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Examining the similarity of event environments or surroundings—more precisely, settings—provides additional insight in analyzing event sequences, as it provides information about the context and potential common factors that may have influenced them. This article proposes a new similarity measure for event setting sequences, which involve the space and time in which events occur. While similarity measures for spatiotemporal event sequences have been studied, the settings and setting sequences have not yet been studied. While modeling event setting sequences, we consider spatial and temporal scales to define the bounds of the setting and incorporate dynamic variables alongside static variables. Using a matrix-based representation and an extended Jaccard index, we developed new similarity measures that allow for the use of all variable data types. We successfully used these similarity measures coupled with other multivariate statistical analysis approaches in a case study involving setting sequences and pollution event sequences associated with the same monitoring stations, which validate the hypothesis that more similar spatial-temporal settings or setting sequences may generate more similar events or event sequences. In conclusion, the developed similarity measures have wide application beyond the case study to other disciplinary contexts and geographical settings. They offer researchers a powerful tool for understanding different factors and their dynamics corresponding to occurrences of spatiotemporal event sequences.

Recent literature recognises the importance of situating social networks in spatial contexts to better understand how space, place, and social networks interact and are co‐constituted. Despite this call, the mainstream literature in social network analysis pays relatively little attention to spatial dimensions of social networks and remains largely disconnected from the vast body of research on spatial networks in geography and cognate fields. This thematic issue is one step towards advancing this research agenda by examining how such an approach relates to issues of social inclusion and social participation. It includes a selection of studies that focus on the relation between space and social networks across a wide variety of research fields and contexts. Contributions use original, often mixed‐method approaches and multiple perspectives for capturing the role of space and people’s experience of place in network formation through physical, cultural, and geographical dimensions. We conclude this editorial by briefly suggesting areas for future research.

Spatial context effects are a topic in many scientific disciplines. This paper examines which conceptual steps are necessary for determining the extension, or the appropriate scale, of relevant spatial environments when contexts can be analytically disaggregated into context elements. Adequate models of scale need to specify not only the distance-dependent relevance of context elements but also their distribution and an adequate combination. In this way, it becomes possible to understand why non-monotonic patterns in scale-related context effects have been repeatedly found in spite of common assumptions of distance decay in relevance. In many cases, a distance-related maximum of (aggregate) context relevance can be expected, so that there is an “optimal” range for the measurement of context effects. It is also important to distinguish between applications in two- and three-dimensional space. This general model helps to specify the steps necessary for the determination of spatial context patterns and to identify unrealistic assumptions.

The mobilization of resources is an essential challenge for entrepreneurs. Existing research suggests that access to standard and high-quality resources is an important condition for entrepreneurial success, yet such resources are often out of reach for entrepreneurs. In this study, we explore entrepreneurial resource mobilization in resource-constrained peripheral locations. We identify three activities together constituting an underlying logic of spatial bricolage, defined as making do with the resources at hand in the immediate spatial context. Further, we suggest that the likelihood and prevalence of this logic of action is both situational and dispositional, as individual and contextual factors combine to generate important differences in the resource mobilization activities of the entrepreneurs. Our study contributes to a contextualized understanding of entrepreneurship by showing how spatial bricolage as a distinct logic can help entrepreneurs overcome resource constraints, and how the spatial context incorporates an important dimension of what constitutes ‘at hand’ in entrepreneurial bricolage.

The colors that people see depend not only on the surface properties of objects but also on how these properties interact with light as well as on how light reflected from objects interacts with an individual’s visual system. Because individual visual systems vary, the same visual stimulus may elicit different perceptions from different individuals. #thedress phenomenon drove home this point: different individuals viewed the same image and reported it to be widely different colors: blue and black versus white and gold. This phenomenon inspired a collection of demonstrations presented at the Vision Sciences Society 2015 Meeting which showed how spatial and temporal manipulations of light spectra affect people’s perceptions of material colors and illustrated the variability in individual color perception. The demonstrations also explored the effects of temporal alterations in metameric lights, including Maxwell’s Spot, an entoptic phenomenon. Crucially, the demonstrations established that #thedress phenomenon occurs not only for images of the dress but also for the real dress under real light sources of different spectral composition and spatial configurations.

