The Life and Afterlife of Gay Neighborhoods

Journal Information
ISSN / EISSN : 2365-757X / 2365-7588
Current Publisher: Springer Science and Business Media LLC (10.1007)

Latest articles in this journal

, Jason Sauer
The Life and Afterlife of Gay Neighborhoods pp 47-66; doi:10.1007/978-3-030-63131-4_4

Assessing present social and biophysical conditions of communities that are at risk of injury due to extreme weather events is an important component of creating future visions of resilience. Spatial patterns of vulnerability to extreme events are manifestations of structural injustice that leave their mark on the built environment and in socio-spatial segregation patterns. Socio-spatial inequity often arises from development practices that favor particular racial and ethnic social groups over others. These segregation patterns are aligned with patterns of exposure to pollution, extreme weather events, and other types of environmental hazards. Spatial vulnerability assessments can be powerful tools for prioritizing where and how cities should make investments for mitigating the impacts of extreme events, and can provide an entry point for asking more fundamental questions about the processes that produce patterns of climate inequity, as well as how to avoid reproducing such processes in the future. Maps express uneven distributions of risk and manifestations of structural inequality in social–ecological–technological systems (SETS). They enable communities to visualize distributional injustice, consider ways in distributions that may be misaligned with cultural values, and develop adaptive practices toward climate justice. Here, we demonstrate approaches for assessing vulnerability to extreme flooding and heat, and show how vulnerability distributions are embedded in landscape patterns that produce uneven risk.
, Marta Berbés-Blázquez, Lelani M. Mannetti, Nancy B. Grimm, David M. Iwaniec, Tischa A. Muñoz-Erickson
The Life and Afterlife of Gay Neighborhoods pp 99-111; doi:10.1007/978-3-030-63131-4_7

Participatory scenario visioning aims to expose, integrate, and reconcile perspectives and expectations about a sustainable, resilient future from a variety of actors and stakeholders. This chapter considers the settings in which transdisciplinary participatory visioning takes place, highlighting lessons learned from the Urban Resilience to Extremes Sustainability Research Network (UREx SRN). It reflects on the benefits of engaging in the co-production process and the challenges that must be considered amid this process.
, David M. Iwaniec, Zoé A. Hamstead, Marta Berbés-Blázquez, Elizabeth M. Cook, Tischa A. Muñoz-Erickson, Lelani Mannetti, Nancy Grimm
The Life and Afterlife of Gay Neighborhoods pp 173-186; doi:10.1007/978-3-030-63131-4_12

A fundamental systems approach is essential to advancing our understanding of how to address critical challenges caused by the intersection of urbanization and climate change. The social–ecological–technological systems (SETS) conceptual framework brings forward a systems perspective that considers the reality of cities as complex systems and provides a baseline for developing a science of, and practice for, cities. Given the urgency of issues we collectively face to improve livability, justice, sustainability, and resilience in cities, bringing a systems approach to resilience planning and policymaking is critical, as is development of positive visions and scenarios that can provide more realistic and systemic solutions. We provide a vision for more resilient urban futures that learns from coproduced scenario development work in nine US and Latin American cities in the URExSRN. We find that developing an urban systems science that can provide actionable knowledge for decision-making is an emerging, and much needed, transdisciplinary research agenda. It will require true boundary-crossing to bring the knowledge, skills, tools, and ideas together in ways that can help achieve the normative goals and visions we have for our shared urban future.
, Marta Berbés-Blázquez, Elizabeth M. Cook, Nancy B. Grimm, Lelani M. Mannetti, Timon McPhearson, Tischa A. Muñoz-Erickson
The Life and Afterlife of Gay Neighborhoods pp 85-97; doi:10.1007/978-3-030-63131-4_6

