GIScience

This paper presents a new geospatial approach, and a proposal to study the geographic educational path of individuals or social groups identified by researchers using a Geographic Information System (GIS) and spatial statistics. A scheme of research proceedings has been proposed,
including obtaining data from various sources (including surveys and other sources, e.g., from the university and OpenStreetMap), their proper preparation and categorisation into one geodatabase
on the GIS system, followed by visualisation and the calculation of statistics. The whole research
procedure was carried out in GIS. The results can be useful for detecting patterns of educational paths
in different countries and social groups, and comparing them. Indirectly, they can be used to study
mobility, and to indicate the spatial range of studied schools. The study was carried out among a
group of students of geoinformation at the University of Lodz. Visualization and analysis of their geographical educational path showed that most of them attended schools close to where they lived, indicating low mobility during their education. The results obtained may be relevant to the “spatial turn” in education research

Since its emergence in the 1990s, the area of Participatory GIS (PGIS) has generated numerous interactive mapping tools to support complex planning processes. The need to involve non-expert users makes the usability of these tools a crucial aspect that contributes to their success or failure. While many approaches and procedures have been proposed to assess usability in general, to date there is no standardized way to measure the overall usability of a PGIS. For this purpose, we introduce the Participatory GIS Usability Scale (PGUS), a questionnaire to evaluate the usability of a PGIS along five dimensions (user interface, spatial interface, learnability, effectiveness, and communication). The questionnaire was developed in collaboration with the user community of SeaSketch, a web-based platform for marine spatial planning. PGUS quantifies the subjective perception of usability on a scale between 0 and 100, facilitating the rapid evaluation and comparison between PGIS. As a case study, the PGUS was used to collect feedback from 175 SeaSketch users, highlighting the usability strengths and weaknesses of the platform.

Anyone involved in teaching the principles and applications of geographic information science and technology (GIS&T) understands the challenges of effective instruction within an environment subject to nearly constant change. Indeed, the dynamic nature of GIS&T introduces both new paradigms and increasingly powerful tools for exploring spatial relationships. However, while past efforts among educators and practitioners have identified knowledge and competen-cies important to GIS&T learning, less attention has been directed at methods used to teach GIS&T. For example, while some instructors employ traditional approaches such as lectures and structured laboratory exercises, others have shifted to active learning strategies such as "flipped class-rooms" and collaborative, project-oriented assignments. In this article, we assess the pedagogical approaches used to teach GIS&T courses through an Internet-based survey of 318 college and university faculty. Our findings demonstrate that active learning pedagogies are becoming more firmly established, supplementing or replacing traditional teaching approaches. Contrary to our assumptions, age and teaching experience are not factors that influence the adoption of active learning strategies. Along with assessing instructional approaches, our survey identifies the challenges associated with teaching GIS&T, as identified by survey respondents.

GIS technology has transformed spatial data handling capabilities and made it necessary for governments to reexamine their roles with respect to the supply and availability of geographical information. This paper reviews the experiences of eleven national initiatives which together constitute the ® rst generation of national spatial data infrastructures and it also considers what lessons might be learnt for the next generation that will come into being over the next ten years. The presentation is divided into three sections. The ® rst of these consists of a short pro® le of each of the eleven strategies and United States. These are evaluated in the second section in relation to the driving forces behind them and their main features in terms of status, scope, access, approach to implementation and resources. The last section considers what lessons might be learnt from this experience and discusses the changing context within which the next generation of national spatial data infrastructures are likely to be formulated. It concludes with some thoughts on which countries are most likely to be candidates for the next generation of national spatial data infrastructures.

