Mixed-use distribution index: A novel bilevel measure to address urban land-use mix pattern (A case study in Tehran, Iran)

Motieyan, Hamid; Azmoodeh, Mohammad

doi:10.1016/j.landusepol.2021.105724

Cited by 12 publications

(7 citation statements)

References 26 publications

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“…As already shown in the existing literature, increasing the LMU can stimulate urban dynamics [18,47], and the discussions were mainly centered around land use patterns of different types of land uses [12,48]; or avoiding NIMBY syndromes that suggested the integration of mutually reinforcing (land) functions [42,49]. In this study, we argue that these discussions cannot avoid the scale that is identified as one of the most influential elements in the discussion of LMU [9,19].…”

Section: Discussionmentioning

confidence: 65%

“…Although industrial use has been less commonly included, the current study also suggests the possibility of a mixture in certain urban regions [11]. The degrees of the land mixture in terms of land-use priorities, distance, and attributes are taken as key factors in the existing research to reflect the outcomes and direct relevant practices [12,13]. More recently, the discussion also extended to travel behavior that is closely related to health outcomes [14], life satisfaction [15], and energy and environmental performance resulting from land mixed uses [16], which were highly related to timely topics and current development challenges.…”

Section: Introductionmentioning

confidence: 96%

“…As the existing studies suggested that simple, area-based measures of land use mix are not sufficient to capture the complex difference resulting from the nuance of land use mixture [14], indexing is, therefore, one of the approaches that are most commonly employed and suggested methods to analyze the effects of LMU [9,11,12,17]. In the same light, more complex mixed-use indicator sets were introduced for the studies at different spatial scales (e.g., city, district, subdistrict, or neighborhood) and in various classifications (e.g., land categories) [13].…”

Section: Introductionmentioning

confidence: 99%

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Towards a Multi-Scale Effect of Land Mixed Use on Resident Population—A Novel Explanatory Framework of Interactive Spatial Factors

Liu,

Huang,

2024

Land

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Starting from Jane Jacobs’ critiques and largely promoted and emphasized by New Urbanism, land mixed use (LMU) has become prevalent worldwide. It is believed to be an efficient approach to shaping a higher level of vitality in the economy, equality in society, and quality in the environment. To reveal the differences of this effect at distinct spatial scales, this study selected the two most related outcomes of LMU—resident population distribution and changes—to investigate the LMU impacts. A novel framework is developed to quantify the interactive impact of pairwise LMU-related factors at multiple scales, and the geographical detector is applied to identify the relationship between resident population distribution/changes and LMU. Taking the Jiading District of Shanghai as a pilot case, the framework was applied and tested. The results showed LMU affected resident population distribution distinctively from 600 m to 3000 m grid scales. The grid scale of 1800 m, approximately ten blocks, is revealed to be the optimal scale for discussing LMU with the selected factors. Also, these factors play different roles at different spatial scales. Some factors strongly affect the resident population distribution only when working with other factors. The study emphasized the crucial role of scale in LMU and suggested an open framework to support the decision making and policy making in planning for a better performance of smart growth and sustainability via LMU. It can help researchers obtain the optimal scale for the LMU plans with different sets of factors and identify the key factors in various contexts. Thus, this framework also contributes to supporting other practices of land mixed use beyond our study region.

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Section: Discussionmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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Towards a Multi-Scale Effect of Land Mixed Use on Resident Population—A Novel Explanatory Framework of Interactive Spatial Factors

Liu,

Huang,

2024

Land

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“…In the high-quality development of Chinese cities, the emphasis on mixed-use functions is the national demand in the future. Facing the urgent purpose of urban renewal in modern society, identifying mixed-use functional areas, excavating the modes of mixed-use urban functions, and evaluating the rationality of mixed-use functions have become vital scientific problems 12 . Those issues should be solved first, then decision-makers can make a better decision and then improves the sense of gain, security, and happiness of residents.…”

