Street Patterns Research Articles

A dramatic morphological transformation from a spontaneous, organic street pattern to pre-planned-based order: learning from Baghdad city

ABSTRACT A city can be characterised as a measurable pattern that comprises streets surrounded by block patterns. These street patterns are largely responsible for connectivity and accessibility, which enable people to move and interact. The study compares four samples in a case study in Baghdad, Iraq. The assets of Baghdad today belong to its historical period as its prevailing organic zigzagged network pattern determine its character. However, urban areas outside the historical zone are constructed according to modern schemes and a modernist ideology. This paper tests the connectivity and accessibility of the street network for four selected neighbourhoods. To achieve this, five indicators were applied, namely: intersection density Id, street density Sd, link to node ratio LNR, internal node connectivity INC and external point connectivity EPC. Following that, a correlation for each street parameter within the selected regions was analysed to identify the main characteristics of each variable in each area. Besides connectivity and accessibility, the paper’s aim is to characterise the historical neighbourhood of Baghdad by comparing it with other chosen areas. This study applies two stages to its case study; the first reviews traditional urban pattern and compares this to the other three examples. The second stage includes the selection of three different samples within the same city, where every sample has several common variables. Adopting a quantitative method, the outcomes revealed variation across the characteristics and parameters of the street pattern within the four chosen neighbourhoods. This finding offer a precise platform and key plan for future urban design strategies and planning methods. The research concluded that a greater understanding of street patterns and parameters could help to improve the built environment and the transformation processes of the urban form, particularly when considering walkability, connectivity, accessibility, and sustainability.

Multi-Scale Effects of Landscape Pattern on Soundscape Perception in Residential Green Spaces

Soundscape quality in green spaces of residential areas directly contributes to residents’ quality of life. It has close relationships with landscape characteristics, which should be considered in landscape planning and design processes in residential areas. Accordingly, this study proposed a new perspective on the interrelationships between soundscape perception and landscape pattern on multi-scale, based on a case study of 30 residential green spaces in Fuzhou, China. Percentage of Landscape (PLAND), Patch Density (PD), Landscape Shape Index (LSI), and Patch cohesion index (COHESION) were utilized to represent the landscape pattern of vegetation, buildings, and roads in the residential areas. Soundscape perception was interpreted using the sound dominant degree (SDD) of sound sources and overall soundscape quality. The examined spatial scales range from 20 m to 180 m, with concentric circles spaced 20 m apart for each sampling point. Correlation analyses indicated that most landscape indices of vegetation and buildings were correlated with these soundscape perception indicators, while limited landscape indices of roads were associated with them. Based on the multi-scale landscape indices, multiple linear regression models for the SDD of sound sources and overall soundscape quality were established, confirming that the scale effect of landscape patterns can affect soundscape perception. Expressly, results indicated that these models were chiefly influenced by the landscape indices at a scale less than 120 m, but the scale effect of landscape pattern on the SDD of birdsong, pleasantness, and quietness was not so evident. Furthermore, we found that the number of explanatory variables may somewhat affect the model performance. The overall interpretability of these landscape indices for the SDD of sound sources was better than that of overall soundscape quality, implying the complexity of the latter. This study offers a fresh insight into the relationship between landscapes and soundscapes at varying scales. The findings can provide useful information for the promotion strategies of landscapes and soundscapes, especially in residential green spaces.

Increase in optimal configuration of 25–60-day atmospheric circulations for Yangtze heavy rainfall under global warming background

In summer, the middle and lower reaches of the Yangtze River (MLYR) often suffers from severe floods as a result of a dominant intraseasonal oscillation (ISO) of rainfall with the quasi-period of 25–60 days. 75% of flooding events during summers of 1961–2022 are found to occur following wet phases of the 25−60-day ISO in rainfall. This study objectively extracts the optimal configuration (OC) of 25−60-day atmospheric ISOs for the wet phase of MLYR rainfall. The OC is characterized by the quadruple pattern of tropical convection configuring with the 25−60-day Silk Road Pattern (SRP) in the mid−high latitudes. The 25−60-day SRP in cooperation with tropical ISO over the western Pacific induces dipolar vertical cells over eastern China, with ascending branch between the vertical cells providing the vitally dynamical condition for MLYR rainfall. With topographic blocking of the Tibetan Plateau, the northward-propagating tropical ISO over the Indian Ocean enhances maintenance of the 25−60-day SRP via upper-tropospheric divergent flows, thus anchoring anomalous ascents to the MLYR. Numerical experiments further verify the remarkable tropical-extratropical interaction around the Tibetan Plateau in this OC. Under the global warming background, the tropical 25−60-day ISO tends to strengthen, leading to an increase in the occurrence frequency of strong OC through tropical-extratropical interaction, and thus the severe flood events doubled in summers of 1991–2020.