In the northern latitudes of the Western Hemisphere, a region dominated by tundra environments and limited resource variability, human foragers adapted their hunting and settlement strategies to gain advantage over an abundant and highly predictable terrestrial resource (caribou) (Binford 1978, 1980; Heffley 1981; Kelly 1995; Nelson 1899; VanStone 1974). The study area's unique landscape character and abundant resources attracted the region's prehistoric inhabitants far from the power centers of their affiliated socioterritories. The first objective of this research will analyze the correlation between hunting features and ice/snow patches in order to illustrate whether or not intercept hunting tactics where employed by the region's foraging groups during the summer months. The second objective is to analyze prehistoric settlement distribution patterns in order to determine the level of dispersion among socially relatable home bases or power centers. The third objective of this research is to analyze prehistoric hunter-gatherer time and energy costs incurred by travelling to the study area, as well as the amount of processed game (caribou) needed to balance those costs.

Gazetteers are important tools used in a wide variety of workflows that depend on linking natural language text to geographical space. The spatial properties of these data sources, such as coverage, balance, and completeness, affect the performance of common tasks such as geoparsing and geocoding. However, little attention has focused on how these properties vary in global gazetteers, particularly across country boundaries and according to feature types. In this paper, we present a detailed investigation of the spatial properties of two open gazetteers with worldwide coverage: GeoNames, and the Getty Thesaurus of Geographic Names (TGN). Using point density maps, correlations, and linear regressions, we analyze the global spatial coverage of each data source for the full set of features and for top feature types: populated places, streams, mountains, and hills. Results show wide discrepancies in coverage between the two datasets, sharp changes in feature type coverage across country borders, and idiosyncratic patterns dominated by a few countries for the more sparsely covered natural features. As more and more systems rely on recognizing and grounding named places, these patterns can influence the analysis of growing amounts of online text content and reinforce or amplify existing inequalities.

OpenStreetMap (OSM) is currently an important source for building data, despite the existence of potential quality issues. Previous studies have assessed OSM data quality by comparing it with reference building data, which may not otherwise be readily available. This study assessed OSM building completeness using population data, and investigated the effectiveness of using population data for building reference data. We proposed various approaches, including type-based and regression-based approaches and their subtypes, and designed measures and methods to evaluate these approaches. Our evaluation examined four study areas in two countries, using global population data sets at three spatial resolutions (1-km, 100-m, and 30-m). Results showed that the type-based approach correctly classified approximately 80–99% of the assessed grid cells. The regression-based approach resulted in a high linear correlation (0.7 or greater) between the population counts and the referenced building count/building area size, with the strongest correlation present for the 1-km population dataset. We conclude that the use of population data as referenced building data is an effective method for the assessment of OSM building completeness. The paper concludes with the advantages and limitations of using both the type-based and the regression-based approaches.

The geographic domain has widely been studied in ontology research. However, integrating the conceptualization of time and temporal referencing of geographic concepts in data models is a complex task that has by no means been " solved ". Existing geospatial ontologies have adopted a space-time model that, for example, distinguishes endurant entities (lasting through time, e.g., fixed natural features) from perdurant entities (e.g., processes or events). Such a model might exclude indigenous conceptualizations of time that are far more sophisticated. We find that conventional ontologies make assumptions about time that fail to take into consideration indigenous notions including: 1. Time is not linear; 2. Nothing is completely fixed in time; 3. Time has agency; and 4. Time is not temporal but social.

In the northern latitudes of the Western Hemisphere, a region dominated by tundra
environments and limited resource variability, human foragers adapted their hunting and
settlement strategies to gain advantage over an abundant and highly predictable terrestrial
resource (caribou) (Binford 1978, 1980; Heffley 1981; Kelly 1995; Nelson 1899; VanStone 1974).
The study area's unique landscape character and abundant resources attracted the region's
prehistoric inhabitants far from the power centers of their affiliated socioterritories.
This research has applied evolutionary theory to a geospatial analysis of prehistoric
hunting features in an effort to identify a link between feature clustering and the proximities of
ice/snow patches at Kuzitrin Lake and Twin Calderas, and in doing so, illustrate an
undocumented intercept game drive tactic used in the summer when caribou are broadly
dispersed. This thesis sought to clarify the spatial distribution patterns of hunting features in
the study area and settlements of Seward Peninsula, determine if features and settlements
cluster on the landscape consistent with the expectations derived from optimal foraging theory,
and explain how their spatial patterns can reveal prehistoric hunter-gatherer lands use in the
study area. The hypothesis offered at the beginning of this study was that collective hunting
tactics employed by prehistoric foraging groups were shaped by a drive to achieve net energy
optimality, and that hunting groups would maximize energy and time expenditures to exploit
the highest-ranking prey resources within their limits of available travel modes.
The expectations presented in this research have been statistically validated and are
premised on optimal foraging. Thus, it is reasonable to deduce that prehistoric foraging groups
maximized caribou exploitation by engaging in a unique collective hunting tactic associated
with the ice/snow patches at Kuzitrin Lake and Twin Calderas, and that socioterritorial
dominion over the area was dictated by available modes of travel and the time and energy
costs required to complete a journey.
I offer an alternative model of late Holocene hunter-gatherer land use based on the
findings of this research. The static model presented at the conclusion is provided as a heuristic
device for future investigation into late Holocene caribou hunting and settlement in Seward
Peninsula.

