Integrating spatial and temporal approaches for explaining bicycle crashes in high-risk areas in Antwerp (Belgium)

The majority of bicycle crash studies aim at determining risk factors and estimating crash risks by employing statistics. Accordingly, the goal of this paper is to evaluate bicycle-motor vehicle crashes by using spatial and temporal approaches to statistical data. The spatial approach (a weighted kernel density estimation approach) preliminarily estimates crash risks at the macro level, thereby avoiding the expensive work of collecting traffic counts; meanwhile, the temporal approach (negative binomial regression approach) focuses on crash data that occurred on urban arterials and includes traffic exposure at the micro level. The crash risk and risk factors of arterial roads associated with bicycle facilities and road environments were assessed using a database built from field surveys and five government agencies. This study analysed 4120 geocoded bicycle crashes in the city of Antwerp (CA, Belgium). The data sets covered five years (2014 to 2018), including all bicycle-motorized vehicle (BMV) crashes from police reports. Urban arterials were highlighted as high-risk areas through the spatial approach. This was as expected given that, due to heavy traffic and limited road space, bicycle facilities on arterial roads face many design problems. Through spatial and temporal approaches, the environmental characteristics of bicycle crashes on arterial roads were analysed at the micro level. Finally, this paper provides an insight that can be used by both the geography and transport fields to improve cycling safety on urban arterial roads

Dasymetric modelling of population dynamics in urban areas [Dasimetrično modeliranje dinamike prebivalstva na urbanih območjih]

Solving the problem of publicly available census data disaggregation has preoccupied numerous researchers intensively A noteworthy advance in the methodology was made thanks to the contemporary storage and presentation of spatial and socio-economic data in the GIS environment. It is also important that a large number of auxiliary databases (satellite images, theme layers pertaining to land use and land cover, etc.) are publicly available and are periodically supplemented at increasingly shorter time intervals. Soil sealing databases are another class of auxiliary databases that pertain to land areas which have, due to anthropogenic influences, become a water-impermeable layer and indicate the level of spatial development and spatial contents that correlate to the population distribution. The soil sealing database can be a useful tool for dasymetric mapping of population when combined with town planning documentation that describes land use and height of residential buildings. The results of such mapping can help monitor the spatio-temporal dynamics of population trends in periods between two censuses. This study presents a methodology in which a soil-sealing database is combined with auxiliary data in a test area covered by the Master Plan of the Belgrade City, with census data from the year 2002 and the results of the year 2011. The results of the model validation indicate application of the proposed methodology in highly urbanised areas

An Approach to Developing a Spatio-Temporal Composite Measure of Climate Change-Related Human Health Impacts in Urban Environments

Introduction: Rapid population growth along with an increase in the frequency and intensity of climate change-related impacts in costal urban environments emphasize the need for the development of new tools to help disaster planners and policy makers select and prioritize mitigation and adaptation measures. Using the concept of the resilience of a community, which is a measure of how rapidly the community can recover to its previous level of functionality following a disruptive event is still a relatively new concept for many engineers, planners and policy makers, but is becoming recognized as an increasingly important and some would argue, essential component for the development and subsequent assessment of adaptation plans being considered for communities at risk of climate change-related events. The holistic approach which is the cornerstone of resilience is designed to integrate physical, economic, health, social and organizational impacts of climate change in urban environments. This research presents a methodology for the development of a quantitative spatial and temporal composite measure for assessing climate change-related health impacts in urban environments. Methods: The proposed method is capable of considering spatial and temporal data from multiple inputs, relating to both physical and social parameters. This approach uses inputs such as the total population density and densities of various demographics, burden of diseases conditions, flood inundation mapping, and land use change for both historical and current conditions. The research has demonstrated that the methodology presented generates sufficiently accurate information to be useful for planning adaptive strategies. To assemble all inputs into a single measure of health impacts, a weighting system was assigned to apply various priorities to the spatio-temporal data sources. Weights may be varied to assess how they impact the final results. Finally, using spatio-temporal extrapolation methods the future behavior of the same key spatial variables can be projected. Although this method was developed for application to any coastal mega-city, this thesis demonstrates the results obtained for Metro Vancouver, British Columbia, Canada. The data was collected for the years 1981, 1986, 1991, 1996, 2001, 2006 and 2011, as information was readily available for these years. Fine resolution spatial data for these years was used in order to give a dynamic simulation of possible health impacts for future projections. Linear and auto-regressive spatio-temporal extrapolations were used for projecting a 2050’s Metro Vancouver health impact map (HIM). Conclusion: Results of this work show that the approach provides a more fully integrated view of the resilience of the city which incorporates aspects of population health. The approach would be useful in the development of more targeted adaptation and risk reduction strategies at a local level. In addition, this methodology can be used to generate inputs for further resilience simulations. The overall value of this approach is that it allows for a more integrated assessment of the city vulnerability and could lead to more effective adaptive strategies

