اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدUrban Morphometrics: Towards a Science of Urban Evolution
108
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Urban theorists, social reformists and philosophers have considered the city as a living organism since Plato. However, despite extraordinary advancements in evolutionary biology, now being used to explain social and cultural phenomena, a proper science of evolution in cities has never been established since Geddes work at the dawn of the Town Planning discipline. Commencing in the tradition of Urban Morphology, this research develops and validates a statistically reliable and universally applicable urban taxonomy. The research solidifies existing definitions of built form at the scale of the urban fabric and identifies the constituent elements of form in 40 contemporary UK cities. Quantifiable measurements of these elements allow mathematical descriptions of their organization and mutual relationships. Further, an optimized list of indices with maximum discriminatory potential distinguishes between cases from four historically characterised categories: 1) Historical, 2) Industrial, 3) New Towns, 4) Sprawl. Finally, a dendrogram is produced that shows the tree of similarity between cases, where the great divide between pre and post WWII war urban form is demonstrated. This work shows that: a) it is conceptually sound and viable to measure urban fabric utilizing public, big-data repositories, b) the proposed urban morphometrics system accurately characterises the structure of urban form and clusters cases properly based on their historical origins, c) scientific models of biological evolution can be applied to urban analysis to understand underlying structural similarities.
قيم البحث
اقرأ أيضاً
We propose hypotheses describing the empirical finding of an association between the exponents of urban GDP scaling and Zipfs law for cities. These hypotheses represent various combinations of directional or reciprocal causal links between the two ph
enomena and include inter- and intra-city processes. Future theories and models can be motivated with and categorized according to these hypotheses. This paper intends to stimulate the discussion around the processes behind these phenomena and pave the way to a Unified Urban Theory.
The advent of shared-economy and smartphones made on-demand transportation services possible, which created additional opportunities, but also more complexity to urban mobility. Companies that offer these services are called Transportation Network Co
mpanies (TNCs) due to their internet-based nature. Although ride-sourcing is the most notorious service TNCs provide, little is known about to what degree its operations can interfere in traffic conditions, while replacing other transportation modes, or when a large number of idle vehicles is cruising for passengers. We experimentally analyze the efficiency of TNCs using taxi trip data from a Chinese megacity and a agent-based simulation with a trip-based MFD model for determining the speed. We investigate the effect of expanding fleet sizes for TNCs, passengers inclination towards sharing rides, and strategies to alleviate urban congestion. We show that the lack of coordination of objectives between TNCs and society can create 37% longer travel times and significant congestion. Moreover, allowing shared rides is not capable of decreasing total distance traveled due to higher empty kilometers traveled. Elegant parking management strategies can prevent idle vehicles from cruising without assigned passengers and lower to 7% the impacts of the absence of coordination.
The identification of urban mobility patterns is very important for predicting and controlling spatial events. In this study, we analyzed millions of geographical check-ins crawled from a leading Chinese location-based social networking service (Jiep
ang.com), which contains demographic information that facilitates group-specific studies. We determined the distinct mobility patterns of natives and non-natives in all five large cities that we considered. We used a mixed method to assign different algorithms to natives and non-natives, which greatly improved the accuracy of location prediction compared with the basic algorithms. We also propose so-called indigenization coefficients to quantify the extent to which an individual behaves like a native, which depends only on their check-in behavior, rather than requiring demographic information. Surprisingly, the hybrid algorithm weighted using the indigenization coefficients outperformed a mixed algorithm that used additional demographic information, suggesting the advantage of behavioral data in characterizing individual mobility compared with the demographic information. The present location prediction algorithms can find applications in urban planning, traffic forecasting, mobile recommendation, and so on.
Assessing the resilience of a road network is instrumental to improve existing infrastructures and design new ones. Here we apply the optimal path crack model (OPC) to investigate the mobility of road networks and propose a new proxy for resilience o
f urban mobility. In contrast to static approaches, the OPC accounts for the dynamics of rerouting as a response to traffic jams. Precisely, one simulates a sequence of failures (cracks) at the most vulnerable segments of the optimal origin-destination paths that are capable to collapse the system. Our results with synthetic and real road networks reveal that their levels of disorder, fractions of unidirectional segments and spatial correlations can drastically affect the vulnerability to traffic congestion. By applying the OPC to downtown Boston and Manhattan, we found that Boston is significantly more vulnerable than Manhattan. This is compatible with the fact that Boston heads the list of American metropolitan areas with the highest average time waste in traffic. Moreover, our analysis discloses that the origin of this difference comes from the intrinsic spatial correlations of each road network. Finally, we argue that, due to their global influence, the most important cracks identified with OPC can be used to pinpoint potential small rerouting and structural changes in road networks that are capable to substantially improve urban mobility.
Cycling is a promising solution to unsustainable car-centric urban transport systems. However, prevailing bicycle network development follows a slow and piecewise process, without taking into account the structural complexity of transportation networ
ks. Here we explore systematically the topological limitations of urban bicycle network development. For 62 cities we study different variations of growing a synthetic bicycle network between an arbitrary set of points routed on the urban street network. We find initially decreasing returns on investment until a critical threshold, posing fundamental consequences to sustainable urban planning: Cities must invest into bicycle networks with the right growth strategy, and persistently, to surpass a critical mass. We also find pronounced overlaps of synthetically grown networks in cities with well-developed existing bicycle networks, showing that our model reflects reality. Growing networks from scratch makes our approach a generally applicable starting point for sustainable urban bicycle network planning with minimal data requirements.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