Arctic Sea Ice Loss Inducing Northwest Extension of Summer Precipitation over the Tibetan Plateau

Abstract Summer precipitation over the Tibetan Plateau (TP) has experienced obvious changes in recent decades, with significantly increased trends observed over the northern and western regions during 1961–2020. Results indicate that there are two pathways linking them to the reduced Arctic sea ice from late spring (April and May) to early summer (June and July). First, decreased sea ice in late spring favors wet and dry soil over the eastern Caspian Sea and northeastern TP by stimulating anomalous wavelike patterns and modulating snow melting. Furthermore, the soil moisture anomalies during late spring could maintain to July because of memory effects, strengthen the midlatitude Silk Road pattern, and contribute to the formation of a dipole mode around TP, characterized by a west cyclone and an east anticyclone. Second, through exciting an anomalous Rossby wave directly spreading from the Arctic to TP, a similar dipole pattern on 500-hPa geopotential height could be associated with the decline of sea ice in early summer. Consequently, enhanced southwesterly winds shown with the west cyclone cause more water vapor input to the western TP, while easterly anomalies along with the east anticyclone inhibit climatological westerly winds and prevent water vapor from outputting. This dipole pattern finally brings more moisture accumulated in the western and northern TP and increases the precipitation. This study links heterogeneous changes in summer precipitation over TP to Arctic sea ice changes and provides insights for further investigation into whether the TP could serve as a bridge connecting the Arctic and tropical climates.

Extreme heat event over Northwest China driven by Silk Road Pattern teleconnection and its possible mechanism

Under the background of global warming, heat wave events have become significantly frequent and have received increasing attention. Northwest China is located in the drylands of central Eurasia, where the climate and ecological environment are more vulnerable to global warming than in other parts of the world. Over the past few decades, the frequency of heat waves in Northwest China has increased significantly, and its causes remain unclear. We found that the heat events in Northwest China were closely related to the Silk Road Pattern teleconnection (SRP), and the strongly positive phase of SRP frequently corresponded to the occurrence of heat waves. Furthermore, the wave source of SRP was determined by the Linear baroclinic model to be located in the North Atlantic Ocean. We then selected an extreme heat event over Northwest China in 2021 as a typical case to discuss the possible mechanism. The regressed circulation fields to daily SRP were highly consistent with the anomalies that occurred during July 9–22, 2021, indicating that the diurnal propagation of SRP modulated the circulation anomaly related to the heat wave event and that diabatic heating influenced by SRP was the primary factor to the thermal low over Northwest China. Diabatic heating was strengthened in the lower troposphere due to the enhancement of downward shortwave radiation and surface sensible heat flux accompanied by strong descending motions and cloud cover reduction by an SRP-guided anticyclone over Northwest China. This study enhances the understanding and certainty regarding large-scale circulation effects on local temperature anomalies in middle latitudes.

Road Pattern Classification Using Deep Learning for Noise Data for Autonomous Driving Vehicle

Tire-pavement Interaction Noise (TPIN) is noise caused by interactions between rolling tires and road surfaces. After measuring the TPIN using a microphone, transform TPIN to images using continuous wavelet transform (CWT). The transformed images are used to classify the driving road and tire using convolutional neural network (CNN). The road and tire classification network using CNN is required for braking systems in autonomous vehicle. The CNN in this paper can classify snow road, asphalt road, and two types of tires with over 97% accuracy.

