Proposing the Urban Plant Suitability Index (UPSI): A Multi-Criteria Framework for Selecting Flora in Tropical Urban Ecosystems

Rapid urbanization in tropical cities has led to severe environmental degradation, including air and noise pollution, and the urban heat island effect. While urban greening is a proven mitigation strategy, the selection of plant species is often arbitrary, lacking a scientific basis for suitability in challenging urban environments. This paper proposes a novel, data-driven framework called the Urban Plant Suitability Index (UPSI) to address this gap. The UPSI is a composite index built on eight critical parameters: Air Pollution Tolerance Index (APTI), Carbon Sequestration Potential (CSP), Particulate Matter (PM) Interception, Noise Reduction Potential (NRD), Root System Integrity (RSI), Drought & Heat Tolerance (DHT), Low Maintenance (LM), and Allergenic Potential (AP). Weights for these parameters were derived using the Analytical Hierarchy Process (AHP) to ensure objectivity. The index was applied to 15 plant species common in Tamil Nadu, India, using data collected through a comprehensive review of existing literature and botanical databases. The results provide a baseline ranking of species, with Azadirachta indica and Pongamia pinnata emerging as top performers. Furthermore, scenario-based analysis demonstrates the UPSI's utility as an adaptable decision-support tool for urban planners, generating context-specific rankings for different urban zones, such as pollution hotspots and infrastructure-sensitive areas. The UPSI provides a robust, transparent, and replicable methodology for optimizing plant selection, thereby enhancing the long-term success and ecological benefits of urban greening initiatives. • A novel Urban Plant Suitability Index (UPSI) is proposed for selecting urban flora. • The index integrates 8 ecological and resilience parameters using AHP for weighting. • Azadirachta indica and Pongamia pinnata ranked highest for general suitability in Tamil Nadu. • Scenario-based analysis demonstrates the UPSI as a dynamic decision-support tool.