We describe the rationale and framework for developing scenarios of positive urban futures. The scenario framework is conducted in participatory workshop settings and composed of three distinct scenario approaches that are used to (1) explore potential outcomes of existing planning goals (strategic scenarios), (2) articulate visions that address pressing resilience challenges (adaptive scenarios), and (3) envision radical departures from the status quo in the pursuit of sustainability and equity (transformative scenarios). A series of creative and analytical processes are used to engage the community in imagining, articulating, and scrutinizing visions and pathways of positive futures. The approach offers an alternative and complement to traditional forecasting techniques by applying inspirational stories to resilience research and practice.
, Nancy B. Grimm, Elizabeth M. Cook, David M. Iwaniec, Tischa A. Muñoz-Erickson, Vivian Hobbins, Darin Wahl
The Life and Afterlife of Gay Neighborhoods pp 113-127; doi:10.1007/978-3-030-63131-4_8

In the absence of strong international agreements, many municipal governments are leading efforts to build resilience to climate change in general and to extreme weather events in particular. However, it is notoriously difficult to guide and activate processes of change in complex adaptive systems such as cities. Participatory scenario planning with city professionals and members of civil society provides an opportunity to coproduce positive visions of the future. Yet, not all visions are created equal. In this chapter, we introduce the Resilience, Equity, and Sustainability Qualitative (RESQ) assessment tool that we have applied to compare positive scenario visions for cities in the USA and Latin America. We use the tool to examine the visions of the two desert cities in the UrbanResilience to Extreme Events Sustainability Research Network (UREx SRN), which are Hermosillo (Mexico) and Phoenix (United States).
The Life and Afterlife of Gay Neighborhoods pp 197-211; doi:10.1007/978-981-15-8983-6_13

The resilience concept has become more significant in the past decade as a means for understanding how cities prepare and plan for, absorb, recover from, and more successfully adapt to adverse events. Definitional differences—resilience as an outcome or end-point versus resilience as a process of building capacity—dominate the literature. Lagging behind are efforts to systematically measure resilience to produce a baseline and subsequent monitoring, in order to gauge what, where, and how intervention or mitigation strategies would strengthen or weaken urban resilience. The chapter reviews research and practitioner attempts to develop urban informatics for resilience and provides selected case studies of cities as exemplars.
, Takanori Sakai, Fang Zhao, Linlin You, Peiyu Jing, Lynette Cheah, Christopher Zegras, Moshe Ben-Akiva
The Life and Afterlife of Gay Neighborhoods pp 171-195; doi:10.1007/978-981-15-8983-6_12

Advancements in information and communication technologies (ICT) and the advent of novel mobility solutions have brought about drastic changes in the urban mobility environment. Pervasive ICT devices acquire new sources of data that can inform detailed transportation simulation models, and are useful in analyzing new policies and technologies. In this context, we developed software laboratories that leverage the latest technological developments and enhance freight research. Future mobility sensing (FMS) is a data-collection platform that integrates tracking devices and mobile apps, a backend with machine-learning technologies and user interfaces to deliver highly accurate and detailed mobility data. The second platform, SimMobility, is an open-source, agent-based urban simulation platform which replicates urban passenger and goods movements in a fully disaggregated manner. The two platforms have been used jointly to advance the state of the art in behavioral modeling for passenger and goods movements. In this chapter, we review recent developments in freight-transportation data-collection techniques, including contributions to transportation modeling, and state-of-the-art transportation models. We then introduce FMS and SimMobility and demonstrate a coordinated application using three examples. Lastly, we highlight potential innovations and future challenges in these research domains.
Pierre Melikov, Jeremy A. Kho, Vincent Fighiera, Fahad Alhasoun, Jorge Audiffred, José L. Mateos,
The Life and Afterlife of Gay Neighborhoods pp 153-170; doi:10.1007/978-981-15-8983-6_11

