Urban EcoScore index-based assessment of biophilic potential and habitat-structural condition of the Kolkata metropolitan area

Abstract

Urban sustainability assessment is crucial due to rapid urbanisation and environmental stress, particularly in the Kolkata Metropolitan Area (KMA), where land-use changes contribute to ecological degradation. This research develops and assesses the Urban EcoScore Index (UESI) as a method for evaluating biophilic potential and habitat-structural condition in the KMA, integrating six ecological indicators across three dimensions: ecological integrity, anthropogenic pressure, and spatial proximity to natural features. Each indicator is oriented a priori to a common ecological direction before aggregation, and indicator weights are derived through Principal Component Analysis rather than expert judgement. The assessment employs remote sensing and machine learning techniques to model ecological relationships and uses explainable AI methods, such as SHAP, to interpret these models. The UESI assessment showed pronounced spatial disparities across the KMA, with 21.9% (384 km 2 ) of the area classified as Poor, concentrated in urban cores. In contrast, 24.7% (433 km 2 ) fell under the Good category, while 8.6% (151 km 2 ) achieved Excellent conditions (UESI > 0.8), mainly in ecologically sensitive zones. Intermediate Fair (445 km 2 , 25.4%) and Moderate (339 km 2 ) zones indicate transitional areas where restoration could enhance ecological function. SHAP-based decomposition identified potential species richness and human disturbance as the indicators contributing most to the composite's spatial variability, consistent with the broader evidence on biodiversity and land use in urban ecology. UESI serves as a screening-level diagnostic for biophilic potential but does not assess actual human-nature interactions, biodiversity, or distributional equity, as these necessitate field surveys and socio-demographic data beyond the remote-sensing proxies utilized.