The primary aim of image data collection is to extract information from imagery and turn scene content into knowledge. In Geographic Information Science (GIScience), the term " object-based image analysis " (OBIA) was tentatively introduced in 2006. When it was re-formulated in 2008 as GEOBIA, the primary focus was set on Earth data-derived applications and the interdisciplinary novelty was emphasized of geospatio-temporal reasoning to cope with massive Earth observation (EO) imagery, where to integrate achievements accomplished by the remote sensing (RS) and CV communities. This article tries to (re-)emphasize the role of space/geospatial in image analysis, flanked by recent trends, such as big data analytics. The following key aspects of multi-source EO image analysis are promoted: (1) EO image enhancement and interoperability/harmonization at the radiometric and semantic levels of analysis; (2) big raster data storage and exploitation, affected by ongoing lacks in tackling spatiotemporal information in vector format; (3) deep (multi-scale) distributed CV systems (artificial neural networks); (4) hybrid (combined deductive/top-down and inductive/bottom-up) inference, (5) structured CV system of systems design, based on a convergence of spatial and color evidence, (6) consistency of CV with human visual perception; (7) semantic content-based image retrieval. The plea for a manifesto GEOBIA 2.0 is backed up backed up by some illustrative examples from the field of GIScience applications.

Choosing a textbook is among the most important decisions instructors
make in preparation for an academic term. Geographic Information Systems and Technology (GIS&T) textbook development has been influenced by a unique set of circumstances, mainly the rapid development of the discipline within an interdisciplinary environment,
which has resulted in a continuous state of evolution. We examine the anatomy of GIS&T textbooks through a comparison of their organization, content, and depth of coverage. Specifically, utilizing
the Geographic Information Science and Technology Body of
Knowledge (BoK) as a comprehensive reference, we categorize the
content of 26 of the most widely used introductory GIS textbooks.
Our results show that there has been consistent coverage of topics
over time, with analytical methods and geospatial data being the most
prominent topics covered in texts. However, individual textbooks
place varying emphasis on the BoK knowledge areas, which is potentially useful to instructors seeking books that emphasize particular
knowledge areas. Additionally, long-term trends indicate a shift toward an emphasis on new forms of geospatial data (e.g., social media). Ongoing efforts to expand and revise the BoK reflect how the discipline continues to manage its own evolution as new geographic research linked to GIS and GIScience emerges.

