Urban Flight Research Articles

Flight test for the noise source modeling of the optionally piloted personal air vehicle

An acoustic flight test is carried out in order to obtain the noise hemisphere of the optionally piloted personal air vehicle (OPPAV). The OPPAV is one-seater, research urban air mobility (UAM) being developed by Korea Aerospace Research Institute. Noise radiated from the aircraft is measured using a microphone array consisting of a total of 78 microphones. Flight logs such as the aircraft position, velocity, and attitude are recorded synchronously with the acoustic signals. Measured acoustic signals are dedopplerized and divided into a number of segments. Noise source model for the OPPAV flight is constructed using these segments. The noise source model will be used for the assessment of noise annoyance during urban flight of the UAMs.

Prosperity in progress: a new look at archetypes of successful community development

This study navigates the terrain of community development in metropolitan areas across the United States (US), spotlighting the interplay between stakeholder engagement, development success, and distinct types of community development characteristics. While urban centers in US cities experienced disinvestment and urban flight for more than 5 decades, they now experience renewed interest amidst the complexities of rampant urbanization. Gentrification and displacement are some of the critical consequences of urban re-development, which warrants the exploration of the success metrics that turn disinvested communities into thriving ones. Methodologically, archetype analysis is employed to examine 73 case studies reported by the United States Department of Housing & Urban Development (HUD) as examples of successful development. The case studies span 37 US states and 67 cities. The analysis utilizes the Distressed Communities Index (DCI) as a supporting metric and offers an intermediate level of abstraction between a case-by-case analysis of successful development strategies and a generalized approach that assumes that one strategy fits all. Instead, the analysis identifies four distinct types of successful community development archetypes based on five relevant characteristics that emerged from our analysis: (1) public investments, (2) private investment (3) development plans, (4) stakeholder engagement, and (5) the DCI. The four identified archetypes represent unique Community Development Success pathways with specific development characteristics. Understanding the diversity reflected in these distinct archetypes is crucial for policymakers and stakeholders seeking to address the specific needs and challenges of each development success type. This can inform more targeted policy initiatives for fostering prosperity and vitality in diverse communities across the US and beyond.

Urban flight: A short‐term phenomenon or long‐term trend?

AbstractWe investigate whether the urban flight from more to less dense locations identified by previous housing studies for the early COVID period is a temporary, pandemic‐induced phenomenon, or long‐term trend. We focus on the period of 2017–2022, 14,961 single‐family home transactions from Southwestern Ontario, and three housing market metrics. Our results for sales price in the early pandemic periods are in line with previous studies. However, our results for sales price in the last pandemic phase (2022), marketing time, and visit activity suggest that the urban flight was a temporary phenomenon characteristic of the early COVID phases.

3D-flight route optimization for air-taxis in urban areas with Evolutionary Algorithms and GIS

Electric aviation is being developed as a new mode of transportation for the urban areas of the future. This requires urban air space management that considers these aircraft. Flight routes need to be determined that avoid no-fly areas, and minimize flight time, energy consumption and added noise. Yet, no method currently exists for optimizing urban flight routes under multiple conflicting objectives while avoiding three-dimensional restricted areas. In our work, this research gap is overcome by optimizing 3D-routes with the multi-criteria optimization technique called Non-dominated Sorting Genetic Algorithm II. We propose a novel procedure in the optimization process to incorporate geographical representations. Furthermore, we include a seeding procedure for initializing the flight routes and repair methods for invalid flight routes that may arise during the optimization process. We apply the optimization to a case study in Manhattan (New York City) for two different aircraft types, the Lilium Jet (vectored thrust) and the EHANG 184 (wingless multicoptor), under three objectives concerning flight time, energy consumption and added noise. Compared to a least-distance path, flight routes were obtained with maximum improvements of 38% in added noise, 65% in flight time and 52% in energy consumption for the EHANG 184. For the Lilium jet, maximum improvements of 43% in added noise, 47% in flight time and 47% in energy consumption were obtained. Still, the obtained noise addition levels by the aircraft in New York City exceed 5 dB, which is considered as long-term noise annoyance. We illustrated that minimizing the added noise requires high search effort compared to the other two objectives. Upon further analysis of the optimization results, we conclude that the Lilium jet as representative of the eVTOL type vectored thrust is more sensitive to flight route changes than the multicoptor EHANG 184. This information may help in air taxi type choice for a certain region as well as in flight route planning.