The muskrat (Ondatra zibethicus) is an invasive species in Europe. The extensive waterways of the Netherlands provide ideal habitat for muskrats, and a large population established itself after arrival in 1941. A control program was put into effect immediately because muskrat burrowing can compromise the integrity of dikes and, hence, poses a significant public safety risk. The current (2015) annual catch of approximately 89,000 individuals is equivalent to approximately 0.30 muskrats/km of waterway, well above the national objective in spite of decades of effort. The control program is expensive (€35 M annually) and contested by animal rights groups. These factors created the need for a careful evaluation of the full range of control possibilities, from ‘no control’ to ‘extermination.’ As part of this, we experimentally evaluated the validity of a previously published correlation (based on historical data) between catch and effort. We raised or lowered removal effort (2013–2016) in a stratified random sample of 117 5-km × 5-km ‘atlas squares’ from the national grid. We found that catch-per-unit effort (CPUE) decreased after effort was increased, and rose after effort was decreased, by amounts slightly greater than expected based on the correlational data, though confidence intervals enclose zero. As anticipated, CPUE varied consistently and strongly between seasons. The biggest (and unanticipated) effects were those of the catch in the preceding 3 years (‘history’), and surrounding area (‘neighborhood’). Our experiment confirms estimates of intensity of control required to lower muskrat populations. These results will help with more effective allocation of control effort, and better-informed evaluation of the economic costs of various control options.

Salient object detection aims to obtain the most attractive objects from the input images, which severs as a pre-processing step for many image processing tasks. This paper presents a novel deep neural network design for salient object detection by formulating a pyramid spatial context module, PSC module for short, to capture the spatial context information at multiple scales. To achieve this, we first adopt convolutional operations with different dilated rates to generate the feature maps with different respective fields, and then use the two-round recurrent translations to explore multiple types of spatial context features on these feature maps. By further inserting this module in a deep network, namely PSCNet, we are able to optimize the network in an end-to-end manner for salient object detection. We evaluate the proposed method on six public benchmark datasets by comparing it with 25 salient object detection methods. The experimental results demonstrate that our PSCNet performs favorably against all the other methods.

This article explores the role of neighbourhoods as a spatial context for peer relationships among adolescents. We examine the correlations between neighbourhood composition and places suitable for young people for friendship intimacy and peer belonging. We hypothesise that favourable demographic and social neighbourhood compositions, knowledge, and use of places suitable for young people, as well as the spatial appropriation of such places, promote peer relationships. The present study carries out empirical testing of the spatial hypotheses with survey data from adolescents (N = 3225) in two German cities with 30 neighbourhoods. Our results show that neighbourhood composition is not related to peer relationships. Nevertheless, knowledge of safe places suitable for adolescents, as well as the appropriation of unsupervised (hang out) places, correlate with peer relationships. Interestingly, there are divergent results for 7th and 9th graders that can be explained by the developmental stages of the adolescents.

Spatial context may be important to direct to con­sumer (DTC) programs aimed at improving fresh fruit and vegetable access for low-income individu­als. The purpose of this study was to examine the sociodemographic and geospatial context (distance to pickup sites, number and density of proximal food retail outlets, etc.) surrounding community supported agriculture (CSA) pickup locations in relation to low-income customer residential loca­tions, and to synthesize this information with inter­view-derived perspectives on the challenges and opportunities of the pickup location from DTC producers and customers. This in-depth study examined cost-offset community supported agri­culture (CO-CSA) operations across four U.S. states (New York, North Carolina, Vermont, and Washington) and varying pickup sites (n=23), with pickup operational decisions determined by farm­ers (n=12). Physical addresses of farms, CO-CSA customers, and pickup sites were collected and geocoded. Geographic information systems (GIS) was used to examine road network distances for pickup locations across the study sites. Demo­graphic information at the census block level (e.g., percent racial minority, percent poverty level) was obtained for all study sites. Descriptive statistics were generated for geospatial variables. In-depth interviews with farmers and focus groups with CO-CSA customers were conducted to understand experiences with the CO-CSA in terms of physical access of pickup sites. We found that pickup sites were an average of 6.2 miles (10 kilometers) from customers’ homes, and on average, further than the supermarket (2.9 miles or 4.7 km). Farmers reported their efforts to select convenient pickup locations for low-income customers, though CO-CSA customers expressed mixed levels of accessi­bility. Spatial inaccessibility and differences in soci­odemographic data for customer versus pickup may explain perceived inaccessibility for some cus­tomers. These findings may help inform future approaches to plan and evaluate DTC operations targeting low-income individuals by consider­ing geospatial context and stakeholder experiences. See the press release for this article.