The increased summer monsoon rainfall in Northwest India: Coupling with the Northwestern Arabian Sea warming and modulated by the Silk Road Pattern since 2000

This study investigates changes in rainfall patterns over Northwest India (NWI) and the warming of the Northwestern Arabian Sea (NWAS) since 2000. These changes are attributed to the Silk Road Pattern (SRP) phase change in the late 1990s. The SRP positive phase triggers geostrophic deformation over the Tibetan Plateau (TP) by inducing an anomalous circulation pattern along the westerly jet, at 200 hPa. This deformation along the westerly Jet leads to Jet streaks and thermally indirect ageostrophic circulation over TP. In addition, the intensified heating over the TP led to a westward shift of the South Asian High (SAH). Associated with this, the interaction of positive temperature advection and northward ageostrophic wind (Jet entrance) over south-central Asia generates a southward component of ageostrophic wind (Jet Exit), causing upper-level convergence at southeast TP, excites the sinking cold air thereby strengthen the surface pressure below, over TP. This amplifies the anomalous anticyclone effect over there resulting in strong easterly wind anomalies along the monsoon trough at 850 hPa, disrupting the monsoon circulation. These anomalies, combined with a poleward shifting moisture-laden Low-Level Jet (LLJ), contribute to the warming of the NWAS and increased rainfall over NWI. The NWAS has shown significant summer warming over the past two decades. The poleward shift of the LLJ and SRP-induced circulation changes also impact the ocean dynamics. Given the occurrence of severe floods in this region of the Indian subcontinent, these findings have broader implications for predicting and projecting monsoon variability and extremes.

Effect of various housing patterns on social cohesion

Social cohesion in housing is an attribute of the quality of the community of its inhabitants. Housing planning needs to function to facilitate the social interaction of its inhabitants. This research aims to identify the effect of housing patterns on social cohesion in various housing patterns. Most existing housing patterns built are grid, linear, and T-shape patterns. It is necessary to know the effect of each pattern on social cohesion. The data collection technique used the questionnaire survey method. Two clusters were selected as samples such as the Lavender Lane 1 and Graha Sevilla in Citra Raya, Tangerang Regency. Those samples have linear, grid, and T-shape patterns. The total number of respondents from the three housing patterns is 121. The analysis technique used simple linear regression using Smart-PLS software. The results showed that the effect of housing patterns on social cohesion was evident in the linear and T-shape patterns, while it was not in the grid pattern. The housing pattern indicators affecting social cohesion are the total row of houses, building layout plans, and street patterns that need to be considered in cluster housing planning to build social cohesion.

Relationship between the Silk Road and Circumglobal Teleconnection Patterns on the Interannual and Interdecadal Timescales

The Silk Road pattern (SRP) and circumglobal teleconnection pattern (CGT) are two well-known teleconnection patterns, representing the summer circulation variations of the Northern Hemisphere mid-latitudes, which have different definitions but are often regarded as one teleconnection pattern. In view of the distinct features of the SRP/CGT on the interannual (IA) and interdecadal (ID) timescales, the present study investigates the linkages and differences between the SRP and CGT on the two timescales, respectively. On the IA timescale, both the SRP and CGT feature a similar circumglobal wave train structure with strong and significant centers over Eurasia but show clear independence. Specifically, the SRP and CGT illustrate largely the mid-/high-latitude-related and tropics-related parts of the Northern Hemisphere upper tropospheric circulation variations, respectively. Also, the CGT shows a stronger connection to the Indian summer monsoon (ISM) heating and El Niño–Southern Oscillation than the SRP, which makes the CGT more like a tropical forcing-driven atmospheric mode and the SRP more like an internal atmospheric mode. The linkages and differences between them are associated with their asymmetrical relationship during their positive and negative phases, which are attributed mainly to the asymmetrical impact of the ISM heating/cooling on the Eurasian circulations. On the ID timescale, the SRP and CGT are characterized by a coherent two-wave train structure over Eurasia and feature a similar teleconnection pattern over Eurasia, which is associated with the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation. The present findings on their linkages and differences are helpful in understanding the variability and prediction of the SRP and CGT.

A Spatiotemporal Analysis of “Spongy urban area” focusing on Parking Lots and Street Patterns in Central Area of Local City

A Spatiotemporal Analysis of “Spongy urban area” focusing on Parking Lots and Street Patterns in Central Area of Local City

Street Vibrancy and Outdoor Activities under COVID-19 Psychological Distress: Lessons from Hong Kong

