Streets play significant roles in meeting multiple sustainability objectives. This research addresses Abu Dhabi’s and Dubai’s street connectivity at the neighborhood (local) and city (global) scales. It focuses on two parameters of street network analysis: efficiency and centrality. Efficiency is evaluated in terms of directness, noting that network designs that provide short and direct access between origins and destinations are more efficient. Centrality is evaluated using graph theory metrics that enable the identification of high- and low-accessibility locations within networks. Research has shown that network centrality metrics are useful for capturing location advantage, a significant factor for land use distribution. An understanding of centrality and its impacts makes it possible to plan land uses that bring destinations closer to residences, an important factor in environmental, economic, and social sustainability. The proposed study will offer scientifically grounded strategies and policies that will enable various stakeholders to design more sustainable street systems and land uses. 

              Analysis for local scale has been completed for 13 neighborhoods. Six of these neighborhoods namely Al Bahya, Al Falah, Baniyas, Khalifa City, MBZ, and West Island AD are located in Abu Dhabi. While, eight neighborhoods namely Al Barsha, Al Satwa, Al Quoz, Al Rashidiya, Al Warqa, Creek area, and Jumeirah are located in Dubai. The evaluation of accessibility of the built environment was accomplished through the use of computational tools.

              The project utilizes a novel methodology that uses conventional morphological analysis (e.g., mapping and quantification of blocks, plot sizes, building density, and land uses) to build a foundation for conducting advanced computational studies. Spatial network analysis, namely Multiple Centrality Assessment and Urban Network Analysis (UNA), is used to evaluate various performance indicators that take into account spatial relationships and connections between different locations in urban space. Centrality assessment metrics like Reach, Straightness, Gravity, and Betweenness are calculated for each of the selected neighborhoods. For each neighborhood, these metrics are calculated for different radii like 400 meters, 800 meters, and 1600 meters for the local scale analysis. In addition, global scale analysis is carried out for the chosen neighborhoods to determine how metrics like reach, straightness, betweenness, etc. vary with increasing radii of 3,000 meters and 6,000 meters. In addition, advanced metrics like Closest Facility is also computed for all neighborhoods which provides new insights about the patronage of a destination like potential number of visitors for a commercial outlet. Advanced Betweenness is calculated which takes into account the population data associated with the origin points (i.e. estimated number of people living in a plot). Order and adaptability of street networks are also being measured/investigated. Order of street orientation is represented as the Shannon entropy. This value represents the level of order/disorder. The smallest value of φ is 0 which means complete disorder, while φ =1 means a perfect order. Adaptability of street network is characterized by a semi-lattice system which is in turn defined as overlapping.  The degree of movements on a street segment represents levels of overlapping activities in a street network. This value of movement is the value of betweenness centrality.

               For each neighborhood, maps are prepared for the illustration of aforementioned metrics and the spatial distribution of its values. First, local scale analysis is conducted at three scales- 400 meters, 800 meters, and 1600 meters corresponding to 5 minutes, 10 minutes, and 20 minutes’ walk respectively. Second, global scale analysis is conducted at 2000 meters, 5000 meters, and 10,000 meters. Broadly, the analysis is classified into two approaches- 1) All-to-all where all plots are considered as origins, and all plots simultaneously considered as destinations, and 2) Targeted Destinations where public facilities like hospitals and schools, or points of interest like parks and mosques, are set as destination points, while residences are set as origins. Four types of target destinations are used in this project namely Commercial (i.e. grocery stores, malls, laundry, typing center, etc.), Parks (i.e. big parks to small children parks), Educational (i.e. nurseries to universities), and Mosques. Furthermore, advanced spatial analysis was conducted twice for each metric in ArcGIS and Rhino with UNA tool; once by adding alleyways network into analysis, and once without the alleyway network.

 Articles

Alawadi, K., Khaleel, S., & Benkraouda, O. (2020). “Design and planning for accessibility: lessons from Abu Dhabi and Dubai’s neighborhoods”. Journal of Housing and the Built Environment, 1-34. https://doi.org/10.1007/s10901-020-09763-3

2)  Alawadi, K., Alameri, H., & Scoppa, M. (2020). Reclaiming alleyways to improve network connectivity: Lessons from Dubai’s neighborhoods. Journal of Planning Education and Research. https://doi.org/10.1177%2F0739456X20931907

3)      Alawadi, K., Khanal, A., El Doudin, A., & Abdelghani, R. Revisiting Transit-Oriented Development: Alleys as Critical Walking Infrastructure. Transport Policy. https://doi.org/10.1016/j.tranpol.2020.11.007

Alawadi, K., Khanal, A., Al Hinai, S. Rethinking suburban design: streets v/s alleys in improving network connectivity. Journal of Urban Design. https://doi.org/10.1080/13574809.2021.1921570

 Alawadi, K., Hong Nguyen, N., Alrubaei, E., & Scoppa, M. Streets, density, and the superblock: neighborhood planning units and street connectivity in Abu Dhabi. Journal of Urbanism: International Research on Placemaking and Urban Sustainability  https://doi.org/10.1080/17549175.2021.1944281

Alawadi, K., Hong Nguyen. N., & Mariam J. The Edge and the Center in Neighborhood Planning Units: assessing permeability and edge attractiveness in Abu Dhabi. Transportation, 1-29. https://doi.org/10.1007/s11116-021-10257-6