Section: Introductionmentioning

confidence: 99%

Identification and prediction of mixed-use functional areas supported by POI data in Jinan City of China

Zheng

Wang

Shang

et al. 2023

Sci Rep

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The urban development of China is changing from incremental expansion to stock renewal mode. The study of urban functional areas has become one of the important fundamental works in current urban renewal and high-quality urban development. In recent years, big spatiotemporal data has been well applied in the urban function field. However, the study of spatial–temporal evolution characteristics and forecasting optimization for mixed-use urban functional areas has not been examined well. Thus, in this study, we proposed a new approach that applies a revised information entropy method to analyze the degrees of mixing for urban functional areas. We applied our approach in Jinan City, Shandong Province as the study area. We used Point-of-Interest, OpenStreetMap and other datasets to identify the mixed-use urban functional areas in Jinan. Then, the CA–Markov model simulated the urban layout in 2025. The results showed that: (1) the combination of road network and kernel density method has the highest accuracy of identifying urban functional areas. (2)The mixing degree model is constructed by using the improved information entropy, which makes up for the shortcoming of identifying the mixed functional areas simply by the frequency ratio of POI data. (3) The “residence and business” functional area has the highest proportion in the central area of Jinan from 2015 to 2020, and the total area of mixed-use unban functional areas continuously increased during this period. (4) The total area of the central area in Jinan has significantly increased in 2025. The optimization of urban functions should expand mixed-use functional areas and increase the proportion of infrastructure. Also, Jinan should improve the efficiency of space development.

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“…MLU refers to a range of functional land-uses, including residential, commercial, industrial, institutional, and transportation-related. It has been promoted as a significant component of modern urban development strategies, such as smart growth, Transit-Oriented Development (TOD), walkability, and compact development [1][2][3][4]. MLU is expected to provide numerous social benefits such as urban vitality, social cohesiveness, job generation, and efficient use of public utilities, and reduce travel distance, energy consumption, and CO 2 emissions [5].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Effects of Transportation Supply on Mixed Land-Use at the Parcel Level

Almansoub

Zhong

Raza

et al. 2022

Land

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The interactive relationship between transportation and land use has become more difficult to understand and predict, due to the economic boom and corresponding fast-paced proliferation of private transportation and land-development activities. A lack of coordination between transportation and land-use planning has created an imbalanced provision of transportation infrastructure and land-use patterns; this is indicated by places where a high-density land-development pattern is supported by a low-capacity transport system or vice versa. With this, literature suggests that Mixed Land-Use (MLU) developments have the potential to provide relevant solutions for urban sustainability, smart growth, inclusive public transit use, and efficient land-use. Therefore, this study employed deep neural network models—Long Short-Term Memory (LSTM), and Multilayer Perceptron (MLP)—for forecasting the effect of transportation supply on the MLU pattern at the parcel level in the Jiang’an District, Wuhan, China. The findings revealed a strong relationship between the supply of public transportation and MLU. Moreover, the study results indicated that MLU is widely available in areas with high accessibility, high density, and proximity to the city center. The forecasting results from the MLP and LSTM models showed an average error of 5.55–7.36% and 3.62–4.28% for mixed use, respectively, while most of their 90th percentile errors were less than 13.73% and 10.46% for mixed use, respectively. The proposed models and the findings from this study should be useful for stakeholders and policy makers for more precise forecasting of MLU at the urban level.

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Mixed-use distribution index: A novel bilevel measure to address urban land-use mix pattern (A case study in Tehran, Iran)

Cited by 12 publications

References 26 publications

Towards a Multi-Scale Effect of Land Mixed Use on Resident Population—A Novel Explanatory Framework of Interactive Spatial Factors

Towards a Multi-Scale Effect of Land Mixed Use on Resident Population—A Novel Explanatory Framework of Interactive Spatial Factors

Identification and prediction of mixed-use functional areas supported by POI data in Jinan City of China

Exploring the Effects of Transportation Supply on Mixed Land-Use at the Parcel Level

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