The COVID-19 pandemic has had a distinctive impact on Hong Kong, especially given the city’s prior experience with the SARS outbreak. The resulting psychological distress has been exacerbated by Hong Kong’s extreme density and compactness, which places residents in proximity on the streets searching for outdoor activities. Streets are a precious source of space for social interactions, but, unfortunately, the pandemic has forced them to empty, leading to increased distress and challenging the psychological well-being of the urban population. In this study, we explore street vibrancy patterns in terms of outdoor activities, here addressed through a decision-making psychological perspective as volitional behaviors determined by psychological factors and essential for well-being, in one of the densest neighborhoods in Hong Kong. We statistically analyzed behavioral monitoring data in relation to spatial and morphological characteristics of their environments under COVID-19 psychological distress. The results highlighted the relevance of specific parcels of the streets acting as clusters and vibrancy initiators, stressing their significance in terms of affective and cognitive inputs determining context-based outdoor activities. The decision-making psychological perspective adopted here to address outdoor activities has relevant implications for design and planning strategies for post-pandemic scenarios, for psychological well-being, and for the future of urban density.

Global urban road network patterns: Unveiling multiscale planning paradigms of 144 cities with a novel deep learning approach

Urban road networks (URNs) are ubiquitous and essential components of cities. Visually, they present diverse patterns that embody latent planning principles. However, we still lack a global insight into such patterns. In this paper, we propose a scalable deep learning-based framework to automate accurate and multiscale classification of road network patterns in cities and present a comprehensive global implementation on 144 major cities around the world, yielding their multiscale pattern profiles and urban fabrics, highlighting both similarities and contrasts. We observe significant disparities across continents and regions, particularly at larger scales. We give particular attention to exploring inter-city pattern similarities with new metrics we introduce, and uncover subgroups in each continent, unveiling the potential intercontinental dissemination of planning paradigms. We establish four modes of intra-city spatial distribution of patterns considering diversity and clustering. Notably, radial road networks are found to be positively correlated with GDP per capita and negatively correlated with PM2.5 pollution. Our global study provides a new perspective to understand the URN texture of cities, which helps to understand the externalities of different road patterns and accordingly promote scientific and sustainable solutions for urban development.

Prevalent atmospheric and oceanic signals of the unprecedented heatwaves over the Yangtze River Valley in July–August 2022

Unprecedented heatwaves attacked the Yangtze River valley (YRV) in July–August of 2022. The heatwave-favorable circulation pattern for the YRV is identified by using a self-organizing map. Result shows that the dominant daily circulation pattern driving heatwaves in the YRV is the East Asian anticyclonic pattern (EAAP), characterized by an anomalous deep anticyclone over the East Asian mid-latitudes. Remarkably, the unprecedented frequent occurrence of EAAP in 2022 contributes about 84.6% of the temperature anomalies in the 35 YRV hot days, which is the key dynamical factor for the heatwave in 2022. Physical mechanisms for the occurrence of EAAP are revealed on interannual and interdecadal time scales. On interannual time scale, the dipole sea surface temperature (SST) anomalies over the North Atlantic, characterized by warm and cold SST anomalies in the midlatitudes and subtropics, respectively, exert an important influence on the EAAP days. This dipole SST pattern is unprecedentedly strong in 2022. It facilitates the EAAP through the maintenance of the coupled British–Okhotsk Corridor pattern and the Silk Road pattern in the mid-latitudes. Additionally, the persistent cold SST anomalies in tropical Indian ocean and the central-eastern Pacific from the preceding spring to summer contribute to cooling of the tropical troposphere and induce easterly anomalies in the East Asian subtropics, thereby further promoting the occurrence of EAAP. On interdecadal time scale, the negative Pacific Decadal Oscillation may establish favorable circulation conditions for the occurrence of the EAAP through modulating the interdecadal Silk Road pattern. These findings improve our understanding of the physical mechanisms for driving extreme heatwaves in the YRV and have an implication for enhancing regional heatwave prediction.

Seasonally Evolving Trends Explain the North‐South Dipole Pattern Observed in Tibetan Plateau Precipitation

AbstractThe Tibetan Plateau (TP) precipitation is experiencing the north‐south dipole tendency pattern since 1979. In this study, we identify four primary seasonally evolving patterns (SEPs) that explain approximately 50% of the total variance in precipitation variability over the TP. These SEPs contribute 60%–90% of the spatial mean amplitude of precipitation trends across seasons. In particular, the second SEP that features a north‐south dipole pattern dominates the annual mean trend of the precipitation over the TP. The interdecadal variability of the seasonally evolving north‐south dipole pattern is linked to the interdecadal variations of summer Silk Road Pattern and Indian monsoon. These findings suggest that the climate variability expressed through SEPs could potentially serve as a significant source for the interdecadal rainfall prediction.

