Abstract A growing body of research shows affluent White neighborhoods have more acres of parks and more park facilities than low-income ethnic minority communities in many Global North cities. Most of these investigations focused on neighborhood-level differences and did not analyze broader inequities across cities. This is a particularly significant limitation in the U.S., where changes in the political economy of parks due to a reduced local tax base have led cities to compete against each other to secure park funding from national nonprofits and public agencies. To address this gap, we examined whether the quality of urban park systems – measured through The Trust for Public Land’s ParkScore – varies depending on a city’s median income and ethnic composition. Based on multivariate regressions in which we control for features of the urban fabric, we found U.S. cities with higher median incomes and lower percentages of Latino and Non-Hispanic Black residents have higher ParkScores than other cities. Some inequities also emerged for park coverage, park spending per person, and park facilities, with majority-Latino cities being particularly disadvantaged. These findings echo the results of neighborhood-level studies in Global North contexts, suggesting neighborhood-level inequities in park provision might scale up to inequities across cities. This study contributes to environmental justice theory and advocacy by demonstrating the importance of scaling up analyses of park provision to cross-city comparisons. Implications for landscape planning, public policy, and grant-making are discussed.
Because of radical economic and technological changes cities are facing growing competition for investors, tourists, qualified labour or international events over the last decades (see Begg 1999). As a consequence city rankings have experienced a remarkable boom: On the one hand the comparison of cities can support investors in their choice of location, on the other hand it can be an important guide for the cities to judge their strengths and weaknesses and to define their goals and strategies for future development and better positioning in the urban system. However, there is some evidence that the discussion of city rankings is mainly concentrated on the final ranks totally neglecting (1) the methods and indicators used (see Schönert 2003) resp. (2) its purpose and effectiveness for strategic planning aiming at the strengthening of the position to be gained. In front of this development, this paper concentrates first on the question what are the basic characteristics of national and international city rankings. Correspondingly, a selected number of city rankings are analyzed in order to identify different types of such rankings. Thereby, the number and features of the indicators used in these rankings as well as their methods of sequencing is described systematically. The sample of indicators and the complexity of the ranking approach itself constitute the base for a quality assessment of city rankings discussed within this paper. In particular, an own ranking approach ("European Smart Cities") is described. In the second part, the paper concentrates on the question how cities cope with the results and what are typical reactions of local governments and stakeholders. For providing insight into the way cities respond, it is described how they try to make use of their results to city rankings respectively how they reflect on the strengths and weaknesses revealed in the study. In this context different urban strategies for steering development and processes of learning in general, but especially with respect to urban planning and marketing, are discussed within this paper. Answering these questions the paper concludes in proposals for making city rankings a more significant and effective instrument for steering economic, social and spatial processes in cities: recommendations for researchers and analysts dealing with the design and methodology of city rankings on the one hand and for local governments and stakeholders concerning the reasonable handling of results on the other hand are formulated.
Bramantyo Eko Prabowo, Fitri Rachmayani, Glenn Adriel Adiguna
et al.
Landslides and slope instability events in Indonesia frequently occur during the rainy season. The relationship between rainfall and landslide activity is closely linked to the ability of rainwater to infiltrate the soil, which in turn affects slope stability. The objective of this study is to assess the duration of water infiltration in unsaturated soil conditions. Soil samples were taken from the western region of Indonesia and classified as silty sand (SM). Advanced laboratory testing was conducted to obtain the unsaturated soil properties, including soil water characteristic curve (SWCC), shrinkage curve, unsaturated permeability, and unsaturated shear strength. Few studies have examined the influence of different rainfall durations on seepage and slope stability. In this study, numerical simulations include rainfall application on the ground surface for three different durations over 1 day, that is, 6-h, 12-h, and 24-h simulations. A groundwater table was located at a depth of 5 m from the surface. The simulation results reveal increases in the groundwater level and in pore-water pressure during infiltration. This event reduces the suction force in unsaturated silty sand soil, thereby decreasing the factor of safety (FoS) in slope stability. The most significant decrease in FoS occurs in the 6-h simulation, while the effect on the safety factor in the 24-h simulation is not significant. This occurs due to the high intensity of rain during the shorter rainy period. After the rainy conditions, the factor of safety gradually rises and stabilizes on the sixth day, reaching an FoS of 1.86. This work identifies areas where silt–sand lithology predominates, along with high rainfall intensity and landslide susceptibility, providing important information to guide mitigation measures.
Engineering (General). Civil engineering (General), City planning
Mirko Lai, Anna Sapienza, Salvatore Vilella
et al.
The 15-minute city concept has gained momentum as an urban planning strategy to enhance livability, inclusiveness, and sustainability by ensuring that essential services are within a short walk or bike ride from home. However, while hyper-proximity is often promoted as desirable, its potential side effects on spatial segregation and social exclusion remain underexplored. In this paper, we propose a network-based analytical framework to investigate whether hyper-proximity models - such as the 15-minute city - may inadvertently reinforce spatial segregation by shaping service accessibility and urban transport connectivity. We model cities as complex spatial networks, quantify accessibility using the distribution of relevant Points of Interest (PoIs) and employ closeness centrality as a proxy for connectivity across multiple scales, from residential addresses to network-derived clusters and entire cities. Our results show that areas with better access to services generally exhibit higher connectivity and vice versa. However, this tendency is uneven when looking at socio-demographic factors. Some neighborhoods, particularly lower-income ones, experience both lower accessibility and weaker connectivity. In contrast, certain higher-income neighborhoods display low accessibility and limited connectivity, suggesting patterns of voluntary isolation. These findings indicate that hyper-proximity alone does not guarantee inclusiveness and may mask underlying socio-economic inequalities.