Integrating population dynamics into mapping human exposure to seismic hazard

Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making

The Long-term Impact of Land Use Land Cover Change on Urban Climate: Evidence from the Phoenix Metropolitan Area, Arizona

abstract: This dissertation research studies long-term spatio-temporal patterns of surface urban heat island (SUHI) intensity, urban evapotranspiration (ET), and urban outdoor water use (OWU) using Phoenix metropolitan area (PMA), Arizona as the case study. This dissertation is composed of three chapters. The first chapter evaluates the SUHI intensity for PMA using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product and a time-series trend analysis to discover areas that experienced significant changes of SUHI intensity between 2000 and 2017. The heating and cooling effects of different urban land use land cover (LULC) types was also examined using classified Landsat satellite images. The second chapter is focused on urban ET and the impacts of urban LULC change on ET. An empirical model of urban ET for PMA was built using flux tower data and MODIS land products using multivariate regression analysis. A time-series trend analysis was then performed to discover areas in PMA that experienced significant changes of ET between 2001 and 2015. The impact of urban LULC change on ET was examined using classified LULC maps. The third chapter models urban OWU in PMA using a surface energy balance model named METRIC (Mapping Evapotranspiration at high spatial Resolution with Internalized Calibration) and time-series Landsat Thematic Mapper 5 imagery for 2010. The relationship between urban LULC types and OWU was examined with the use of very high-resolution land cover classification data generated from the National Agriculture Imagery Program (NAIP) imagery and regression analysis. Socio-demographic variables were selected from census data at the census track level and analyzed against OWU to study their relationship using correlation analysis. This dissertation makes significant contributions and expands the knowledge of long-term urban climate dynamics for PMA and the influence of urban expansion and LULC change on regional climate. Research findings and results can be used to provide constructive suggestions to urban planners, decision-makers, and city managers to formulate new policies and regulations when planning new constructions for the purpose of sustainable development for a desert city.Dissertation/ThesisDoctoral Dissertation Geography 201

Defining the Peri-Urban: A Multidimensional Characterization of Spatio-Temporal Land Use along an Urban−Rural Gradient in Dar es Salaam, Tanzania

Highly dynamic peri-urban areas, particularly in the Global South, face many challenges including a lack of infrastructure, ownership conflicts, land degradation, and sustainable food production. This study aims to assess spatial land use characteristics and processes in peri-urban areas using the case of Dar es Salaam, Tanzania. A mixed-method approach was applied, consisting of expert interviews and spatial data analysis, on a local scale along an urban–rural gradient. Expert interviews were conducted during a field study and analyzed regarding the characteristics and processes of peri-urban land development. A GIS-based analysis of land use patterns was applied using satellite imagery and Open Street Map data to identify a number of variables, such as building density and proximity to environmental features. Results show specific patterns of land use indicators, which can be decreasing (e.g., house density), increasing (e.g., tree coverage), static (e.g., house size), or randomly distributed (e.g., distance to river), along a peri-urban gradient. Key findings identify lack of service structures and access to public transport as major challenges for the population of peri-urban areas. The combination of qualitative expert interviews and metrics-based quantitative spatial pattern analysis contributes to improved understanding of the patterns and processes in peri-urban land use changes.Peer Reviewe

Image Based Surface Temperature Extraction and Trend Detection in an Urban Area of West Bengal, India

