Developing Of An Urban Environmental Quality Indicator

Abstract

Human intervention on vegetation cover has always had a negative impact on the environment, directly affecting the quality of life in urban areas. Therefore, this study aimed to develop a methodology for the construction of an urban environmental quality indicator (UEQI) that could reflect the environmental quality of urban areas considering the vegetation conditions to which the resident population is exposed. For this, the method sought to integrate data on demographic density (Dd), leaf area index (LAI), normalized difference vegetation index (NDVI), and surface temperature (St). The Mamdani fuzzy inference system was used to generate a rule base containing 108 variations and a defuzzed output with five condition classes, ranging from very bad to excellent. The results showed that the studied area is characterized by a very bad to good UEQI, with most neighbourhoods having poor conditions (64.51%) and only two with good conditions. It was found that in general the studied area has unsatisfactory environmental quality, showing the need for initiatives aimed at urban afforestation in order to improve the quality of life for the studied population. It can be concluded that UEQI proved to be an efficient tool to identify priority areas for the planning and management of vegetation cover in urbanized areas, enabling the improvement of people's living conditions.

Keywords

• vegetation indexes
• population dynamics
• urban areas
• fuzzy logic