Seamless access to destinations of value such as workplaces, schools, parks or hospitals, influences the quality of life of people all over the world. The first step to planning and improving proximity to services is to estimate the number of trips being made from different parts of a city. A challenge has been representative data available for that purpose. Relying on expensive and infrequently collected travel surveys for modeling trip distributions to facilities has slowed down the decision-making process. The growing abundance of data already collected, if analyzed with the right methods, can help us with planning and understanding cities. In this chapter, we examine human mobility patterns extracted from data passively collected. We present results on the use of points of interest (POIs) registered on Google Places to approximate trip attraction in a city. We compare the result of trip distribution models that utilize only POIs with those utilizing conventional data sets, based on surveys. We show that an extended radiation model provides very good estimates when compared with the official origin–destination matrices from the latest census in Mexico City.
, Prince M. Amegbor, Zhaoxi Zhang, Tzu-Hsin Karen Chen, Maria B. Poulsen, Ole Hertel, Torben Sigsgaard, Henriette T. Horsdal, Carsten B. Pedersen, Jibran Khan
The Life and Afterlife of Gay Neighborhoods pp 259-280; doi:10.1007/978-981-15-8983-6_17

This chapter explores how the Internet of Things and the utilization of cutting-edge information technology are shaping global research and discourse on the health and wellbeing of urban populations. The chapter begins with a review of smart cities and health and then delves into the types of data available to researchers. The chapter then discusses innovative methods and techniques, such as machine learning, personalized sensing, and tracking, that researchers use to examine the health and wellbeing of urban populations. The applications of these data, methods, and techniques are then illustrated taking examples from BERTHA (Big Data Centre for Environment and Health) based at Aarhus University, Denmark. The chapter concludes with a discussion on issues of ethics, privacy, and confidentiality surrounding the use of sensitive and personalized data and tracking or sensing individuals across time and urban space.
, Jianwei Wu
The Life and Afterlife of Gay Neighborhoods pp 367-400; doi:10.1007/978-981-15-8983-6_22

In this chapter, we present an advanced machine learning strategy to detect objects and characterize traffic dynamics in complex urban areas by airborne LiDAR. Both static and dynamical properties of large-scale urban areas can be characterized in a highly automatic way. First, LiDAR point clouds are colorized by co-registration with images if available. After that, all data points are grid-fitted into the raster format in order to facilitate acquiring spatial context information per-pixel or per-point. Then, various spatial-statistical and spectral features can be extracted using a cuboid volumetric neighborhood. The most important features highlighted by the feature-relevance assessment, such as LiDAR intensity, NDVI, and planarity or covariance-based features, are selected to span the feature space for the AdaBoost classifier. Classification results as labeled points or pixels are acquired based on pre-selected training data for the objects of building, tree, vehicle, and natural ground. Based on the urban classification results, traffic-related vehicle motion can further be indicated and determined by analyzing and inverting the motion artifact model pertinent to airborne LiDAR. The performance of the developed strategy towards detecting various urban objects is extensively evaluated using both public ISPRS benchmarks and peculiar experimental datasets, which were acquired across European and Canadian downtown areas. Both semantic and geometric criteria are used to assess the experimental results at both per-pixel and per-object levels. In the datasets of typical city areas requiring co-registration of imagery and LiDAR point clouds a priori, the AdaBoost classifier achieves a detection accuracy of up to 90% for buildings, up to 72% for trees, and up to 80% for natural ground, while a low and robust false-positive rate is observed for all the test sites regardless of object class to be evaluated. Both theoretical and simulated studies for performance analysis show that the velocity estimation of fast-moving vehicles is promising and accurate, whereas slow-moving ones are hard to distinguish and yet estimated with acceptable velocity accuracy. Moreover, the point density of ALS data tends to be related to system performance. The velocity can be estimated with high accuracy for nearly all possible observation geometries except for those vehicles moving in or (quasi-)along the track. By comparative performance analysis of the test sites, the performance and consistent reliability of the developed strategy for the detection and characterization of urban objects and traffic dynamics from airborne LiDAR data based on selected features was validated and achieved.
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