EVALUATION OF LANDSCAPE DESIGNS AT MICROECONOMIC LEVEL WITH ARTIFICIAL INTELLIGENCE

Abstract

Landscape design is increasingly central in urban areas due to the growing need for functional, aesthetically pleasing, and sustainable spaces. This study examines the sustainability of designs that consider ecological values such as biodiversity and energy efficiency. Additionally, it explores how landscape areas can achieve a microeconomic level, defined as a design approach that maximizes environmental efficiency while minimizing costs. Microeconomic designs are minimalist approaches that integrate environmental efficiency, social benefits, and functional landscape features into urban planning. These designs aim to create spaces that are not only ecologically sound but also economically viable in the long term. In this context, the study prioritizes factors such as energy consumption and water use to ensure the sustainability of landscape designs. The criteria for microeconomic landscape designs were determined based on extensive literature research, providing the basis for selecting the most appropriate measures. These criteria have been transformed into landscape designs within an artificial intelligence environment. Artificial intelligence has been integrated with a systematic evaluation method to assess the success of the emerging designs. The evaluation criteria include various factors that contribute to the effectiveness of the design. Ultimately, the study emphasizes that low-cost, environmentally friendly landscape designs have the potential to improve both ecological balance and public health. Furthermore, the proposed methodological approaches offer practical guidance for landscape professionals and designers working on sustainable urban projects with the use of artificial intelligence.