Pandemic mobility, second homes and housing market change in a rural amenity area during COVID-19 – The Brecon Beacons National Park, Wales

The Covid-19 pandemic has been presented as a critical change driver for rural amenity areas, precipitating urban flight and a decentralisation of housing choice and investment. House prices in both near-urban and more distant rural markets saw considerable growth in 2020 and 2021, linked to a mix of second home investment, expanded demand for holiday letting, migration to exploit flexible-working opportunities, and homebuying for early retirement. These demand-side pressures, apparently accentuated by the pandemic, combine with supply-side constraints on development in rural areas (which can accommodate a limited amount of additional housing) to produce significant housing stress. However, processes affecting some areas, in different parts of the world, have arguably been generalised to all areas, and localised processes remain under-investigated. This monograph explores the experience of the Brecon Beacons National Park in Wales, UK – an amenity area with good connectivity to a number of major urban centres and therefore sources of extra-local housing demand. Focusing on second home buying, as a leading element of extra-local pressure in amenity areas, the monograph considers the particular circumstances of this area. It shows that a combination of amplified demand-side factors, linked to the pandemic, and heightened supply-side constraints, due to a phosphate crisis affecting the National Park’s major river catchments, requires a programme of actions that extends beyond the housing domain in order to resolve escalating housing market challenges and associated community and economic risks.

JUE Insight: Urban flight seeded the COVID-19 pandemic across the United States

We document large-scale urban flight in the United States during the COVID-19 pandemic. Regions that saw migrant influx experienced greater subsequent new COVID-19 cases, linking urban flight (as a disease vector) and coronavirus spread in destination areas. Urban residents fled to socially connected areas, consistent with the theory that individuals sheltered with friends and family, or in second homes. Populations that fled were disproportionately younger, whiter, and wealthier. The association between migration and subsequent new cases persists when instrumenting for migration with social networks.

Covid-19 impact on US housing markets: evidence from spatial regression models

ABSTRACT This paper empirically investigates the conventional wisdom that urban residents have reacted to the Covid-19 pandemic by fleeing city centres for the suburbs. A conventional panel model of US ZIP code-level data provides mixed evidence in support of a shifting housing preference for more space or neighbourhoods farther from the urban core. Regressions accounting for spatial dependence and spatial heterogeneity show strong support of an urban flight within metro areas, but this local phenomenon is uneven across broad regions of the United States. The finding of geographical disparity underscores both the local as well as the regional nature of housing market conditions.

Decentralized Multi-UAV Path Planning Based on Two-Layer Coordinative Framework for Formation Rendezvous

Unmanned aerial vehicle (UAV) formation rendezvous path planning problem is one of the important research topics in multiple UAV (multi-UAV) coordinated path planning. Aiming at solving low computational efficiency and poor scalability of the traditional multi-UAV path planning method, the decentralized multi-UAV path planning method suitable for obstacle environments is proposed. Firstly, the UAV rendezvous path planning problem with constraints such as the kinematics of UAVs and collision-free constraints is modeled as a non-convex optimal-control problem. To minimize formation rendezvous time and energy consumption, a two-layer coordinative framework is developed to solve this problem. In the coordination layer, relying only on the information of neighboring UAVs, each UAV in the decentralized communication graph negotiates the desired flight time using a consensus protocol to achieve coordination among UAVs. In the planning layer, the initial non-convex formation rendezvous path planning problem is decoupled into several sub-problems, which can be solved in parallel by path planners distributed on each UAV using sequential convex programming. Finally, numerical simulations are carried out to verify the effectiveness and scalability of the proposed method. The results show that this decentralized multi-UAV path planning method can handle the minimum-time rendezvous path planning problem and optimize the energy consumption in flight, and the computing time does not increase significantly with the enlargement of the UAV swarm. This decentralized framework scales well with the number of UAVs and can be applied for future urban flight and supplies delivery tasks.