Contains fulltext : 231575.pdf (Publisher’s version ) (Open Access) The human visual system can rapidly extract regularities from our visual environment, generating predictive context. It has been shown that spatial predictive context can be used during visual search. We set out to see whether observers can additionally exploit temporal predictive context based on sequence order, using an extended version of a contextual cueing paradigm. Though we replicated the contextual cueing effect, repeating search scenes in a structured order versus a random order yielded no additional behavioural benefit. This was also true when we looked specifically at participants who revealed a sensitivity to spatial predictive context. We argue that spatial predictive context during visual search is more readily learned and subsequently exploited than temporal predictive context, potentially rendering the latter redundant. In conclusion, unlike spatial context, temporal context is not automatically extracted and used during visual search. 11 p.

Viminacium was the capital of the Roman province of Moesia Superior and an important legionary fortress. Today it is an archaeological park with protected and presented historic buildings and contemporary facilities, situated by the thermo power plant and strip coal mine near Kostolac in Serbia, and it is identified as a cultural property of exceptional importance for the Republic of Serbia. The protection and presentation of the historic buildings in Viminacium to date can be divided into groups as follows: basic protection and presentation; integrated protection and presentation through interpretation; and integrated protection and presentation through reconstruction and revitalisation. All the processes can be discussed within the framework of the evergreen topic of heritage conservation - the quest for the proper protection and presentation of buildings, which is often connected with the spatial context. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. 47018: IRS - Viminacium, Roman city and military legion camp - research of the material and non-material culture of inhabitants using the modern technologies of remote detection, geophysics, GIS, digitalization and 3D visualization]

Fuzzy c-means (FCM) and possibilistic c-means (PCM) are two commonly used fuzzy clustering algorithms for extracting land use land cover (LULC) information from satellite images. However, these algorithms use only spectral or grey-level information of pixels for clustering and ignore their spatial correlation. Different variants of the FCM algorithm have emerged recently that utilize local spatial information in addition to spectral information for clustering. Such algorithms are seen to generate clustering outputs that are more enhanced than the classical spectral-based FCM algorithm. Nonetheless, the scope of integrating spatial contextual information with the conventional PCM algorithm, which has several advantages over the FCM algorithm for supervised classification, has not been explored much. This study proposed integrating local spatial information with the PCM algorithm using simpler but proven approaches from available FCM-based local spatial information algorithms. The three new PCM-based local spatial information algorithms: Possibilistic c-means with spatial constraints (PCM-S), possibilistic local information c-means (PLICM), and adaptive possibilistic local information c-means (ADPLICM) algorithms, were developed corresponding to the available fuzzy c-means with spatial constraints (FCM-S), fuzzy local information c-means (FLICM), and adaptive fuzzy local information c-means (ADFLICM) algorithms. Experiments were conducted to analyze and compare the FCM and PCM classifier variants for supervised LULC classifications in soft (fuzzy) mode. The quantitative assessment of the soft classification results from fuzzy error matrix (FERM) and root mean square error (RMSE) suggested that the new PCM-based local spatial information classifiers produced higher accuracies than the PCM, FCM, or its local spatial variants, in the presence of untrained classes and noise. The promising results from PCM-based local spatial information classifiers suggest that the PCM algorithm, which is known to be naturally robust to noise, when integrated with local spatial information, has the potential to result in more efficient classifiers capable of better handling ambiguities caused by spectral confusions in landscapes.

Analyses of social contexts are almost universal in social research. In many cases, however, they are not explicitly labelled or even recognized as such. The conceptual aspect of ‘context’ then remains implicit in the substantive research question - such as when investigating the effects of 'social background' as a characteristic of an individual’s parental or family context. Systematic commonalities can be found among various analyses that either implicitly or explicitly deal with social contexts and their relevance for education. This article presents a formal classification of relevant contexts and their effects on education, discusses common methodological issues of contextual analyses and gives a brief survey of important findings in relevant research areas - in particular, family effects, peer effects, school effects and effects that can be associated with larger socio-economic contexts and institutional systems.