Study on the walkability of old city streets in Beijing from the perspective of application of Central Axis for World Heritage List

The year 2023 is a key year for Beijing’s Central Axis to apply for World Heritage List. As the social space of urban culture, the streets are the communication space between modern-day residents and living heritage. In the blocks applying for World Heritage status, the walkability of the streets has an important impact on the presentation of the scene, cultural exchange, and tourist guidance. Based on the perspective of Central Axis application for World Heritage List, this study attempted to provide updated planning suggestions for the improvement of street walkability quality. Focusing on the human scale, first, 13 objective indicators and three subjective indicators of the streets in the buffer zone were evaluated by semantic segmentation, virtual audit, Likert scale, and other methods, as well as by acquiring the latest street view. Pearson’s correlation analysis was used to explore the main factors affecting the walkability of the streets. The results show that 13 objective indicators such as street interface, street facilities and street style in space show a trend of gradual decline from the central axis to both sides. Buildings on the north side of Chang’an Avenue in Beijing’s Old Town better preserve the architectural style of the traditional hutong. The factors that were strongly related to the sense of security were the proportion of fences and the width of the street. The strongest correlation factor concerning comfort is the street aspect ratio, whereas the most important factor related to aesthetic perception is the degree of preservation of traditional features. Finally, the paper puts forward some new strategies, such as clearly distinguishing street pedestrian and vehicular functions, controlling green visual ratio to adjust street visual aspect ratio, and protecting traditional street pattern.

Three-dimensional Budyko framework incorporating terrestrial water storage: Unraveling water-energy dynamics, vegetation, and ocean-atmosphere interactions

The two-dimensional steady-state Budyko framework, widely used to study water-energy dynamics in landscapes, primarily focused on the partitioning of precipitation into evapotranspiration (ET) and water yield. Though this framework has been extended by incorporating water storage changes into precipitation input for non-steady state conditions, the interactions among water-energy dynamics, vegetation covers, and ocean-atmosphere oscillations within the Budyko framework at finer spatial and temporal scales have been unexplored. This study aims to investigate the interactions of regional hydroclimatic conditions, vegetation, and climate teleconnections over the Indo-China Peninsula (ICP), a region highly vulnerable to climate change. To achieve the objective, we propose a three-dimensional Budyko framework that incorporates the ratio of Gravity Recovery and Climate Experiment (GRACE)-based terrestrial water storage (TWS) or its changes (TWSC) to precipitation (SI/SCI) as the third dimension alongside the traditional two-dimensional Budyko framework. Our findings reveal that TWS has a significant impact on the Budyko framework, particularly during the dry season. The dryness index (DI)/evaporative index (EI) and SI/SCI exhibit positive (strongly negative) linear relationships in the wet (dry) season, respectively. Vegetation covers strongly influence the three-dimensional Budyko framework, with poor performance observed in highly vegetated regions due to high ET demand. Through relative importance analysis, we identify the Silk Road Pattern (SRP) as the most influential climate teleconnection among nine different teleconnections, affecting hydroclimatic conditions over the ICP. Positive (negative) phases of SRP encourage water-limited (energy-limited) ET conditions. This demonstrates that the Budyko parameter is influenced not only by landscapes but also by climate teleconnections, offering potential benefits for Budyko parameter estimation. Furthermore, the linear relationships between DI/EI and SI/SCI in three-dimensional Budyko framework can provide a promising alternative method for evapotranspiration and groundwater estimation.

Street network patterns for mitigating urban heat islands in arid climates

ABSTRACT This study explores the impact of street pattern measurements on urban heat islands (UHI) in the arid climate of Mashhad, Iran. The Landsat-8 top-of-the-atmosphere (TOA) brightness images from 2013 to 2021, average values of normalized difference vegetation index (NDVI) and land surface temperature (LST) were calculated. Street pattern measurements, including closeness-centrality, straightness, and street orientation, were employed to analyse the patterns in each district. The results indicated that districts with higher straightness and lower closeness-centrality exhibit cooler surface temperatures. Strong correlations were observed between LST and NDVI, straightness, and local closeness-centrality. The research highlighted the importance of considering street network measurements in long-term urban planning and design to mitigate the UHI effect in arid regions. A moderate grid street pattern with a reasonable distribution of green spaces throughout the region is suggested to reduce surface temperatures sustainably. Street pattern indexes, such as straightness and local closeness-centrality, are identified as significant factors in urban design to mitigate UHI. These findings have implications for urban planners, who can use this information to create street network patterns with lower UHI effects by reducing local closeness-centrality and increasing straightness.

