Analysis of land use/land cover spatio-temporal metrics and population dynamics for urban growth characterization

[EN] Promoting sustainable urbanization and limiting land consumption is a local and regional priority policy target in Europe. Monitoring and quantifying urban growth supports decision-making processes for the prevention of ecological and socio-economic consequences. In this work, we present a methodology based on spatio-temporal metrics and a new index (PUGI), that quantifies the inequality of growth between population and urban areas, to analyze and compare urban growth patterns at different levels. We computed an exhaustive set of spatio-temporal metrics at local level in a testing sample of six urban areas from the Urban Atlas database, then un-correlated metrics were selected and the data were interpreted at various levels. Results allow for a differentiation of growing patterns, discriminating between compact and sprawl trends. The index proposed complements the analysis by including demographic dynamics, being also useful for assessing the growing imbalance between the progression on residential areas and the population change at local level. The analysis at various levels contributes to a better understanding of urban growth patterns and its relation to sustainable policies not only within urban areas, but also for the comparison across Europe.This research has been funded by the Spanish Ministerio de Economia y Competitividad and FEDER, in the framework of the project CGL2016-80705-R and the Fondo de Garantia Juvenil contract PEJ-2014-A-45358.Sapena Moll, M.; Ruiz Fernández, LÁ. (2019). Analysis of land use/land cover spatio-temporal metrics and population dynamics for urban growth characterization. Computers Environment and Urban Systems. 73:27-39. https://doi.org/10.1016/j.compenvurbsys.2018.08.001S27397

A Dynamic Spatio-Temporal Stochastic Modeling Approach of Emergency Calls in an Urban Context

Emergency calls are defined by an ever-expanding utilisation of information and sensing technology, leading to extensive volumes of spatio-temporal high-resolution data. The spatial and temporal character of the emergency calls is leveraged by authorities to allocate resources and infrastructure for an effective response, to identify high-risk event areas, and to develop contingency strategies. In this context, the spatio-temporal analysis of emergency calls is crucial to understanding and mitigating distress situations. However, modelling and predicting crime-related emergency calls remain challenging due to their heterogeneous and dynamic nature with complex underlying processes. In this context, we propose a modelling strategy that accounts for the intrinsic complex space–time dynamics of some crime data on cities by handling complex advection, diffusion, relocation, and volatility processes. This study presents a predictive framework capable of assimilating data and providing confidence estimates on the predictions. By analysing the dynamics of the weekly number of emergency calls in Valencia, Spain, for ten years (2010–2020), we aim to understand and forecast the spatio-temporal behaviour of emergency calls in an urban environment. We include putative geographical variables, as well as distances to relevant city landmarks, into the spatio-temporal point process modelling framework to measure the effect deterministic components exert on the intensity of emergency calls in Valencia. Our results show how landmarks attract or repel offenders and act as proxies to identify areas with high or low emergency calls. We are also able to estimate the weekly average growth and decay in space and time of the emergency calls. Our proposal is intended to guide mitigation strategies and policy

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

A scalable analytical framework for spatio-temporal analysis of neighborhood change: A sequence analysis approach

© Springer Nature Switzerland AG 2020. Spatio-temporal changes reflect the complexity and evolution of demographic and socio-economic processes. Changes in the spatial distribution of population and consumer demand at urban and rural areas are expected to trigger changes in future housing and infrastructure needs. This paper presents a scalable analytical framework for understanding spatio-temporal population change, using a sequence analysis approach. This paper uses gridded cell Census data for Great Britain from 1971 to 2011 with 10-year intervals, creating neighborhood typologies for each Census year. These typologies are then used to analyze transitions of grid cells between different types of neighborhoods and define representative trajectories of neighborhood change. The results reveal seven prevalent trajectories of neighborhood change across Great Britain, identifying neighborhoods which have experienced stable, upward and downward pathways through the national socioeconomic hierarchy over the last four decades

Introduction: Urban revolutions in the age of global urbanism

This special issue, papers presented at an Urban Studies Foundation-funded conference in Jakarta (March 2011), examines the current ‘urban century’ in terms of three revolutions. Revolutions from above index the logics and norms of mainstream global urbanism, particularly the form they have taken as policymakers work with municipal officials worldwide to organise urban development around neoliberal norms. Revolutions from below refer to the multifaceted contestations of global urbanism that take place in and around cities, ranging from urban street demonstrations and occupations (such as those riveting the world in early 2011 when these papers were written) to the quotidian actions of those pursuing politics and livelihoods that subvert the norms of mainstream global urbanism. It also highlights conceptual revolutions, referencing the ongoing challenge of reconceptualising urban theory from the South – not simply as a hemispheric location or geopolitical category but an epistemological stance, staged from many different locations but always fraught with the differentials of power and the weight of historical geographies. Drawing on the insights of scholars writing from, and not just about, such locations, a further iteration in this ‘southern’ turn of urban theorising is proposed. This spatio-temporal conjunctural approach emphasises how the specificity of cities – their existence as entities that are at once singular and universal – emerges from spatio-temporal dynamics, connectivities and horizontal and vertical relations. Practically, such scholarship entails taking the field seriously through collaborative work that is multi-sited, engages people along the spectrum of academics and activists, and is presented before and scrutinised by multiple publics

Monitoring land use changes using geo-information : possibilities, methods and adapted techniques

Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets

Advancing PSS with complex urban systems sciences and scalable spatio-temporal models

Planning Support System (PSS) with a core of dynamic spatio-temporal model has been developed as analytical and information tools to aid and inform urban planning processes. However, scholarly communities identify that PSS has yet been popularized in planning practices, and not fully capable of meeting the challenge of understanding complex urban environments. I am dedicated to investigate and break through the bottlenecks of PSS with my experiences with University of Illinois Landuse Evolution and Impact Assessment Model (LEAM) PSS, which exemplify a PSS that that aid the process of collaboratively building spatio-temporal scenario models and transferring the knowledge to planning practitioners. I explore the future applications of PSS including Smart Cities, sentience, resilience, and environmental planning processes and their role in improving PSS usefulness in the practice of planning. PSS improvements will be presented in terms of multi-directional spatio-temporal processes and scenario planning. Moreover, I will address the process of transferring knowledge to users on model validity and ‘goodness-of-fit’ in real world planning applications. Beyond the traditional theoretical framework of PSS, the emerging Complex Urban System Sciences (CUS) challenge the core assumptions of spatial models of PSS, and pose opportunities for updating current PSS approaches into scalable spatio-temporal model that adheres to CUS principles. I will analyze this potential infusion by examining next generation PSSs within a framework of current CUS theories and advancement in statistical and computational methods. Case studies involved in my dissertation include LEAM PSS’ applications in McHenry County (IL), Peoria (IL), Chicago (IL), and St. Louis (MO). The final part of this dissertation highlights my contributions to the existing CUS theories. I will demonstrates how evidence from empirical applications can contribute to CUS theory itself. I will show how CUS can challenge the core assumptions of “distance to CBD” models that economists use to characterize urban structure and land-use