A GIS-based Approach to Urban Bioclimatic Design and Human Use of Open Public Spaces

Urban open public spaces (OPS) play an important role on preserving population’s wellbeing. Levels of usage and occupancy at urban OPS highly depend on their environmental quality. Poor comfort conditions might negatively impact on expected occupancy levels. Urban design’s main concern is to provide sufficiently comfortable conditions for making OPS enjoyable and attractive to their users. Thus, a deep understanding of the influence of comfort conditions on occupancy becomes essential for supporting efficient design decision-making.

Most of current models for predicting occupancy patterns at urban OPS explain preference for locations based on the influence of morphological properties of the built environment, either the visual structure or the network configuration. By assuming experience of space as merely visual, these models, overlook the influence of non-visual aspects of urban ambience. Thermal comfort models, on the other hand, are either theoretical, based on human body thermoregulatory response, or empirical, based on fieldwork studies of populations’ adaptation to thermal changes.

These models are unable of capturing uncertainties inherent to human thermal sensation, neither combining thermal response with knowledge from different sources. In addition, the majority of currently applied design tools are limited to performance evaluation of alternatives with little ability for generating improved design solutions. As consequence, there is a need for a predictive model of occupancy pattern capable of integrating different influences of urban ambience for supporting design decision-making through each stage of the design process.

The research couple geographical information systems (GIS) with fuzzy logic inference system (FIS) to develop a flexible and dynamic model for generating design alternatives, aimed to improve thermal comfort conditions together with knowledge on human responses to other environmental variables and management of the associate uncertainties. The model was developed and assessed employing an urban OPS in the city of Haifa, Israel, by combining universal thermal comfort index (UTCI) with a measure of the visual structure of the environment. Results indicate that the model provides with good estimate of the potential occupancy pattern at OPS, and supports the design decision making process. The model’s performance for supporting design decision-making was studied and evaluated with a case study of an OPS in Tel Aviv city, Israel.

The model assisted the generation of an improved design alternative, demonstrating its ability for implementing environmentally conscious solutions.