It has been suggested that commuting behaviours become habitual and that changes to commute mode are more likely at the time of major life events. However, evidence to support this has so far been limited to analyses of small-scale samples. To address this evidence gap, we use two waves of panel data from the UK Household Longitudinal Study (2009/10 and 2010/11) to identify and explain the prevalence of individual change in commute mode from year to year amongst a representative sample of the English working population (n = 15,200). One third of those that cycle or get the bus to work, and one quarter of those that walk to work, are shown to change commuting mode by the following year. Car commuting is more stable, with only one in ten car commuters changing mode by the following year. Commute mode changes are found to be primarily driven by alterations to the distance to work which occur in association with changing job or moving home. Switching to non-car commuting becomes much more likely (9.2 times) as the distance to work drops below three miles. High quality public transport links to employment centres are shown to encourage switches away from car commuting and mixed land uses are shown to encourage switches to active commuting (walking and cycling). Switches away from car commuting are found to be more likely (1.3 times) for those with a pro-environmental attitude. The attitude orientation is shown to precede the behaviour change, demonstrating evidence of ‘cause and effect’. Overall, the study shows that changes in commuting behaviour are strongly influenced by life events, spatial context and environmental attitude.

As the Internet of Things evolves, attention has been paid to adding intelligence capabilities, some of them via semantic technologies. However, many of these developments are still too device-centric and more needs to be done to make the IoT more people-centric. One important aspect in this direction is supporting spatial constructs that are meaningful to humans. We present the OpenThings platform as a basis to provide meaning via semantic technologies and demonstrate how it can be used to build environments that take into account a human-centered view of temporal and spatial context. We exemplify this by building a prototype for a system that supports proxemic interactions and time awareness.

Micro, small, and medium-sized enterprises (MSMEs) are an essential part of economies at the national, regional, and local levels. Understanding the determinants of the development of this sector is interesting not only for researchers but also for local governments to support the development of this sector. This paper analyses micro, small, and medium enterprises at the gmina (local) level in one region, the Kujawsko-Pomorskie voivodship (NUTS2) in Poland. The authors use multivariate linear regression, spatial econometrics, and classification trees to model the influence of different factors on the number of enterprises relative to population size. The authors found that the most crucial factor in all cases, independently of the method used, is the local government&rsquo, s revenue from personal income tax per capita. This finding, together with the lack of significance of variables related to the distance to technological parks or economic zones, indicates that the enterprises in the region produce mainly for local consumption and lack innovativeness. The authors also examined the influence of spatial context on the number of enterprises. The most important factor seems to be the percentage of built-up areas, but there are also others, depending on the model type, again, this confirms the local character of the activity of micro, small, and medium enterprises in the region. Variables representing the spatial context can explain the relative number of enterprises with coefficient of determination (R2) between 0.30 and 0.45, which shows that this context played a relatively significant role in the development of the MSME sector in the region. On the other hand, the econometric models (that include the neighborhood) are only significant (improving R2) for medium enterprises, which means that medium enterprises expand their activity beyond the local range.

Generalization of geographic information enables cognition and understanding not only of objects and phenomena located in space but also the relations and processes between them. The automation of this process requires formalization of cartographic knowledge, including information on the spatial context of objects. However, the question remains which information is crucial to the decisions regarding the generalization (in this paper: selection) of objects. The article presents and compares the usability of three methods based on rough set theories (rough set theory, dominance-based rough set theory, fuzzy rough set theory) that facilitate the designation of the attributes relevant to a decision. The methods are using different types (levels of measurements) of attributes. The author determines reducts and their cores (common elements) that show the relevance of attributes stemming from the spatial context. The fuzzy rough set theory method proved the least useful, whereas the rough set theory and dominance-based rough set theory methods seem to be recommendable (depending on the governing level of measurement).