La crescente disponibilità di informazioni geografiche e il rapido sviluppo di nuove tecnologie per la gestione dei dati geografici (dai droni, al WebGIS, al Mobile-GIS) richiedono l'aggiornamento, la riorganizzazione  e  lo  sviluppo  dei  processi  decisionali  in  molti settori  dell'economia, dell’amministrazione pubblica e del non-profit. Allo stesso tempo, le Università devono cogliere la sfida  di  preparare un  ambiente  di  apprendimento  adatto  per  l'aggiornamento  e  la costruzione  di adeguate competenze. Con l'anno accademico 2015/2016 l'Università di Padova ha dato avvio al nuovo  master  di  secondo  livello  in  "GIScience  e  Sistemi  a  Pilotaggio  Remoto  (SAPR) per  la gestione integrata del territorio e delle risorse naturali". Il master vede la collaborazione di cinque dipartimenti  universitari,  aziende  che  operano  nel  campo  della  GIScience  e  dei  droni,  ONG.  Il master offre 4 indirizzi: Produzione e gestione di geo-informazioni; GIScience per la gestione dei conflitti ambientali e per la partecipazione a processi decisionali pubblici; Cartografia e GIS per le infrastrutture verdi; Geoinformazione e nuove tecnologie per un'agricoltura sostenibile. Il master ha avuto inizio a marzo 2016 con un primo gruppo di 25 corsisti ed è ora possibile condividere i primi risultati dell’osservazione partecipante per questa iniziativa, considerando il complesso contesto per il GIScience e la geografia in Italia.

Artykuł prezentuje podejście świata nauki do roli, jaką odgrywa GIS w jej ramach. Przedstawia dyskusję, jaka miała miejsce w 1993 r. w ramach debaty GIS-L, jej najważniejsze wnioski zaprezentowane w pracy D.J. Wrighta, M.F. Goodchilda i J.D. Proctora (1997), a także przyszłość Systemów Informacji Geograficznej widzianą oczami M. Goodchilda (2010). Na tle tych rozważań autorzy przedstawili własne doświadczenia
związane z GIS w polskiej nauce oraz podejście do GIS jako nauki.

The visualization of hierarchical and nested spatial regions remains a challenge to cartographers. Despite progress in
computer algorithms for visualizing general hierarchical data, mapping spatial hierarchical regions, especially with static,
noninteractive means, still requires considerable manual efforts. This paper proposes a two-step algorithm that can
automatically recommend perception-based colors and help reveal the hierarchical structure embedded in nested regions.
It first systematically sorts regions according to their contiguity and containment relations at multiple hierarchical levels.
Then, perception-based colors are generated using the order of regions with the goal of maximizing differentiability
between top-level regions while retaining the perceived uniformity of the bottom-level regions. With the coloring scheme
recommended by this algorithm, the metric color differences among regions mathematically reflect their hierarchical
positions and spatial relations. The resultant colors, therefore, can potentially help map-readers perceive the spatially
constrained hierarchy structure built in nested regions.

Cet ouvrage montre la valeur de la „theorie des lieux centra- ux” pour les etudes byzantines. Cette methode regressive permet la reconstruc- tion des structures d'habitat non seulement dans l'Empire byzantin et l'Empire serbe mais encore dans lEmpire ottoman. L'analyse des sources ecrites - en particulier les actes des monasteres du Mont Athos - a partir de la periode de 1259 a 1395 sur une etude de cas (la vallee de Strumica) a produit les resultats suivants concernant la „theorie des lieux centraux”: dans la vallee de Strumica il y avait trente habitats avec une continuite de peuplement a l'epoque byzan- tine. L'analyse des donnees est fondee sur ces schemas que Koder a developpe basee sur la „theorie des lieux centraux” de Christaller. On reconnait que 24 ha- bitats sont attestes aussi a l'epoque ottomane, 6 habitats sont disparus. En outre, les registres ottomans confirment l'impression que les sources byzantines et vieux-slaves ne sont pas transmises completement, parce que le defter de 1519 consigne 94 villages de plus, le defter de 1570/73 86 villages de plus que les sources medievales dans la vallee de Strumica.

The increasing availability of geographic information and the rapid development of new technologies for the management of geographic data (from drones, to WebGIS, to Mobile-GIS) require the updating, the reorganization and the development of decision-making processes in many sectors of the economy, public administration and the non-profit. At the same time Universities are challenged in providing suitable learning environment for updating and building appropriated skills. With the academic year 2015/2016 the University of Padua has launched the new Master di secondo livello on "GIScience and Unmanned System for the integrated management of the territory and the natural resources-with majors" (Professional Master). The master sees the collaboration of five departments, firms operating on GISciences and drones, NGO. The master offers 4 academic paths: Production and management of geo-information; GIScience for environmental conflict management and participation on public decision making; Cartography and GIS for green infrastructures; Geoinformation and new technologies for sustainable agriculture. With a first group of 25 people the Master started in March 2016 so we can share the first results participant observation of this initiative considering the complex context for GIScience and geography in Italy.

