS) analysis involves the use of technology to gather, manipulate, and analyze spatial data to understand a range of phenomena. Remote sensing entails obtaining information about the Earth's surface by examining data acquired by a device, which is at a distance from the surface, most often satelli...

Intraurban migration—residential movement within a metropolitan area—defines the nature of urbanization. Housing location decision making is a complex process driven by the interactions between the housing market and home searchers. Researchers have paid much attention to the environmental, socioeconomic, cultural, and policy features of housing ma...

Recent years have seen an increasing amount of work by physicists on topics outside their traditional research domain, including geography. We explore the scope of this development, place it in a historical context dating back at least to statistical physics in the nineteenth century and trace the origins of more recent developments to the roots of...

Rotational grazing (RG) is a livestock management practice that moves grazing cattle among small temporary pastures called paddocks. In dairy farming, RG has potential to improve soil and water conservation by situating well-managed perennial vegetation on erosion-prone parts of farm landscapes. Recently, geospatial technologies have enabled precis...

The Terra Populus project (TerraPop) addresses a variety of data management, curation, and preservation challenges with respect to spatiotemporal population and environmental data. In this article, we describe our approaches to these challenges, with a particular focus on geospatial data workflows and associated provenance metadata. The goal of Ter...

In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very l...

Rotational grazing (RG) has attracted much attention as a cornerstone of multifunctional agriculture (MFA) in animal systems, potentially capable of producing a range of goods and services of value to diverse stakeholders in agricultural landscapes and rural communities, as well as broader societal benefits. Despite these benefits, global adoption...

Multifunctional agricultural systems seek to expand upon production-based benefits to enhance family wellbeing and animal health, reduce inputs, and improve environmental services such as biodiversity and water quality. However, in many countries a landscape-level conversion is uneven at best and stalled at worst. This is particularly true across t...

Web mapping involves publishing and using maps via the Internet, and can range from presenting static maps to offering dynamic data querying and spatial analysis. Web mapping is seen as a promising way to support development of spatial thinking in the classroom but there are unanswered questions about how this promise plays out in reality. This art...

A multitemporal method to map snow cover in mountainous terrain is proposed to guide Landsat climate data record (CDR) development. The Landsat image archive including MSS, TM, and ETM + imagery was used to construct a prototype Landsat snow cover CDR for the interior northwestern United States. Landsat snow cover CDRs are designed to capture snow-...

The environmental sciences increasingly need to understand the ecological effects of urbanization. This is especially true for the urban forest, a major component of the urban environment that is relied on to provide ecosystem services such as air pollution removal and storm water interception. The urbanization gradient is a popular organizing conc...

The growth of web-based mapping is transforming geovisualization. Use of web mapping has become ubiquitous throughout much of the world and has sparked greater public interest in GIS and mapping. Despite the rapid growth of web mapping, there has been relatively little study of the design and usability of web maps. Moreover, the design and function...

Complexity theory provides a common language and rubric for applying agent-based processes to a range of complex systems. Agent-based modeling in turn advances complexity science by actuating many complex system characteristics, such as self-organization, nonlinearity, sensitivity, and resilience. There are many points of contact between complexity...

The neighborhood is the central analytical entry point into a wide range of research topics, but it is an open question as to what defines a neighborhood. Most quantitative neighborhood classification methods are based on the assumption that neighborhoods are composed of places with similar spatial and socioeconomic characteristics. While this assu...

Dynamic relationships among climate, disturbance, and vegetation affect the spatial configuration and composition of ecological communities. Paleoecological records indicate the importance of such relationships in Minnesota’s Big Woods (BW) region, where isolated hardwood forest populations expanded to regional dominance after AD 1250. We used LAND...

There is mounting interest among scientists regarding the use of scientometric social network analysis, or quantitative analysis of the evolution of science as defined by individual researchers and the networks they form. Given that geographers have seldom used this approach compared to researchers in other fields, its implications for research and...

