A review of spatiotemporal models for count data in R packages. A case study of COVID-19 data

Spatiotemporal models for count data are required in a wide range of scientific fields, and they have become particularly crucial today because of their ability to analyze COVID-19- related data. The main objective of this paper is to present a review describing the most important approaches, and we monitor their performance under the same dataset. For this review, we focus on the three R-packages that can be used for this purpose, and the different models assessed are representative of the two most widespread methodologies used to analyze spatiotemporal count data: the classical approach and the Bayesian point of view. A COVID-19-related case study is analyzed as an illustration of these different methodologies. Because of the current urgent need for monitoring and predicting data in the COVID-19 pandemic, this case study is, in itself, of particular importance and can be considered the secondary objective of this work. Satisfactory and promising results have been obtained in this second goal. With respect to the main objective, it has been seen that, although the three models provide similar results in our case study, their different properties and flexibility allow us to choose the model depending on the application at hand

From SpaceStat to CyberGIS: Twenty Years of Spatial Data Analysis Software

This essay assesses the evolution of the way in which spatial data analytical methods have been incorporated into software tools over the past two decades. It is part retrospective and prospective, going beyond a historical review to outline some ideas about important factors that drove the software development, such as methodological advances, the open source movement and the advent of the internet and cyberinfrastructure. The review highlights activities carried out by the author and his collaborators and uses SpaceStat, GeoDa, PySAL and recent spatial analytical web services developed at the ASU GeoDa Center as illustrative examples. It outlines a vision for a spatial econometrics workbench as an example of the incorporation of spatial analytical functionality in a cyberGIS.

Interactive analysis of time intervals in a two-dimensional space

Time intervals are conventionally represented as linear segments in a one-dimensional space. An alternative representation of time intervals is the triangular model (TM), which represents time intervals as points in a two-dimensional space. In this paper, the use of TM in visualising and analysing time intervals is investigated. Not only does this model offer a compact visualisation of the distribution of intervals, it also supports an innovative temporal query mechanism that relies on geometries in the two-dimensional space. This query mechanism has the potential to simplify queries that are difficult to specify using traditional linear temporal query devices. Moreover, a software prototype that implements TM in a geographical information system (GIS) is introduced. This prototype has been applied in a real scenario to analyse time intervals that were detected by a Bluetooth tracking system. This application shows that TM has the potential to support a traditional GIS to analyse interval-based geographical data

Understanding the Spatial Structure of Urban Commuting Using Mobile Phone Location Data: A Case Study of Shenzhen, China

Understanding commuting patterns has been a classic research topic in the fields of geography, transportation and urban planning, and it is significant for handling the increasingly serious urban traffic congestion and air pollution and their impacts on the quality of life. Traditional studies have used travel survey data to investigate commuting from the aspects of commuting mode, efficiency and influence factors. Due to the limited sample size of these data, it is difficult to examine the large-scale commuting patterns of urban citizens, especially when exploring the spatial structure of commuting. This study attempts to understand the spatial structure characteristics generated by human commutes to work by using massive mobile phone datasets. A three-step workflow was proposed to accomplish this goal, which includes extracting the home and work locations of phone users, detecting the communities from the commuting network, and identifying the commuting convergence and divergence areas for each community. A case study of Shenzhen, China was implemented to determine the commuting structure. We found that there are thirteen communities detected from the commuting network and that some of the communities are in accordance with urban planning; moreover, spatial polycentric polygons exist in each community. These findings can be referenced by urban planners or policy-makers to optimize the spatial layout of the urban functional zones. Document type: Articl

Spatio-temporal visualisation and data exploration of traditional ecological knowledge/indigenous knowledge

Traditional Ecological Knowledge (TEK) has been at the centre of mapping efforts for decades. Indigenous knowledge (IK) is a critical subset of TEK, and Indigenous peoples utilize a wide variety of techniques for keeping track of time. Although techniques for mapping and visualizing the temporal aspects of TEK/IK have been utilized, the spatio-temporal dimensions of TEK are not well explored visually outside of seasonal data and narrative approaches. Existing spatio-temporal models can add new visualization approaches for TEK but are limited by ontological constraints regarding time, particularly the poor support for multi-cyclical data and localized timing. For TEK to be well represented, flexible systems are needed for modelling and mapping time that correspond well with traditional conceptions of time being supported. These approaches can take cues from previous spatio-temporal visualization work in the GIS community, and from temporal depictions extant in existing cultural traditions