International audience; Recent developments in transport systems and information technology applications enable people to move more frequently, faster, and further afield. The increasing flexibility of the labour market requires these new potentials to be pressed into use, with increased mobility as a result. Specific high mobility practices are emerging, such as daily long-duration commuting, weekly commuting and work-related frequent trips. However, people are not equal regarding high mobility. Based on the quantitative study Job Mobilities and Family Lives conducted in 2007 and 2011, this article combines longitudinal and cross-sectional perspectives to explore the potential of individuals for (high) mobility, using the concept of “motility”. Results show that motility is able to explain to a significant extent the various situations regarding a possible resort to high mobility. Although some of the participants are in a good position to cope with high mobility, others combine poor access to mobility and poor mobility skills. Even if they declare being ready to move, they appear to be a vulnerable position. Further results show that the evolution of mobility potential is explained by changes in mobility projects: family, economic and spatial contexts are central to a better understanding of these changes. In this regard, the situation of the Spaniards, particularly affected from 2008 by the financial crisis, is striking. Finally, analysis of the link between motility and mobility underlines that a higher mobility potential often does not imply more frequent resort to high mobility.; Le développement des offres en matière de transports et de technologies de la communication permettent aux personnes de se déplacer toujours plus, plus loin et plus rapidement. La flexibilisation du marché du travail impose l’utilisation de ces potentiels et favorise la mobilité. Plus spécifiquement, elle accompagne l’émergence de pratiques de grande mobilité, telles que la pendularité de longue durée, la bi-résidentialité ou encore les voyages fréquents pour motif professionnel. Dans ce contexte, les personnes ne sont pas toutes égales face à la grande mobilité. Basé sur l’enquête quantitative longitudinale Job Mobilities and Family Lives réalisée en 2007 puis en 2011, cet article, dans une perspective transversale et longitudinale, vise à explorer le potentiel de (grande) mobilité des personnes, à l’aide du concept de « motilité ». Premièrement, les résultats montrent que la motilité permet de décrire finement les situations des personnes dans la perspective d’un recours éventuel à la grande mobilité. Alors que certains sont dans une position confortable face à la grande mobilité, d’autres en revanche combinent de mauvaises compétences de mobilité et des accès limités. Même s’ils se déclarent disposés à la grande mobilité, ils apparaissent comme plus vulnérables. Deuxièmement, l’évolution du potentiel de mobilité est avant tout portée par des changements dans les projets de mobilité : les contextes familiaux, économiques et spatiaux dans lesquels les personnes se trouvent expliquent ces changements. La situation des Espagnols, particulièrement touchés par la crise dès 2008, est à ce sujet très parlante. Finalement, l’analyse du lien entre motilité et mobilité montre, de manière contre-intuitive, qu’un plus grand potentiel de mobilité ne se traduit pas nécessairement par un recours plus important à la grande mobilité.

vol.16(1) (2017) 119-138, Niniejszy artykuł został poświęcony kształtowaniu miejskich pieszych przestrzeni publicznych w nowych rewitalizowanych strukturach miejskich miast europejskich początkiem XXI wieku na przykładzie nowego rewitalizowanego centrum Bjørvika Barcode w Oslo. Powstają nowe przestrzenie publiczne kreujące nowy kontekst przestrzenny. Artykuł dotyczy także niektórych aspektów kreacji przestrzeni szczególnie z pozycji pieszych użytkowników „parteru” tych przestrzeni oraz ich percepcji związanej m. in. z kompozycją i estetyką architektury oraz stosunku do otoczenia i natury. Kreacja wnętrz miejskich przestrzeni posiada znaczący wpływ na kształtowanie otaczającej synergicznej architektury i synergicznych pieszych miejskich przestrzeni publicznych, a także tworzy nową tożsamość przestrzenną miejsca i architektury, This paper is devoted to the process of shaping of urban pedestrian public spaces in new revitalised urban structures of European cities in the early 21st century upon the example of a new revitalised centre of Bjørvika Barcode in Oslo. New public spaces emerge, creating a new spatial context. The paper also focuses on some aspects of the creation of space, particularly from the perspective of pedestrian users of the ‘ground floor’ of these spaces and the perception thereof connected with – without limitations – composition and aesthetics of architecture, and its relation towards the surrounding area and nature. Creation of urban spaces has a significant effect on the process of shaping of the surrounding synergic architecture and synergic urban pedestrian public spaces, as well as creates a new spatial identity of the place and its architecture.

Industry competition is moving from the company-level towards business ecosystems, where organizations must develop mutually beneficial relationships with each other. This paper studies business ecosystem phenomena, focusing especially on the spatial (geographical) context within the health and life sciences industry. In addition, business ecosystem evolution and change dynamics are addressed. This study is literature-based; the findings and analysis provide a research frame for forthcoming empirical studies. Despite increasing attention, business ecosystem literature is still relatively immature, and previous studies have mostly focused on software and the information technology (it) industries. Hence, this paper provides new insights into the business ecosystem concept in a novel context.

