Sustainable development is regarded as a pivotal factor for smart urban planning. Transit-Oriented Development (TOD) is a well-known land use transportation integration (LUTI) planning method, which can fulfill sustainable development objectives. In this study, a new spatial index is developed to measure TOD levels in neighborhoods of Tehran, the capital of Iran. To develop the TOD index, several criteria and indicators are first computed using spatial analyses, before being aggregated using a fuzzy-analytic hierarchy process (fuzzy-AHP). The fuzzy-AHP method generates three types of factor maps: that are optimistic, pessimistic, and moderate. This process evaluates the sensitivity of the TOD index by determining the indicators’ weights from various views, or perspectives. The results of this sensitivity analysis show the robustness of results from various views. Furthermore, in order to assess the efficiency of the proposed method, the moderate TOD-level map is compared with both the level of public transit services and trip attraction in neighborhoods. This comparison shows that the TOD map has an accuracy of 77 percent in urban modeling, which verifies the efficiency of the proposed method for measuring TOD.

The contemporary world possesses characteristics such as urbanism and expansion of cities that require a specific type of planning. Transit-oriented development (TOD) planning has emerged as an applicable planning method, which tries to achieve integrated land-use and transportation planning. In this research, a novel methodology was proposed to develop an efficient TOD index measuring land-use characteristics in neighborhoods of an urban region in Tehran, Iran. This index helps urban planners make optimum decisions regarding the development of public transit services in the region. In this research, a comprehensive set of criteria and indicators were developed to compute TOD index. Each indicator was computed using spatial analyses in the vector format since most of the indicators were spatial indicators and compatible with the vector format. Then the indicators were aggregated by hierarchical fuzzy inference system (HFIS) because of the large number of the rules. By such an aggregation method, the model considered the uncertainties and linguistic terms of experts’ rules as well as decreasing the number of rules from 1,600,000 to 221. Due to the fact that the research data were related to the year 2005, the activities that have been conducted since 2005 were evaluated based on the model output. The results demonstrate that TOD planning enables urban planners not only to determine shortcomings of land-use characteristics, but also to allocate public transit services in different neighborhoods.

Sustainable development is a vital and challenging factor for managing urban growth smartly. This factor contains three main components, namely economic growth, ecological protection and social justice. Green Transit-Oriented Development (GTOD) is a consummate planning approach in line with those components. Implementation of GTOD in an urban area is underpinned by its quantification. Therefore, a quantitative spatial index based on several indicators related to TOD and Green urbanism concepts should be developed. In this study, Geo-spatial Information Science and hierarchical fuzzy inference system (HFIS) were employed to calculate the indicators and aggregate them, respectively. In order to showcase the feasibility of the proposed method, it was implemented in a case study area in the City of Tehran, Iran. The result of this method is an integrated spatial GTOD index, which measures the neighbourhoods’ GTOD levels. These measurements specify weaknesses and strengths of neighbourhoods’ factors. Therefore, this index helps decision-makers to plan neighbourhoods based on land use and public transit views. Additionally, the HFIS method helps decision-makers to consider criteria and indicators with their inherent uncertainties and aggregate them with much fewer rules. For evaluating the results, the developed GTOD index was assessed with municipal action planning and attraction maps. According to the outcomes of the assessment, it is concluded that the proposed method is adequately robust and efficient for smart and sustainable urban planning.