2022-ongoing

Funding agency: Technion Data Science Initiative

Research leaders: Or Aleksandrowicz, Avigdor Gal

Researchers: Daniel Rosenberg, Uriel Cohen, Shaked Fried, Lior Motola, Ariel Novominsky, Menachem Brief

The aim of the research project was to use large-scale user window blind-control datasets to better understand and predict occupants’ visual comfort preferences and their possible effect on building energy consumption. We have been able to systematically clean and process a raw dataset of 339 blind controllers installed on the three upper floors of an office building in Tel Aviv to infer the automated blind operation schedules on different building facades. The automated operation of a blind depends on the solar orientation of the façade it is installed in, following a solar calculator that considers the date, time, orientation, and geographic location of the building. Based on the dataset analysis, we were able to create user intervention “heat maps” showing the frequency of user override of the automated blind operation at different time scales: annual, monthly, and daily. These graphic presentations of the data thus enabled us to better trace similarities and differences in user behaviour and to define different “user types” who show recurring patterns of intervention.

2022-ongoing

Funding agency: Center for Humanities and AI

Research leaders: Or Aleksandrowicz, Maoz Azaryahu

Researchers: Anat Goldman, Daniel Rosenberg, Yoav Orion, Iddo Baum

The project aimed to produce rigorous evidence about the emergence and adoption of architectural modernism in residential building design in Tel Aviv through systematic examination of all the buildings (about 7,000 in number) that were constructed in the city between 1921 and 1940. This evidence was used for understanding the historical context and motivations behind the introduction and adoption of the modernist architectural idiom in Tel Aviv and for the identification of individual architects who played a key role in that process. Based on these findings, we also sought to evaluate to what extent the adoption of the architectural modernist idiom in Tel Aviv was motivated by ethical and ideological reasons, or whether other factors were involved in this process.

2021

Funding agency: Israel100 Initiative

Research leader: Or Aleksandrowicz

Developer: Ezra Ozery

 

To date, there is a lack of orderly and data-based methods for quantifying, evaluating, and benchmarking street-level outdoor shade in streets and urban public spaces. The lack of such methods impedes the effective design of walkable and liveable outdoors in locations where shading is essential for significantly mitigating outdoor heat stress. To address this shortcoming, we have developed Kikayon, a relatively simple parametric tool that allows planners and designers to easily compare the effect of design alternatives on outdoor shade provision based on building geometry and tree canopy morphologies while taking into account the variance of exposure to solar radiation at different times. The tool calculates several shade and tree indices, some we have originally developed, for each street design, giving users quick and straightforward feedback and enabling them to quantitatively compare design alternatives. Our tool is implemented as a Grasshopper code that harnesses several components of the Ladybug Tools suite.

2019-2023

Funding agency: Israel Science Foundation

Research leader: David Pearlmutter

Researchers: Or Aleksandrowicz, Michelle Clark Levenson, Tanya Saroglou, Morel Weisthal, Wolfgang Mutsafi-Heller

Research assistants:  Tzur Blank, Yaakov Florentin, Yosef Mor

The primary aim of this research project was to address a significant gap in our ability to map pedestrian thermal stress in cities. This gap involves the modelling of urban microclimate at a scale which is relevant for human thermal comfort, on the one hand, and the need for continuous spatial analysis by urban planners, on the other. The existing conflict between high-resolution scientific analysis and broad spatial coverage is essential to confront if we are to successfully apply scientific data and understanding in urban planning processes. The approach we attempted to adopt in this project was to create a single computational data analysis platform that will enable planning professionals to evaluate heat stress of pedestrians relatively easily in streets and open urban spaces. While developing this platform, we acknowledged the need to significantly reduce calculation complexity without compromising the qualitative insights that can be derived from them about outdoor heat stress. Additionally, we attempted to make the analysis results more accessible to planners and designers by focusing on generating easy-to-read, high-resolution maps that can be effectively used for spatial analysis without the need to have a solid understanding of complex microclimatic phenomena.