What we see depends on the spatial context in which it appears. Previous work has linked the suppression of perceived contrast by surrounding stimuli to reduced neural responses in early visual cortex. This surround suppression depends on at least two separable neural mechanisms, “low-level” and “higher level,” which can be differentiated by their response characteristics. We used electroencephalography to demonstrate for the first time that human occipital neural responses show evidence of these two suppression mechanisms. Eighteen adults (10 women, 8 men) each participated in three experimental sessions, in which they viewed visual stimuli through a mirror stereoscope. The first session was used to identify the C1 component, while the second and third comprised the main experiment. Event-related potentials were measured in response to center gratings either with no surround or with surrounding gratings oriented parallel or orthogonal, and presented in either the same eye (monoptic) or the opposite eye (dichoptic). We found that the earliest component of an event-related potential (C1; ∼60 ms) was suppressed by surrounding stimuli, but that suppression did not depend on surround configuration. This suggests a suppression mechanism that is not tuned for relative orientation acting on the earliest cortical response to the target. A later response component (N1; ∼160 ms) showed stronger suppression for parallel and monoptic surrounds, consistent with our earlier psychophysical results and a second form of suppression that is binocular and orientation tuned. We conclude that these two forms of surround suppression have distinct response time courses in the human visual system, which can be differentiated using electrophysiology.

Mapping deforestation using medium spatial resolution satellite data (e.g. Landsat) is increasingly shifting from decadal and annual scales to sub-annual scales in recent years, but this shift has brought new challenges on how to account for seasonality in the satellite data when detecting deforestation. A seasonal model is typically used to account for seasonality, but fitting a seasonal model is difficult when there are not enough data in the time series. Here, we propose a new approach that reduces seasonality in satellite image time series using spatial context. With this spatial context approach, each pixel value in the image is spatially normalised using the median value calculated from neighbouring pixels whose pixel values are above the 90th percentile. Using Landsat data, we compared our spatial context approach to a seasonal model approach at a humid tropical forest in Brazil and a dry tropical forest with strong seasonality in Bolivia. After reducing seasonal variations in Landsat data, we detected deforestation from the same data using the Breaks For Additive Season and Trend (BFAST) method. We show that, in dry tropical forest, deforestation events are detected much earlier when the spatial context approach is used to reduce seasonal variations in Landsat data than when a seasonal model is used. In the dry tropical forest, the median temporal detection delay for deforestation from the spatial context approach was two observations, seven times shorter than the median temporal detection delay from the seasonal model approach (15 observations). In the humid tropical forest, the difference in the temporal detection delay between the spatial context and seasonal model approach was not significant. The differences in overall spatial accuracy between the spatial context and seasonal model were also not significant in both dry and humid tropical forests. The main benefit for using spatial context is early detection of deforestation events in forests with strong seasonality. Therefore, the spatial context approach we propose here provides opportunity to monitor deforestation events in dry tropical forests at sub-annual scales using Landsat data.

Theory indicates that spatial scale and habitat configuration are fundamental for coevolutionary dynamics and how diversity is maintained in host–pathogen interactions. Yet, we lack empirical data to translate the theory to natural host–parasite systems. In this study, we conduct a multiscale cross-inoculation study using the specialist wild plant pathogen Podosphaera plantaginis on its host plant Plantago lanceolata. We apply the same sampling scheme to a region with highly fragmented (Aland) and continuous (Saaremaa) host populations. Although theory predicts higher parasite virulence in continuous regions, we did not detect differences in traits conferring virulence among the regions. Patterns of adaptation were highly scale dependent. We detected parasite maladaptation among regions, and among populations separated by intermediate distances (6.0–40.0 km) within the fragmented region. In contrast, parasite performance did not vary significantly according to host origin in the continuous landscape. For both regions, differentiation among populations was much larger for genetic variation than for phenotypic variation, indicating balancing selection maintaining phenotypic variation within populations. Our findings illustrate the critical role of spatial scale and habitat configuration in driving host–parasite coevolution. The absence of more aggressive strains in the continuous landscape, in contrast to theoretical predictions, has major implications for long-term decision making in conservation, agriculture, and public health.

Statistical data often have a spatial (geographic) context, be it countries of the world, states in the US, counties within a state, cities across the globe, or locations where measurements have been taken. However, most introductory statistics books do not even suggest that such data often are not independent from location, but rather are eected by some spatial association. Remedies are simple: Display data via various map views and brie y discuss which additional information can be extracted from such a graphical representation. In this report, we will visit a variety of popular introductory statistics textbooks and show how some of the data used in examples and exercises can be initially displayed via various map views, such as choropleth maps or micromaps. Students familiar with R should be able to create similar map displays by themselves via several R packages.