La recherche porte sur un processus participatif de production d'un Système d'information géographique (SIG) amenant les participants à explorer leurs représentations territoriales afin de favoriser leur implication dans l'aménagement. L'étude est réalisée dans un quartier limitrophe à la décharge publique de Dakar, qui sera fermée dans le cadre de projets d'infrastructures qui transformeront les dynamiques territoriales de la région. La recherche est basée sur l'hypothèse que le processus contribuera à la transformation des regards des résidents vers une volonté collective de s'impliquer dans la planification de l'aménagement dont ils sont présentement exclus. Lors d'ateliers de cartes collectives en groupe et de marches documentées dans le quartier, les participants sont amenés à explorer la manière dont ils décrivent leur quartier, leurs déplacements et activités quotidiennes et les sentiments associés à leur environnement. Ces ateliers ont été réalisés durant l'été 2010 avec six groupes de cinq personnes. Les travaux ont été restitués lors d'une séance de consultation publique finale. Les discussions de cette séance sont comparées aux discussions d'une séance de 2009 en utilisant le concept de lieu de contrôle et l'échelle du développement de Perry, empruntés à la psychologie, pour mesurer le sentiment de contrôle et d'engagement envers l'évolution du territoire. Les résultats montrent qu'un pas en avant est fait, notamment par une formulation d'enjeux prioritaires, la volonté d'avoir un plan de quartier, une responsabilisation et un pouvoir d'action par rapport aux enjeux.

In contemporary cities, data are a key component in drives to become "smarter". From sensors embedded in the urban landscape to increasing pressure to make data freely available in open data platforms, new ways of producing and collecting data are shifting how we think of and represent places and people. Data's collection, processing, production, and representation all entail complex negotiations that produce and underwrite new inequalities and exclusions. Yet, while some critical research has begun to explore the precise types and functions of these data-focused inequalities and exclusions, it remains understudied both comparatively and in empirical grounding.

These shifts can be understood through existing geographic research, but raise new questions and research challenges at the intersection of GIScience and urban geography. In this presentation I draw on a nascent project in the city of Calgary that seeks to explore these processes. The City of Calgary currently approaches its open data platform and smart city initiatives in ways that challenge research conducted elsewhere, in avoiding the smart city discursive framework and seeming to cautiously vet the types of data released for public use. I submit that while existing research on knowledge politics is useful for understanding the politics behind open data platforms, the Calgary case entails practices and processes that necessitate reconceptualizing how knowledge, places, and people come to be encoded as data.

A general understanding of the solar admittance and solar gains incident on the urban fabric is very useful to assess the potential implementation of renewable energies at the scale of the city. The authors propose a tool that uses Light Detection and Ranging (LIDAR) data to automatically derive this information in a fast and accurate way with no need to refer to the construction of complex models of the urban layout. In particular, a complete methodology from the extraction of LIDAR data to the environmental analysis of urban models and the visualization of results is presented. Aim of the work is to establish a process to investigate digital urban models integrating cross-disciplinary competences, like remote sensing, GIS, image processing and urban and environmental studies. Toward this goal, working on several interfaces, tools and datasets was necessary to provide a consequent structure to the introduced methodology. Case study for application was two districts in Geneva (a historical district, and a modern one) where LIDAR data are available. The use of a hybrid approach from raw LIDAR data and vectorial digital maps (GIS data) of roofs footprints derived from a 3-D urban model of the city of Geneva allowed to interpolate a 2.5-D urban surface model (DUSM) of roofs buildings, with a resolution grid of 0.50 by 0.50 metres. This step reveals itself as fundamental for processing the environmental analysis of the urban texture. In particular, the implemented tool calculates solar radiation and solar accessibility on buildings’ roofs, in order to investigate the potential for implementing photovoltaic panels.

