Geometric Patterns of Daylight Distribution and Sensory Perceptions of Residents in Residential Buildings

Volume 21, Issue 134
August 2024
Pages 5-20

Document Type : Original Research Article

Authors

1 Ph.D. Candidate in Architecture, Faculty of Architecture and Urban Planning, Shahid Rajaee Teacher Training University, Tehran, Iran.

2 Associate Professor of Architecture, Faculty of Architecture and Urban Planning, Shahid Rajaee Teacher Training University, Tehran, Iran.

Abstract
Problem statement: Daylight is inherently dynamic and variable, which, depending on the architectural design characteristics of light-transmitting surfaces, especially their geometry, can create different patterns of light and shadow within the interior space. This, in turn, can affect the senses and sensory perceptions of residents, manifesting through their emotional responses and providing a distinctive and meaningful spatial experience. However, it appears that contemporary residential buildings do not provide an optimal level of perceptual effects of daylight in interior spaces for their residents. This may be due to architects’ lack of systematic, clear, and precise awareness of the perceptual effects of daylight.
Research objective: This study aims to explain the relationship between geometric patterns of daylight distribution and the sensory perceptions of residents, as well as to identify the most reliable numerical indices for image processing to predict the relationship between these two aspects within the context of residential buildings.
Research method: This study has been conducted using a survey research method and an image processing method in a simulated environment.
Conclusion: The survey findings indicate that changes in the geometric patterns of daylight distribution significantly alter the average sensory perception assessment indices. This highlights the importance for architects to consider and manipulate the geometry of light-transmitting surfaces to create desirable environmental sensations. Additionally, the correlation findings between the survey research and the studied image processing indices suggest that the Michelson, mean-RMS, Fractal D, GIF file size, and RAW-PRIM8 indices are the most reliable for predicting pleasantness. The TIFF-SOBEL, JPEG-PERIM8, Michelson, JPEG file size, and PNG file size indices are the most reliable for predicting attractiveness. The TIFF-SOBEL, Mean mSC, JPEG-PERIM8, JPEG file size, and JPEG-PERIM4 indices are the most reliable for predicting excitement. The RAW-PRIM4, RAW-PRIM8, Michelson, Fractal D, and CANNY 2014-RAW indices are the most reliable for predicting spatial calmness.

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