Urban Flight and Rural Rights in a Pandemic: Exploring Narratives of Place, Displacement, and “the Right to Be Rural” in the Context of COVID-19

The COVID-19 pandemic has exacerbated many preexisting challenges facing rural communities and brought tensions in rural–urban relations closer to the surface. This article offers an explorative contribution to discussions in critical geography by comparing media narratives surrounding urban flight to rural places during the COVID-19 pandemic. Comparing field sites in rural Michigan (United States), Ontario (Canada), and the “Atlantic bubble” (Canada), we use an emerging theorization of the “right to be rural” to explore how urban flight and rural displacement are tied to concepts of community, identity, and safety. This approach is grounded in the political economy of rurality and emphasizes the power relations, inequalities, and historical contingencies that structure the experiences of full-time and part-time rural residents during the pandemic. Our exploratory discussion surfaces critical tensions in the geographically and socioeconomically uneven implications of the pandemic, including the “anxious economic acquiescence” experienced in many tourism-dependent rural regions and both the “hard” and “soft” ways in which rural regions responded to increased demands for access. We argue that the political economy of rural–urban relations is critical to understanding the social processes that will shape the “right to be rural” during and after COVID-19.

Urban Metric Maps for Small Unmanned Aircraft Systems Motion Planning

Low-altitude urban flight planning for small unmanned aircraft systems (UASs) accurate vehicle kinodynamics, environment maps, and risk models to assure that flight plans consider the urban landscape as well as airspace constraints. This paper presents a suite of motion planning metrics designed for small UAS urban flight and defines map-based and path-based metrics to holistically characterize motion plan quality. Proposed metrics are examined in the context of representative geometric, graph-based, and sampling-based motion planners applied to a multicopter small UAS. A novel multi-objective heuristic is proposed and applied for graph-based and sampling motion planners at four urban UAS flight altitude layers. Monte Carlo case studies in a New York City urban environment illustrate metric map properties and planner performance. Motion plans are evaluated as a function of planning algorithm, location, range, and flight altitude.

Spaces of well‐being and regional settlement: International migrants and the rural idyll

AbstractRegionalisation is a hallmark of Australia's approach to international migration, reflecting governments' growing concern with where new arrivals live. Residence in regional Australia is encouraged (mandated, for some visas) in response to urban population pressures alongside rural population and economic decline. Parallel to regionally focused visa schemes exists a pattern of voluntary urban‐to‐rural migration among some international migrants. Such secondary mobility counters the policy logic that international migrants only live outside cities when required to do so. This paper explores 18 African migrants' motivations for ‘urban flight’: Australian cities have failed to sustain their well‐being and they consider rural life a remedy. Their preference for rural locations is not purely instrumental, it is shaped by deep‐seated affective connections. Given the challenges of regional population retention, settlement policies should be recalibrated to support the aspirations of international migrants who feel an affinity for rural places, rather than compelling the rural settlement of others who do not.

Revealing two dynamic dengue epidemic clusters in Thailand

BackgroundThailand is home to around 69 million individuals. Dengue is hyper-endemic and all 4 serotypes are in active circulation in the country. Dengue outbreaks occur almost annually within Thailand in at least one province but the spatio-temporal and environmental interface of these outbreaks has not been studied.MethodsWe develop Bayesian regime switching (BRS) models to characterize outbreaks, their persistence and infer their likelihood of occurrence across time for each administrative province where dengue case counts are collected. BRS was compared against two other classification tools and their agreement is assessed. We further examine how these spatio-temporal clusters of outbreak clusters arise by comparing reported dengue case counts, urban population, urban land cover, climate and flight volumes on the province level.ResultsTwo dynamic dengue epidemic clusters were found nationally. One cluster consists of 47 provinces and is highly outbreak prone. Provinces with a large number of case counts, urban population, urban land cover and incoming flight passengers are associated to the epidemic prone cluster of dengue. Climate has an effect on determining the probability of outbreaks over time within provinces, but have less influence on whether provinces belong to the epidemic prone cluster. BRS found high agreement with other classification tools.ConclusionsImportation and urbanization drives the risk of outbreaks across regions strongly. In provinces estimated to have high epidemic persistence, more resource allocation to vector control should be applied to those localities as heightened transmission counts are likely to occur over a longer period of time. Clustering of epidemic and non-epidemic prone areas also highlights the need for prioritization of resource allocation for disease mitigation over provinces in Thailand.