In just twenty years, the World Wide Web and mobile networks have changed the way we communicate, the way we search for information we need, and the way we organize our activities. The opportunities aff�orded by these changes led to the development of literally millions of applications, including location-based services, which aim to provide information based on a user's position. However, the search methods used by such
mobile information services have been criticized, because of the simplistic approach they employ.

Aim of this dissertation is to o�er an in-depth study of the concept of relevance in mobile information services. The term "geographic relevance" has been proposed in literature to address such a concept, in order to emphasize the importance of space and time in assessing relevance in mobile information services. In this dissertation, I provide a detailed discussion of the concept of geographic relevance, o�er a conceptual
model of geographic relevance, and propose a list of novel criteria of relevance to be used in assessing the geographic relevance of geographic objects in mobile information services. Two empirical studies are presented, which con�rm the validity of the proposed model and criteria. Based on these outcomes, I propose a computational method for the assessment of geographic relevance. The results show that the proposed assessment method is able to replicate human judgements of geographic relevance. Therefore, I argue
that the proposed approach is an eff�ective method for assessing geographic relevance in mobile information services.
The outcomes of the empirical studies presented in this dissertation con�rm previous studies, showing how spatial proximity is not suff�cient to consider a geographic object as relevant -- assuming it is what a user is searching for. The temporal aspect plays a fundamental role, as temporally unavailable objects are to be considered as non-relevant. Moreover, in this dissertation, I suggest and prove that the geographic environment of a place or object has to be taken into account when assessing its geographic relevance. The
presence of more objects of the same category in a neighborhood, or the presence of objects belonging to correlated categories, increases the relevance of the object. Geographic relevance is also dependent on the opportunities off�ered to a user in the neighborhood. Finally, as a user commonly seeks for places in order to perform an activity, I advocate the importance of taking into account the consequences of a user performing an activity in a given place, with respect to previous, concurrent, and subsequent activities, when assessing the geographic relevance of places or geographic objects.

Gazetteers are dictionaries of geographic place-names that have important implications far beyond the worlds of geographers and cartographers. By containing ‘definitive’ lists of places, gazetteers have the ontological power to define what will and will not be geocoded and represented in databases, maps, search engines, and ultimately our spatial understandings of place. This paper focuses attention on GeoNames, which is the world's largest freely available and widely used gazetteer. We illustrate how content in GeoNames is characterised by highly uneven spatial distributions. There are dense clusters of place-names in some parts of the world and a relative absence of geographic content in others. These patterns are related not just to the wealth and population size of a country, but also to its policies on Internet access and open data. The paper then traces some of the specific implications of this information inequality: showing how biases in gazetteers are propagated in a variety of geographic meaning-making.

Interview given by Mihailo Popović on the scholarly project "A Digital Geoportal of the History of the Serbs in Vienna (1741-1918)" (Austrian Journal Kosmo 05/2018, p. 50f.).
Cf. on the respective project: https://orthodoxes-wien.oeaw.ac.at/
The same interview was published online in German: 
https://www.kosmo.at/auf-spurensuche-zwei-historiker-digitalisieren-die-geschichte-der-serben-in-wien/

The relation of spatial data and e-Government is important, but not always acknowledged in the development and implementation of e-Government. The implementation of the INSPIRE directive pushed this agenda towards a growing awareness of the role of spatial data and the need for a spatial data infrastructure to support e-Government. With technology, policies, data and infrastructure in place, new iterations of this relationship are needed, in order to reach a higher level of maturity. This paper analyses and discusses the need for the differentiated roles of spatial data as an important step towards more mature e-Government. As part of this understanding, the paper focuses on a subset of data, so-called 'spatio-legal data'. Spatio-legal data are created within the regulated legal environment of public administration, and used for rulings within a given legal area. Sometimes, the legal status of these data is the wording of the law and the spatial data are just visualisation thereof. Under other circumstances, the spatial data themselves represent the legal status. Compliance between spatial data and the legal administrative framework is necessary, to obtain a mature e-Government. A preliminary test of the hypothesis on a small scale, using Denmark as a case study, supports the need for discussion and awareness of the role of spatial data in e-Government with emphasis on the use of spatio-legal data.