Recent Applications of Smart Technologies for Monitoring the Sustainability of Forest Operations

Precision forestry is a useful technique to help forest stakeholders with proper sustainable forest management. Modern sensors and technologies, with special reference to the sustainability of forest operations, can be applied on a variety of levels, including the monitoring of forest activities regarding the three pillars (economy, environment, and society). In this review, we summarised the current level of knowledge regarding the use of precision forestry techniques for monitoring forest operations. We concentrated on recent data from the last five years (2019–2023). We demonstrated how an Industry 4.0 strategy for remote and proximal monitoring of working performance can be effective when using CAN-bus and StanForD data collected by modern forest machines. The same information can be effectively used to create maps of soil trafficability and to evaluate the patterns of skid tracks or strip roads built as a result of forest intervention. Similar information can be gathered in the case of small-scale forestry by using GNSS-RF (Global Navigation Satellite Systems—Radio Frequency) or even monitoring systems based on smartwatches or smartphones. LiDAR and Structure for Motion (SfM) photogrammetry are both useful tools for tracking soil rutting and disturbances caused by the passage of forest machinery. SfM offers denser point clouds and a more approachable method, whereas laser scanning can be considerably faster but needs a more experienced operator and better data-processing skills. Finally, in terms of the social component of sustainability, the use of location sharing technologies is strongly advised, based for instance on GNSS—RF to monitor the security of forest workers as they operate.

Comparative measurement of CO2, CH4 and CO at two traffic interjunctions having inflated vehicular flow in Delhi

Vehicular emissions are considered one of the major anthropogenic sources of greenhouse gases and poor air quality in metropolitan cities. This study aims to see the correlation of CO2, CH4, and CO through monitoring over a period from December 2020 to October 2021 covering three seasons’ winter, summer, and monsoon at two different traffic locations of Delhi having different traffic volumes, road patterns, and traffic management. The annual average morning concentration of CO2, CH4 and CO was found (533 ± 105), (7.3 ± 3.1), (10.7 ± 3.0) ppm at Najafgarh and (480 ± 70), (5.2 ± 1.8), (7.8 ± 2.8) ppm at Rajendra Place, respectively. A relationship between concentration of all three gases and meteorological parameters such as temperature, humidity, wind speed and wind direction has also been investigated using Pearson correlation coefficient and pollution rose diagram. A comparable pattern in concentration was observed for all three gases in spatial (location) and temporal (diurnal) distribution. The concentration trend of CO2 in different seasons is winter > summer > monsoon, while in the case of CH4 winter = summer > monsoon but not any seasonal trend was noted in CO case. It is observed that CO2 has a good relation with CO (a tracer for vehicular emission) in terms of diurnal variation, whereas, CH4 does not represent a relation with CO and CO2 diurnally, suggesting that vehicles are the source of CO2 but not much contributing to other greenhouse gases like CH4.

A sixfold urban design framework to assess climate resilience: Generative transformation in Negril, Jamaica.

The uncertainty of climate change's impacts hinders adaptation actions, particularly micro-scale urban design interventions. This paper proposes a sixfold urban design framework to assess and enhance the resilience of urban form to climate change, where urban form refers to the patterns of streets, buildings, and land uses. The framework is then applied to Long Bay in Negril, Jamaica-a coastal area that incorporates the complex interactions between urbanization and a highly vulnerable socio-ecological system to climate change-related hazards, primarily sea-level rise. Empirical evidence from 19 in-depth interviews with planning and design professionals and development actors, in situ observations, and morphological analyses reveal that Long Bay's current adaptation strategies heavily rely on bounce-back resilience measures that predominantly consider the impacts of extreme climatic events rather than slow-onset ones. Such strategies abet current tourism-driven development patterns while overlooking Long Bay's inherent abilities for generative transformation and incremental changes to meet climatic uncertainty. Instead, this study's findings highlight how generative urban form transformation would better equip Long Bay to cope with future uncertainty-climatic or other.