2017-2021

Funding agency: Tel Aviv-Yafo Municipality

Research leaders: Or Aleksandrowicz, Shachar Zur, Yonatan Lebendiger, Yoav Lerman

The project attempted to apply state-of-the-art mapping technologies and calculation algorithms for high-resolution city-scale analysis of urban shade. This was done by developing several indices that can be used for comparing the microclimatic characteristics of streets and neighbourhoods across a city. 

To calculate spatial shade indices, we first had to perform a calculation of solar insolation at street level using the Area Solar Radiation function in ArcMap, based on 2.5D mapping of all the buildings and trees in Tel Aviv-Yafo. Using the results of this calculation, we were able to calculate a Shade Index (SI) value for each pixel in the provided mapping, which describes, on a scale of 0 to 1, the ratio between the blocked insolation at a certain location and the maximal insolation of an unobstructed horizontal surface at the same time and location. The lower the exposure to direct solar radiation, the higher the SI value. 

One of the city-scale maps we produced using the SI calculation procedure was a map showing average SI values for every street segment in the city during summer (specifically, in the month of August). The map highlighted the climatic advantages of north-south oriented streets over east-west oriented streets in terms of summer shade. This is a result of the local characteristics of the sun path: in east-west oriented streets, buildings’ effect on street shading is minor (since the summer southern sun appears high in the sky), and therefore reasonable SI values cannot be achieved without the application of a substantial and continuous layer of wide tree canopies.

Following the analysis of shade conditions at street and neighbourhood levels, we proposed a method for prioritizing municipal action towards urban shade management based not only on street-level microclimatic conditions but also on walkability potentials within the urban street network.

For more information on the way shade maps are calculated and used, click here.

A comprehensive set of shade maps and tree maps developed for the Tel Aviv-Yafo Municipality can be accessed here.

2022-ongoing

Funding agencies: National Library of Israel and Yad Hanadiv (POC)

Research leader: Or Aleksandrowicz

Developers: Daniel Rosenberg, Ivan Vasilyev

Researchers: Elad Horn, Yoav Orion

 

The growing quantities of digitized photographs create new opportunities to overcome the inherent difficulties of collecting visual place-related data from a multiplicity of sources, precisely because digitization can offer uniform platforms for data storage, categorization, extraction, and presentation. Nevertheless, as large collections of digitized historical photographs have been created and made available via the internet, it became evident that there are two major inherent problems with the way such data is currently indexed, stored, and made accessible.

The first challenge emanates from the need to systematically add precise geographic reference to each digitized item to efficiently retrieve it based on its geographic location. When processing large datasets this task can become daunting, if not unfeasible by relying only on the human resources of the institutions that manage collections of digital data. Secondly, the hurdles of place-related data extraction are further exacerbated because verbal descriptions of locational data are frequently inaccurate or incomplete. This can be attributed to the inaccurate or incomplete nature of verbal descriptions of source materials assigned to the items by their original creators but can also reflect the more basic limitations resulting from the act of verbally describing places. Even when we know the exact geographic location embedded in a digitized item the words we use to make sense of it may exclude important pieces of information that are essential for conveying its cultural significance as a place.

To overcome these two challenges, we have developed an online indexing and presentation platform (named MAQOM) that consists of a map-based search interface capable of simultaneously presenting and efficiently browsing through a variety of media sources, including digitized photographs. The users retrieve the place-related items by clicking on the interactive map and can filter the presented items via free-text search or by actively changing the geographic extents or the temporal range of the presented search results. To overcome the inherent practical limitations of large-scale georeferencing of digitized items, we suggest exploiting the power of crowdsourcing for collecting geographic and verbal place-related input from users from outside the institutions managing the photo collections. While this approach is more prone to errors than institutional indexing methods, open user feedback is expected to correct many of these errors more easily than keeping indexing behind the closed walls of institutional authority, which is always based on limited human resources and limited expertise when compared to the public’s participation in open data collection efforts.