Navigation Mode Transition Design and Performance Validation for Heterogeneous Sensor Integration under Urban Flight Environment

This paper presents methods of mode transition in the integrated navigation based on selective sensor configurations to ensure continuous and reliable navigation performance in urban flight environments such as high-rise buildings. First, this paper characterizes candidate techniques using conventional DOP and error covariance for quantitative analysis of the navigation mode transition. Then, this paper proposes a new hybrid logic that reflects the deployment of heterogeneous sensor measurements considering characteristics of the urban flight environment. Through the proposed mode transition algorithm, enhanced estimation performance is achieved between GPS/INS integrated navigation and map-aided Range/INS integrated navigation. Finally, simulation and practical flight experiments under the urban flight environment demonstrated the suggested improvement of navigation performance.

Urban Flight Seeded the COVID-19 Pandemic Across the United States

We document large-scale urban flight in the United States in the wake of the COVID-19 pandemic. Populations that flee are disproportionately younger, whiter, and wealthier. Regions that saw migrant influx experience greater subsequent COVID-19 case growth, suggesting that urban flight was a vector of disease spread. Urban residents fled to socially connected areas, consistent with the notion that individuals were sheltering with friends and family or in second homes. The association of migration and subsequent case growth persists when instrumenting for migration with social networks, pointing to a causal association.

Analysis on Observability and Performance of INS-Range Integrated Navigation System Under Urban Flight Environment

This paper investigates the observability and navigation performance analysis of the integrated navigation system for the onboard operation in urban building forests. INS mechanization with some rangefinders is employed to achieve navigation performance with an urban geographical map. First, presented is a model of the range-inertial sensor integrated navigation system for the purpose of performing the observability analysis in a complex urban environment. Next, it is derived from the analysis formula of the filter observability based on the proposed system and measurement model. In order to examine the validity of the model, we analyzed the relationship between observability and estimation performance through simulation and flight experiments. In addition, a comparative study using the ICP matching based integration is presented. The simulation study employs a simple map environment for an intuitive analysis, where error characteristics are related to the observability rank. Finally, a practical test result using the multi-copter system is presented to address the correlation between observability and navigation performance through a real flight adjacent to tall buildings.

Design and Performance Validation of Integrated Navigation System Based on Geometric Range Measurements and GIS Map for Urban Aerial Navigation

This article proposes an efficient integrated navigation algorithm to secure reliable navigation solutions in urban flight environments where satellite navigation is not available. Also, this study investigates a new sensor deployment and filter configuration that can perform real-time navigation onboard small drones by reducing the complexity and computational burden of the conventional point cloud-based pose estimation. The proposed method first derives the geometric relationship between the ranging vector and the known three-dimensional map, where the number of range sensors and deployment structure is refined. Then, we designed the inertial navigation filter structure combining the derived measurement model and evaluated the estimation performance in a realistic urban flight environment. The validity of the proposed algorithm is verified through both error analysis using a simulator with a high-fidelity model and real navigation error analysis from onboard flight test adjacent to urban buildings. In conclusion, this paper presents a distinctive navigation method from the existing point cloud-based approaches and the performance of real-time three-dimensional navigation with a position error of about 1–2 m in satellite unavailability environment.