Image retrieval of landscape photographs requires accurate annotation using multi-faceted descriptions relating to the subject and content of the photograph. The subject of such photographs is dominantly the terrain and spatial objects visible from the photographer’s viewpoint. While some spatial objects in the background may be obscured by foreground vegetation, other visible spatial objects beyond a certain distance may not present noteworthy elements of the captured scene (such as distant houses). Our aim is to assess approaches to improve the identification of practically visible spatial objects for image annotation. These approaches include the consideration of the apparent spatial object size and landcover information about occluding vegetation. These inputs are used to enhance viewshed analysis to accurately identify only spatial objects practically visible and therefore likely to be notable subjects of a photograph. The two approaches are evaluated in an experiment in a semi-rural area of Switzerland, whose results indicate that visual magnitude is key in accurate identification of visible spatial objects.

This paper presents a new geospatial approach, and a proposal to study the geographic educational path of individuals or social groups identified by researchers using a Geographic Information System (GIS) and spatial statistics. A scheme of research proceedings has been proposed, including obtaining data from various sources (including surveys and other sources, e.g., from the university and OpenStreetMap), their proper preparation and categorisation into one geodatabase on the GIS system, followed by visualisation and the calculation of statistics. The whole research procedure was carried out in GIS. The results can be useful for detecting patterns of educational paths in different countries and social groups, and comparing them. Indirectly, they can be used to study mobility, and to indicate the spatial range of studied schools. The study was carried out among a group of students of geoinformation at the University of Lodz. Visualization and analysis of their geographical educatio...

In this chapter, an overview of different variants of the original Self-Organizing Map algorithm is presented, with an emphasis on those that can integrate spatial reasoning or otherwise be applied in the context of Geographic Information Science. A few of the most relevant variants are discussed, together with a recently developed variant proposed by the authors. An example of the application of some SOM variants to an artificial dataset is presented, and their main advantages pointed out. Finally, these variants are used to solve a real world problem, and conclusions and recommendations for future work are given.