2022-2024

Funding agency: Israel Innovation Authority

Research leader: Or Aleksandrowicz

Project supervisors: Daniel Rosenberg, Omri Shafer-Raviv

Project advisors: Noam Ordan, Nick Howell

Project assistants: Dina El Qasem, Hodaya Saada, Mai Sabbah, Sherry-Atara Khasdan, Naama Koren, Shiran-Ester Shnaiderman

The construction industry is one of the main economic sectors in Israel and it is expected to maintain its central position in the coming decades in light of the country’s rapid population growth rate. Unlike many developed countries, where the rate of new construction is slow due to low rates of population growth, in Israel, the built-up area doubles every 25 years. The creation of a textual corpus in Hebrew on construction, planning, and architecture is expected to facilitate and expedite the development of NLP-based tools for application and assimilation in technological fields related to the construction industry.

The corpus consists of Hebrew documents from a wide variety of contemporary and historical sources, including legislative decrees, regulatory guidelines, research reports, academic studies, and professional journals. In the development of the corpus, we are using digitally born as well as scanned printed publications, which go through a process of optical character recognition (OCR), cleaning, and parsing. Parsing was performed using the Trankit Python Toolkit.

The corpus holds 22,382,594 words in 1218 documents.

The corpus is available for all types of uses for NLP research and development according to the CC BY 4.0 license (Attribution 4.0 International).

We wish to thank Vicky Davydov, Lena Avrahami and Shai Zack from the Library of the Faculty of Architecture and Town Planning (Technion), as well as Moti Yeger, Director of the Technion’s Central Library, and Prof. Rafael Sacks, Head of the National Building Research Institute, for the help they have been providing for the project since its inception.

Cite: Aleksandrowicz, O., Rosenberg, D., Shafer-Raviv, O., Ordan, N. (2024). Hebrew textual corpus on construction, planning, and architecture. GitHUB. https://github.com/bdar-lab/heb_architecture_corpus.

 

2022-2024

Funding agency: Yad Hanadiv

Research leaders: Or Aleksandrowicz and David Pearlmutter

Researchers: Naama Shapira, Michelle Clark Levenson, Shachar Zur

Shading in the urban environment is closely related to the planning and design of built-up spaces. In certain street orientations, the design of buildings can result in good shading conditions along the sidewalks. However, in many cases, it is necessary to use additional elements such as pergolas, shading fabrics, and especially street trees to secure even reasonable levels of shade. Shade promotion using trees, as a central part of Israel’s policy towards adaptation to global warming, also lies at the centre of the Israeli Government’s Resolution 1022 of 23 January 2022. Yet, the national strategic plan for shading and cooling of urban spaces published at the end of 2022 included an implicit acknowledgement of the methodological difficulties inherent in the implementation of the government’s decision from the beginning of that year. The plan recognized that there is still a lack of an established scientific methodology for determining urban shading and forestry goals and for defining the mapping needs arising from these goals. In the absence of such a methodology, all the factors involved in promoting the decision will have difficulty in efficiently and effectively implementing the planting of shade trees in Israeli cities, monitoring the progress of operations in this area, and directing resources to places where they are mostly needed.

The purpose of this project was to present a systematic methodology for promoting strategic shading programs in urban spaces and to provide planning bodies and planners with indicators for quantitative and qualitative assessment of existing and future shading levels according to various planning scenarios. We suggested starting strategic planning with comprehensive shade mapping using a method we had developed in previous projects and prioritising intervention according to the mapping results. Detailed intervention should follow a new grading system according to a new quantitative index, the Shade Availability Index (SAI), which emphasizes the conditions of shading on sidewalks. We proposed to establish three ascending levels of SAI (reasonable, very good, and excellent) that should serve for setting municipal shading goals in different streets. In addition to the description of the index and the goals derived from it, the work also contained systematic demonstrations of the application of the index in different planning scenarios and an analysis of the applicability of meeting these goals in real-life design of streets in Israel.