Rapid urbanization and change of landuse/landcover results in changes of the thermal spectrum of a city even in small cities like English Bazaar Municipality (EBM) of Malda district. Monitoring the spatio-temporal surface temperature patterns is important, therefore, the present paper attempts to extract spatio-temporal surface temperature from thermal band of Landsat imageries and tries to validate it with factor based Land Surface Temperature (LST) models constructed based on six proxy temperature variables for selected time periods (1991, 2010 and 2014). Seasonal variation of temperature is also analyzed from the LST models over different time phases. Landsat TIRS based LST shows that in winter season, the minimum and maximum LST have raised up 2.32°C and 3.09°C in last 25 years. In pre monsoon season, the increase is much higher (2.80°C and 6.74°C) than in the winter period during the same time frame. In post monsoon season, exceptional situation happened due to high moisture availability caused by previous monsoon rainfall spell. Trend analysis revealed that the LST has been rising over time. Expansion and intensification of built up land as well as changing thermal properties of the urban heartland and rimland strongly control LST. Factor based surface temperature models have been prepared for the same period of times as done in case of LST modeling. In all seasons and selected time phases, correlation coefficient values between the extracted spatial LST model and factor based surface temperature model varies from 0.575 to 0.713 and these values are significant at 99% confidence level. So, thinking over ecological growth of urban is highly required for making the environment ambient for living

Developing a flexible framework for spatiotemporal population modeling

This article proposes a general framework for modeling population distributions in space and time. This is particularly pertinent to a growing range of applications that require spatiotemporal specificity; for example, to inform planning of emergency response to hazards. Following a review of attempts to construct time-specific representations of population, we identify the importance of assembling an underlying data model at the highest resolution in each of the spatial, temporal, and attribute domains. This model can then be interrogated at any required intersection of these domains. We argue that such an approach is necessary to moderate the effects of what we term the modifiable spatiotemporal unit problem in which even detailed spatial data might be inadequate to support time-sensitive analyses. We present an initial implementation of the framework for a case study of Southampton, United Kingdom, using bespoke software (SurfaceBuilder247). We demonstrate the generation of spatial population distributions for multiple reference times using currently available data sources. The article concludes by setting out key research areas including the enhancement and validation of spatiotemporal population methods and model

Key drivers of stream water quality along an urban-rural transition : a watershed-scale perspective

