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Urban planning has a crucial role in helping cities meet the United Nations’ Sustainable Development Goals and robust datasets to assess mobility accessibility are central to smart urban planning. These datasets provide the information necessary to perform detailed analyses that help develop targeted urban interventions that increase accessibility...
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... MMA has been identified as the second-most-polluted city in Latin America and is the ninth-most-polluted city in the world [18]. These levels of pollution are strongly related to the industrial activities located in the city, but also to the city's dependency on motorized vehicles (see Figure 1). ...
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... the decision was made to manually map missing locations based on Google Maps data. Figure 11 shows a significant change in the number of destinations, demonstrating that the original data source for the Stanford District, OSM, has not been updated. In contrast, the database from DENUE for Distrito Tec showed no missing locations. ...
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... contrast, the database from DENUE for Distrito Tec showed no missing locations. Hence, running UrMoAC with the data shown in Figure 11 would surely bring new and better results, as accessibility levels in the Stanford District would increase. Such faults represent a considerable constraint in planning processes and can mislead decisions regarding urban interventions that aim to improve accessibility levels. ...
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... if the level of access to elementary schools is high enough, such trips could be easily made by walking and, therefore, not relying on motorized transport. Figure 12 shows that the Stanford District has 14 different public elementary schools within its boundaries. Even though the number is considerably high, most of them are in the northeastern and eastern sides of the polygon. ...
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... Tec has only two elementary schools (see Figure 13), but the surrounding areas have a higher density of destinations. Consequently, 72.72% of the aggregation areas within Distrito Tec have a high level of accessibility and the remaining 27.27% a medium one (see Table 9). ...
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... their commuting patterns are similar to primary school students, where their parents usually drop them off at school, with a car or with public transport, or they arrive by school bus. Figure 14 shows the five public middle schools located within the Stanford District. These are located in the eastern and western areas of the polygon. ...
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... 20.25% of the block groups have a high level of accessibility with the remaining 79.75% a medium level (see Table 10). Distrito Tec has only two public middle schools (see Figure 15). However, all the aggregation areas have a high level of accessibility (see Table 10). ...
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... modes of transport can also be easily complemented with school buses or public transport if the commutes are long. Figure 16 shows the number of public high schools within the Stanford District. Immediately, it can be noticed that the density is very low, with only three destinations inside the district, two located at the center and one at the eastern corner. ...
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... only 7.59% of the aggregation areas have high accessibility levels, 91.14% medium levels, and 1.27% low levels (see Table 11). Figure 17 shows that like in the Stanford District, in Distrito Tec, there is an extremely low density of public high schools, with only one destination available within the area. Nevertheless, 81.81% of the aggregation areas have a high level of accessibility and the remaining 18.18% a medium level (see Table 11). ...
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... historically, many cities have had a lack of investment in such spaces, and many urban morphologies and typologies have prioritized private space over public space. Figure 18 shows the parks within the Stanford District. The vast number of parks are located throughout the entire area, excluding the south. ...
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... High (0)(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) 63/79-79.75% 11/11-100% Figure 18. Stanford District average travel time to the closest park by foot. Figure 19 shows the parks within Distrito Tec. ...
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... District average travel time to the closest park by foot. Figure 19 shows the parks within Distrito Tec. Most of them are located in the north, west, and south of the polygon, leaving the east with few destinations, as well as the center. ...
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... 0/11-0% Figure 21 demonstrates that Distrito Tec does not have any public general hospitals within its area, nor in the vicinity. Consequently, the levels of accessibility to such destinations are mainly low (72.72% of aggregation areas) and the remaining 27.27% medium (see Table 13). ...
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... The methodology developed in the study presented by the authors allows us to evaluate whether the existing infrastructure in residential complexes can be intervened by changing the function and satisfy the needs of the population of the area (prioritizing thermal comfort, comfort due to vibrations, and economic aspects, among others). The need for datasets to assess mobility accessibility in urban areas was discussed [19]. A comparative analysis of urban accessibility was made for two university campuses and their surrounding urban areas. ...
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... Recent studies highlighted the significance of datasets on urban accessibility. These studies were conducted on various areas by considering the correlation between urban form characteristics and accessibility and factors, such as time, distance, average speed, and transportation services, associated with traveling to destinations within a city [62][63][64][65][66][67]. ...
... Recent studies highlighted the significance of datasets on urban accessibility. These studies were conducted on various areas by considering the correlation between urban form characteristics and accessibility and factors, such as time, distance, average speed, and transportation services, associated with traveling to destinations within a city [62][63][64][65][66][67]. Referring to the United Nation s SDGs [68], several studies have begun including walking accessibility by focusing on travel modes that yield the lowest carbon emissions; these studies have also addressed limiting the travel range in terms of the duration and distance while examining the diversity of travel patterns within this range [33,[69][70][71]. ...
We investigated the relationship between urban accessibility of museums in the urban spaces of Tokyo and Seoul within limited travel distances. Similarities and differences were identified in the museum accessibility between the two cities. The urban accessibility of museums was set as the dependent variable, calculated via space syntax. For the spatial accessibility of museums, five walking ranges (1000–2000 m) were set as independent variables, with a distance of 250 m as the basic unit. Data normality and independence of the derived data were checked, and polynomial curve fitting was performed to interpret the accessibility of museums in each city. A comparative analysis was conducted on museum accessibility. The results show areas with a high concentration of museums in Tokyo and Seoul partially deviated from the center of the urban hierarchy. The urban and spatial accessibilities of museums in both cities quantitatively correlated with limited travel distances. Museum visitors in Tokyo were more likely to have relatively free-flowing routes in the city. The museums in Seoul had a lower overall accessibility than those in Tokyo, and travel patterns and routes to these museums were likely to be restricted when located in urban areas and consequently resembled a forced movement pattern.
... Due to increasing environmental attention, a new consciousness is changing how citizens move across the city [17], and slow and light mobility plays a pivotal role in this cultural change promoted after the COVID-19 outbreak [18]. The increasing demand for alternative transportation modes forces radical changes in urban layout [19] from car-centred to proximity-based cities [20]. Proximity among city areas, especially to green spaces and services, shortens spaces and time, and favours the neighbourhood relationship [21]. ...
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