Vahid Isazade, Abdul Baser Qasimi, Abdulla Al Kafy
et al.
Flood events are the most sophisticated and damaging natural hazard compared to other natural catastrophes. Every year, this hazard causes human-financial losses and damage to croplands in different locations worldwide. This research employs a combination of artificial neural networks and geographic information systems (GIS) to simulate flood-vulnerable locations in the Samangan Province of Afghanistan. First, flood-influencing factors, such as soil, slope layer, elevation, flow direction, and land use/cover, were evaluated as influential factors in simulating flood-prone areas. These factors were imported into GIS software. The Fishnet command was used to partition the information layers. Furthermore, each layer was converted into points, and this data was fed into the perceptron neural network along with the educational data obtained from Google Earth. In the perceptron neural network, the input layers have five neurons and 16 nodes, and the outputs showed that elevation had the lowest possible weight (R2 = 0.713) and flow direction had the highest weight (R2 = 0.913). This study demonstrated that combining GIS and artificial neural networks results in acceptable performance for simulating and modeling flood susceptible areas in different geographical locations and significantly helps prevent or reduce flood hazards.
In this work, we introduce a planning neural operator (PNO) for predicting the value function of a motion planning problem. We recast value function approximation as learning a single operator from the cost function space to the value function space, which is defined by an Eikonal partial differential equation (PDE). Therefore, our PNO model, despite being trained with a finite number of samples at coarse resolution, inherits the zero-shot super-resolution property of neural operators. We demonstrate accurate value function approximation at $16\times$ the training resolution on the MovingAI lab's 2D city dataset, compare with state-of-the-art neural value function predictors on 3D scenes from the iGibson building dataset and showcase optimal planning with 4-DOF robotic manipulators. Lastly, we investigate employing the value function output of PNO as a heuristic function to accelerate motion planning. We show theoretically that the PNO heuristic is $ε$-consistent by introducing an inductive bias layer that guarantees our value functions satisfy the triangle inequality. With our heuristic, we achieve a $30\%$ decrease in nodes visited while obtaining near optimal path lengths on the MovingAI lab 2D city dataset, compared to classical planning methods ($A^\ast$, $RRT^\ast$).
To reduce waste and improve public health and sanitation in New York City, innovative policies tailored to the city's unique urban landscape are necessary. The first program we propose is the Dumpster and Compost Accessibility Program. This program is affordable and utilizes dumpsters placed near fire hydrants to keep waste off the street without eliminating parking spaces. It also includes legal changes and the provision of compost bins to single/two-family households, which together will increase composting rates. The second program is the Pay-As-You-Throw Program. This requires New Yorkers living in single/two-family households to purchase stickers for each refuse bag they have collected by the city, incentivizing them to sort out compostable waste and recyclables. We conduct a weighted multi-objective optimization to determine the optimal sticker price based on the City's priorities. Roughly in proportion to the price, this program will increase diversion rates and decrease the net costs to New York City's Department of Sanitation. In conjunction, these two programs will improve NYC's diversion rates, eliminate garbage bags from the streets, and potentially save New York City money.
Litchi seed starches from six varieties, as compared with maize starch, were studied for their multilevel structures, thermal and digestion properties to understand the distinct feather of each variety and provide guidance for their utilization in multi-industries. The results showed different varieties of litchi seed starch shared similar appearances with granules in oval shape and with a smooth surface. Starch granules of all the varieties exhibited typical bimodal size distributions consisting of small (<40 μm) and large granules (40–110 μm), although their relative proportions were largely dependent on variety. Huaizhi had the largest D50 value, whilst Guiwei showed the lowest. All the litchi seed starches had A-type crystalline with relative crystallinity varying from 20.67% (Huaizhi) to 26.76% (Guiwei). Similarly, the semi-crystalline structure varied apparently with variety. As to the chain-length distribution, only slight differences were observed among varieties, except Huaizhi displayed apparently higher amylose content (34.3%) and Guiwei showed the lowest (23.6%). Significant differences were also present in the gelatinization properties. Huaizhi seed starch showed significantly higher gelatinization temperatures and lower enthalpy change than the others. The digestibility of cooked litchi seed starches was only slightly different among varieties, suggesting variety is not the most critical factor regulating the digestibility of cooked litchi seed starch.
For the city of Barnaul, a study was carried out on the development of suburbanization –growth of a habitable suburban area with low-density building. Archival maps, up-to-date aerial photography, and materials of the master plan helped establish the periods of Barnaul suburbanization from the foundation of the city to the present time. Based on the research literature devoted to the current problems of suburbanization and selected scenarios of suburbanization according to the world urban planning experience, a forecast is made regarding further suburbanization of Barnaul over the next decade. It is assumed that in this large regional city with a compact planning structure, suburbanization will follow a hybrid “post-Soviet” scenario, in which low-intensity development of suburbanization will prceed along with “peripheral urbanization” partially replacing suburbanization through the construction of high-rise neighborhoods along the Zmeinogorsky and Pavlovsky tracts, mainly within the administrative boundaries of the city. An assumption is made about the limitations of the suburbanization processes in the city of Barnaul due to the exhaustion of migration and demographic resources compared to the situation in the 20th century.