Detecting trends in stream water quality is one of the key objectives of environmental monitoring. Identifying factors controlling stream water pollutants is challenging due to the diversity of potential sources, pathways, and processes. Natural processes regulating the water quality of a watershed are often affected by anthropogenic activities, resulting in the redistribution of runoff from base flow to storm flow and the introduction of new pollutant sources. Despite the observed consequences of urbanization, a lack of understanding of the factors simultaneously controlling water quality is among the biggest gaps in our current knowledge of hydrogeography. Moreover, prevailing discussions of land-cover effects often neglect the potential contribution of other factors, such as surficial deposits, in stream water concentrations. This thesis aims to 1) examine the most influential watershed properties determining spatial variation in stream water quality; 2) identify key water quality and watershed variables controlling stream biotic responses (i.e. diatom community composition); 3) investigate the effects of multiscale temporal variation on urban runoff in cold climatic regions; and 4) evaluate whether advanced statistical methods are applicable in hydrogeographical modeling of small watersheds. To fulfill these objectives, spatial watershed-scale analyses were conducted using modern non-parametric approaches and theory-driven methods such as structural equation modeling. This thesis is based on unique data sets of both multibasin and multiyear sampling and spatial data from the Helsinki region, southern Finland. A combination of GIS-based approaches and statistical analyses revealed significant links and novel insights into complex relationships between water quality and spatial biogeophysical properties of the surrounding landscape. The importance of land cover was emphasized throughout the thesis. Under base flow conditions the significance of soil type was mainly controlled by land cover. Further, this thesis demonstrates how land cover and stream water quality strongly determine the spatial assemblages of aquatic biota, as elevated pollutant levels were linked to decreased species richness and dominance of more tolerant species of diatom taxa. From a temporal perspective, the results suggest that urban runoff pollution is a chronic phenomenon, and is controlled by both runoff volume (summer) and pollutant sources (winter). Both the divergent temporal behavior and dominant role of diffuse pollution sources indicated challenges for stream water management practices. Based on the observed substance levels, year-round runoff treatment in urban areas is highly recommended. Finally, this thesis increases our knowledge of stream water quality variation in space and time. In this thesis, key local phenomena in contemporary hydrogeography were identified with a spatial modeling framework. The inclusion of indirect effects into the models improved our understanding of these systems, thus emphasizing the importance of simultaneously studying multiple concurrent processes.Yksi ympäristötutkimuksen tärkeimmistä tavoitteista on tunnistaa virtavesien, kuten purojen ja jokien laadun vaihtelu. Tärkeimpien vedenlaatua säätelevien ympäristötekijöiden tunnistaminen on kuitenkin vaikeaa aineiden lukuisten lähteiden, kulkeutumisreittien ja prosessien takia. Ihmistoiminta vaikuttaa myös luonnollisiin vedenlaatua sääteleviin tekijöihin valuma-alueella, muuttaen virtaamaa pohjavalunnasta enemmän sateiden yhteyteen, ja tuottaen uusia haitta-ainelähteitä. Vaikka kaupungistumisen vaikutukset ympäristöön ovat kiistattomia, emme juurikaan tunne eri ympäristötekijöiden yhteisvaikutusta vaikutusta vedenlaatuun. On myös huomionarvoista, että tieteellinen keskustelu maanpeitteen vaikutuksista vedenlaatuun poissulkee usein muiden, kuten maaperätekijöiden vaikutukset virtavesien pitoisuuksiin. Tutkimuksen tavoitteena on 1) tunnistaa virtavesien laadun alueellista vaihtelua vahvimmin säätelevät tekijät 2) tunnistaa tärkeimmät elollisia vedenlaatuindikaattoreita säätelevät valuma-alue- ja vedenlaatutekijät, 3) tutkia kylmän ilmaston kaupungin virtavesien (huleveden) ajallista vaihtelua ja 4) arvioida, voiko nykyaikaisia tilastollisia menetelmiä soveltaa pienten valuma-alueiden alueellisessa mallinnuksessa. Tutkimus perustuu moderneihin ja teorialähtöisiin menetelmiin, kuten rakenneyhtälömalliin. Työssä sovelletaan sekä alueellisesti laajaa että ajallisesti kattavaa mittausaineistoa Helsingin seudulta, Etelä-Suomesta. Työssä käytetyt paikkatietopohjaiset lähestymistavat ja tilastolliset analyysit tuottivat uutta tietoa tärkeistä vedenlaadun ja ympäristötekijöiden monimutkaisista suhteista. Maanpeitteen tärkeys vedenlaatua säätelevänä tekijänä korostui läpi tutkielman. Sateettomana aikana eli pohjavaluntatilanteissa maaperän tärkeys vedenlaadulle oli vahvasti maanpeitteen säätelemä. Tulokset osoittavat, miten sekä maanpeite että vedenlaatu molemmat vaikuttavat virtavesien eliölajirunsauteen. Vesien korkeat ainepitoisuudet olivat suoraan yhteydessä pienempään lajirunsauteen ja enemmän tolerantteihin lajeihin. Ajallisesti tarkasteltuna kaupunkivesien korkeat pitoisuudet ovat jatkuva ongelma viitaten krooniseen ympäristöongelmaan. Pitoisuuksien ajallinen vaihtelu on kesäaikaan vahvasti virtaaman ja talviaikaan ainelähteiden säätelemä. Sekä virtavesien laadun voimakas ajallinen vaihtelu, että hajakuormituksen suuri merkitys ovat merkittäviä haasteita virtavesien kestävälle hallinnalle. Tulosten perusteella kaupunkialueiden hulevedet tarvitsisivat ympärivuotista käsittelyä ennen niiden purkamista muihin vesiin. Lopuksi, työ lisäsi ymmärrystämme virtavesien laadun alueellisesta ja ajallisesta vaihtelusta. Tutkimuksessa tunnistettiin tärkeimmät paikalliset hydrogeografiset ilmiöt soveltaen alueellisen mallintamisen menetelmiä. Epäsuorien vaikutusten tarkastelu lisäsi ymmärrystämme näistä monimutkaisista systeemeistä, korostaen sitä, miten tärkeää on tarkastella useita prosesseja samanaikaisesti