État des lieux des représentations dynamiques des temporalités des territoires

Le temps et ses caractéristiques ont toujours fait l’objet de grandes attentions pour comprendre les dynamiques des territoires. Aujourd’hui, que ce soit à cause des nouvelles capacités d’observation en temps réel, de l’accumulation des séries de données au cours du temps, ou à cause de la multiplication des rythmes, les temporalités à prendre en compte pour comprendre les dynamiques territoriales se multiplient et leurs imbrications se complexifient. Interroger les rythmes, les vitesses, les cycles de ces dynamiques, ou mettre en relation temporelle des phénomènes spatiaux tels que les évènements catastrophiques passés devient plus que jamais un enjeu pour comprendre et décider.Les jeux de méthodes mobilisables aujourd’hui pour représenter les temporalités des territoires sont en plein renouvellement, et imposent désormais bien souvent de franchir les fractures disciplinaires traditionnelles entre échelles, entre outils, entre formalismes. Les domaines d’applications potentiellement concernés, comme celui du développement durable des territoires, sont autant de domaines susceptibles de nourrir les questions associées à l’exploration des temporalités des territoires. Le projet "Représentation dynamique des temporalités des territoires" se veut un état des lieux de différents développements et solutions pour analyser et rendre compte des temporalités des territoires. Cet état des lieux est à entrées multiples, interrogeant à la fois des choix amont (modélisation) et des choix proprement liés à la question de la représentation. Le projet débouche sur un ensemble de résultats dont certains sont mis en ligne sur le site: http://www.map.cnrs.fr/jyb/puca/- Une grille de lecture de la collection d'applications analysée (voir onglet "47 applications"), grille où sont combinés des indicateurs généraux sur par exmeple le type de service rendu ou le type de dynamique spatiale analysée, et des indicateurs plus spécifiques au traitement des dimensions spatiales et temporelles. Cette grille est mise en place sur 47 applications identifiées et analysées,- Des visualisations récapitulatives conçues comme outils d'analyse comparative de la collection,- Une bibliographie structurée en relation avec la grille de lecture

Vandalism : a crime of place?

Vandalism is a problem for many communities across Scotland negatively affecting the lives of people who live in them. Whilst there has been recent research into the broad phenomena of anti-social behaviour, there has been little recent research into the specific phenomena of vandalism. In particular, little is understood about why vandalism often persistently re-occurs year in year out in particular locations. Wider research into crime and place suggests that, opportunities to commit crime, levels of relative deprivation, and the capacity or belief that a community can work together (collective efficacy) may be relevant factors. Other theories suggest some areas may act as crime attractors or be more criminogenic than others. There is a strong need for a better understanding of why certain places experience persistent vandalism and others do not. This thesis seeks to redress that gap by suggesting that to understand the nature of vandalism it is best understood as a crime of place rather than property. By drawing on theoretical and methodological approaches from both criminology and geography the thesis explores whether some areas experience high and low concentrations of vandalism year on year; if patterns change over time and whether areas with differing levels of vandalism share characteristics. Exploring issues related to crime and place presents specific methodological challenges. In criminology there has been much debate about whether it is best to consider crime and place processes at the micro or macro level. This thesis contributes to this debate by contending that it is necessary to employ a multi-method approach which integrates both micro and macro levels of investigation to properly understand crime and place. The results presented here are based on secondary analysis of six years of recorded crime data on vandalism supplied by Lothian and Borders police covering the period 1 April 2004 to 31 March 2010 for a case study area within Edinburgh with a broad mix of socio-demographic contexts. The thesis investigates the value of taking an Exploratory Spatial Data Analysis approach combining GIS based Crime Mapping and LISA (Local Indicators of Spatial Autocorrelation) analysis with Group Trajectory Analysis. This is complimented by data acquired from holding focus groups with Police Officers responsible for neighbourhood policing who used shaded maps to aid discussion of characteristics of areas with high and low vandalism. Findings suggest there are distinct High, Low and Drifting areas of vandalism with particular characteristics influenced by crime attractors, routine activities, relative deprivation and collective efficacy. By using an innovative multi-method ESDA quantitative and qualitative approach, important insights into the nature of vandalism as a place crime are gained; using a multi-spatial and temporal approach was found to be crucial. Findings are somewhat confined as they relate to a single case study area and a small number of focus groups were undertaken only with police Officers and not other community actors which may limit generalisabily. These concerns are discussed along with recommendations for future policy on vandalism and theoretical and methodological approaches for researching crime and place