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Biomass carbon content on land converted to urban or cropland use between 2000 and 2015. (0.21 MB JPG)

Areas where significant irrigation use is assumed if the grid cell is in cropland use. (0.37 MB JPG)

Cropland suitability map for the country scenario. Scores have been normalized within a country so cross country comparisons are not appropriate. (0.45 MB JPG)

Estimates of equation (10) in Text S1. (0.04 MB XLS)

The average yield of each crop or crop group in 2000 by country (Mg ha−1). (0.07 MB XLS)

Calories per crop or crop type. (0.05 MB XLS)

The relative mix of crops or crop groups produced in each country in 2000: q = year 2000 crop mix. (0.07 MB XLS)

Alternative 2015 crop mix by country: q = 2 (“Low” 2015 harvested hectare mix). (0.07 MB XLS)

Alternative 2015 crop mix by country: q = 4 (“Mean” 2015 harvested hectare mix). (0.07 MB XLS)

Irrigated and rainfed cropland grid cell area in 2000 and 2015 under both scenarios. (0.09 MB XLS)

Crop grid cell area growth rate for each region under the regional scenario. (0.03 MB XLS)

Expected growth in yields by crop or crop group and country. (0.06 MB XLS)

Alternative 2015 crop mix by country: q = projected 2015 crop mix. (0.07 MB XLS)

Average biomass carbon storage by forest type by country in 2000 (Mg of carbon equivalent ha−1). (0.05 MB XLS)

Avoided emissions analysis. (0.03 MB XLS)

Urban suitability map. (0.24 MB JPG)

Cropland suitability map for the regional scenario. Scores have been normalized within a region so cross region comparisons are not appropriate. (0.49 MB JPG)

Urban grid cell area in 2000 and 2015 under both scenarios. (0.07 MB XLS)

Change in cropland grid cell area under the country scenario. (0.07 MB XLS)

Observed irrigation intensity in grid cells assigned irrigated cereal yield by country. (0.06 MB XLS)

The fraction of cropland grid cell area in each cropping zones under both scenarios. (0.07 MB XLS)

Alternative 2015 crop mix by country: q = 3 (“Mean” 2015 Harvested Hectare Mix). (0.07 MB XLS)

Net loss of biomass carbon between 2000 and 2015 due to LULC change. Results are summarized at the country-level and presented in Mg ha−1 units. (0.36 MB JPG)

Regions and their member countries in the regional scenario. (0.03 MB XLS)

Change in cropland grid cell area under the regional scenario. (0.04 MB XLS)

The relative difference in cropland suitability in 2015 versus 2000 by country. (0.06 MB XLS)

Average water yield on rainfed cropland in 2000 and under both scenarios by country. (0.05 MB XLS)

As the global human population grows and its consumption patterns change, additional land will be needed for living space and agricultural production. A critical question facing global society is how to meet growing human demands for living space, food, fuel, and other materials while sustaining ecosystem services and biodiversity [1]. We spatially...

Spatial distance is a critical component of theories across the social, natural, and information sciences, but too often the methods and metrics used to describe spatial distance are implicit or underspecified. How distance is measured may influence model results in unanticipated ways. We examined the differences among distances calculated in three...

Various approaches are used to identify West Nile virus (WNV) exposure areas, including unusual sightings of infected dead birds, mosquito pools or human cases both prospectively and retrospectively. A significant and largely unmet need in WNV research is to incorporate the temporal characterization of virus spread and locational information of the...

Parcel data, or information about individual plots of land, may be used to examine a broad range of social and environmental issues. While analog parcel information has long been available, the move towards digital georeferenced data offers a more readily available means of using detailed structural and land use information. Parcels map onto useful...

The high spatial resolution of QuickBird satellite images makes it possible to show spatial variability at fine details. However, the effect of topography-induced illumination variations become more evident, even in moderately sloped areas. Based on a high resolution (1 m) digital elevation model generated with high-frequency real-time kinematic gl...

Scale pervades interdisciplinary research on human–environment systems that exhibit hallmarks of complexity such as path dependence, nonlinearity, and surprise. Although scale concepts are woven through the data, methodology, and theory of human–environment research, the question remains: does scale exist? More broadly, can a single definition of s...

Cross-site comparisons of case studies have been identified as an important priority by the land-use science community. From an empirical perspective, such comparisons potentially allow generalizations that may contribute to production of global-scale land-use and land-cover change projections. From a theoretical perspective, such comparisons can i...

For the complex systems modeller, uncertainty is ever-present. While uncertainty cannot be eliminated, we suggest that formally incorporating an assessment of uncertainty into our models can provide great benefits. Sources of uncertainty arise from the model itself, theoretical flaws, design flaws, and logical errors. Management of uncertainty and...

In this paper, we present a hybrid approach, robust principal component geographically weighted regression (RPCGWR), in examining urbanization as a function of both extant urban land use and the effect of social and environmental factors in the Twin Cities Metropolitan Area (TCMA) of Minnesota. We used remotely sensed data to treat urbanization via...