Identification of urban flight corridors for migratory birds in the coastal regions of Shenzhen city based on three-dimensional landscapes

The rapid urban expansion in southern coastal regions of China can endanger the quality and connectivity of bird habits and thus challenge our capacity for protecting bird species in urban areas. Identifying the ecological corridors that allow migratory birds to and from urban green landscapes is therefore essential for conserving biodiversity in urban areas. This study aimed to explore how urban expansion in vertical direction affects the flying paths of migratory birds and seek measurements to enhance bird migration to and from urban areas. The ecological security pattern (ESP) for migratory birds in a coastal region near the Shenzhen city of China was determined based on three-dimensional landscape data and results were evaluated against historical eBird record abundance data. The positive agreement with historical bird abundance demonstrated that the consideration of three-dimensional landscape in parameterizing the resistance for ESPs can help identify the flight corridors for migratory birds in urban areas and the consequent sixteen key flight corridors with a total length of 454.78 km were identified in and around the Shenzhen city. The three-dimensional landscape data are essential for identifying flight corridors for migratory birds to and from urban landscapes. The extracted flight corridors in and around the Shenzhen city connected natural reserves with urban parks, thereby enlarging bird habitats and its conservation inside the Shenzhen city.

Managing crime for urban wellbeing and sustainable housing delivery: Through the lens of residents and housing developers in Malaysia

Social sustainability is a form of development that promotes a harmonious society that is conducive to residential integration and improvement of the population's quality of life. The rapid urbanization of today’s society has increased the costs of living and created much social problems and crime. Crime has turned new residential projects into urban ghettoes, driving property prices down, encouraging urban flight. The desertion of traditional housing estates and the poor sales performance of new residential projects has put a dampener into the national property market. Thus, this study was conducted in two stages at the southern region of Malaysia. First, semi-structured interviews were conducted with 24 residents in crime-prone localities using snowball sampling. Second, discussions were held with 11 housing developers. This paper discusses the impacts of crime on residents, the housing market, and how the issue may be resolved from the perspectives of these two groups of respondents. The interviews revealed the destabilizing nature of crime on the sustainability of urban housing and the gradual failing of traditional open neighbourhoods in favour of safer, gated and guarded neighbourhoods; it also revealed the difficult operational positions faced by property developers in the past in particular the high costs incurred and the large overhang units. This paper contributes by recommending how developers may incorporate crime-prevention measures through innovative spatial management practices such as in eco-housing to increase attractiveness of their projects while minimizing costs. Keywords: crime; housing innovation; social sustainability; spatial management

A Multi-Trip Vehicle Routing Problem for Small Unmanned Aircraft Systems-Based Urban Delivery

With the emergence of new technologies for small unmanned aircraft systems (sUAS), such as lightweight sensors and high-efficiency batteries, the operation of small unmanned aerial vehicles (sUAVs) will expand from military use to commercial use. A promising commercial application of sUAS is package delivery because of its potential to reduce acquisition and operating costs of the last-mile delivery system, while enabling new services such as same-day delivery. Moreover, in urban areas, sUAVs can deliver packages to customers without negatively affecting street traffic. To conduct urban operations, sUAS-based delivery systems must obey regulations for sUAS operations and avoid urban obstacles. In this paper, a maximum-flight-time-constrained multitrip vehicle routing problem with time windows optimization model is used to create routes for sUAS-based delivery missions. To address the actual urban environment with the optimization model, a two-layered urban flight network is built by feeding an airborne light detection and ranging sensor data into an algorithm that uses a Voronoi diagram to create collision-free paths. This paper uses this approach to study a possible package delivery using sUAS in San Diego, CA.

Experimental Validation of Gaussian Process-Based Air-to-Ground Communication Quality Prediction in Urban Environments.

This paper presents a detailed experimental assessment of Gaussian Process (GP) regression for air-to-ground communication channel prediction for relay missions in urban environment. Considering restrictions from outdoor urban flight experiments, a way to simulate complex urban environments at an indoor room scale is introduced. Since water significantly absorbs wireless communication signal, water containers are utilized to replace buildings in a real-world city. To evaluate the performance of the GP-based channel prediction approach, several indoor experiments in an artificial urban environment were conducted. The performance of the GP-based and empirical model-based prediction methods for a relay mission was evaluated by measuring and comparing the communication signal strength at the optimal relay position obtained from each method. The GP-based prediction approach shows an advantage over the model-based one as it provides a reasonable performance without a need for a priori information of the environment (e.g., 3D map of the city and communication model parameters) in dynamic urban environments.