There has been much successful research to analyze the movement of people, wildlife, goods, and more, where the data is precise movement trajectories. This research has mostly ignored geographic movement that comes in the form of text descriptions. Descriptions of things moving have an advantage over trajectory data. It often includes rich contextual information that describes what is moving, when it moves, why it moves, and how it moves. Challenges exist to utilizing this source, like ambiguities in the text's meaning and the author and reader's knowledge and background. Still, computational advances like Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning are well suited to uncover essential features in the movement descriptions. This research makes several contributions to improve the understanding of geographic movement described in text documents. It also guides further research to improved methods for utilizing this underused resource. First, I created a corpus of sentences labeled as describing geographic movement or not. Creating this corpus proved difficult without any comparable corpora to start with, high human labeling costs, and text ambiguities. To overcome these challenges, I developed an iterative process employing hand labeling, crowd voting for agreement, and machine learning to predict more labels. By merging advances in word embeddings with traditional machine learning models, and model ensembling, prediction accuracy is acceptable to produce a larger silver-standard corpus where a small amount of error in predictions is accepted. In addition to the detection of movement, my corpus will likely benefit computational processing of geography in text and spatial cognition. The corpus contains many geographic place mentions along with contextual information that computational processing can learn important linguistics features that are associated with the place mentions. Spatial cognition research can analyze differences in geographic understanding of the text both from the author's side and any reader's side. My process also provides a baseline method to detect statements that describe geographic movement. Second, I show how interpreting geographic movement described in text documents is challenging because of general spatial terms, linguistics that make the thing(s) movement unclear, and many temporal references and groupings. To overcome these challenges, I identified multiple essential characteristics of the movement described that humans use to differentiate descriptions. I also explore current computational text processing techniques to analyze the movement characteristics described in the text and show how these characteristics help people understand patterns in larger bodies of text describing movement. My findings contribute to an improved understanding of the critical characteristics of geographic movement in text descriptions. The third contribution in my research is an initial effort to derive meaningful information from geographic movement descriptions at a large and general scale. Geographic Information Retrieval (GIR) is a sub-domain of both IR and GIScience that has emphasized retrieval of documents that mention or are about places along with some focus on geographic feature extraction. GIR advances have created an as yet primarily unrealized potential to leverage text documents as sources for geographic-scale movement information. The geographic movement described in text documents can complement detailed movement data, provide an alternative when precise data does not exist, and provide the added benefit of rich context about the movement. As an initial large-scale effort to derive meaningful information from textual data describing geographic movement, we applied multiple computational techniques to hundreds of millions of statements. First, we identify and geolocate the geographic places mentioned. Next, we predict those that describe geographic movement. Finally, because the COVID-19 pandemic highlighted the importance of global movement disruptions, we predict if the statement describes not moving or restricted movement. Since the data is messy and complicated and the prediction techniques are not perfect, we designed and implemented a geovisual analytics system through which a visual interface enables humans to explore initial statement classifications, the places mentioned in them, and co-occurring place mentions to assess the validity of computational methods and provide direct feedback toward improving results. We include two user scenarios that show how a human can derive meaningful information about geographic movement through the geovisual analytics system. The user scenarios constitute systematic case studies to demonstrate the utility of the approach. Existing geographic movement research has improved analysis methods and shown how these methods enhance understanding of human movement, wildlife movement, and much more. This research primarily uses precise movement data acquired through sensors like GPS but ignores such data in text documents. The geographic movement described in text documents can complement detailed movement data, provide an alternative when precise data does not exist, and provide the added benefit of rich context about the movement. My research has shown why this information is challenging to use, how people differentiate the movement described, and how computational methods can utilize the movement's differences to improve sense-making with this underused resource.

User-generated family trees are invaluable for constructing population-scale family networks and studying population dynamics over many generations and far into the past. Family trees contain information on individuals such as birth and death places and years, and kinship ties, e.g., parent-child, spouse, and sibling relationships. Such information about individuals in family trees makes it possible to extract migration networks over time. Despite the recent advances, existing spatial and temporal abstraction techniques for time-variant flow data have limitations due to the lack of knowledge on the effect of temporal partitioning on flow patterns. In this study, we extracted state-to-state migration patterns over a period of 150 years between 1776 and 1926 from a cleaned, geocoded and connected family trees from Rootsweb.com. We used birthplaces and birthyears of parents and children to extract intergenerational migration flows between states. To reveal the temporal trends of migration patterns, we evaluated three temporal partitioning strategies: (1) predefined periods in American history, (2) overlapping time periods with fixed length, and (3) time periods with variable length, which have approximately equal volume of moves per time period. To account for the effect of geographic proximity and flow volumes in migration flows, we transformed the raw flows into modularity flows using a double-constrained a gravity model. Our preliminary results revealed longitudinal population mobility in the U.S. on such a large spatial and temporal scale.

The accreditation of GIS programs was first proposed more than 25 years ago as a means of encouraging consistency in instructional content and learning outcomes across many new GIS programs being developed at U.S. colleges and universities. However, in lieu of a peer review system to evaluate the quality of instruction, the GIS community focused instead on certification programs for recognizing and rewarding competency and professionalism among persons already in the workforce. With hundreds of colleges and universities now offering formal programs in GIScience ranging from certificates to undergraduate and graduate degrees, it may be an appropriate time reconsider rewards associated with accreditation. This article argues that accreditation can benefit institutions, students, and GIScience employers by directing attention to “upstream” and formative elements in the preparation of entry-level GIScience professionals that can potentially complement “downstream” and summative programs for recognizing experienced GIScience professionals such as certification. Along with providing detail about the implementation and administration of accreditation, we explore accreditation processes in surveying and engineering as possible pathways for accrediting academic GIScience programs.