Development of an ecological greenness index (EGI) for urban environmental monitoring: a remote sensing and multivariate analytical approach

Abstract Several remote sensing-based indices have been proposed. While most measures are disjointed, several integrated ecological indices are offered. The purpose of this study is to introduce an Ecological Greenness Index (EGI) as a composite and integrated ecological index. This index was established by combining eight remote sensing-derived indices, including NDVI, NDSI, NDBI, LST, LAI, and three Tasseled Cap indices. Principal Component Analysis (PCA) was used to reduce dimensionality among RS-based derived components. The PCA eigenvalues were used as weights in the fuzzy logic method. The fuzzy logic overlay method was used to combine the retained components and produce the final EGI map. The results showed that four principal components (SIPC1–SIPC4), which explained about 99.99% of the total variance, were used for the final EGI construction. The EGI was implemented and internally assessed in Tehran, Iran, as a case study. The eigenvalue (λ) of each retained SIPC was used to derive the component weights for EGI construction. The results revealed substantial regional heterogeneity: the mean quantity of EGI in Tehran’s northern area was 0.29 (e.g., District 1), while it reduced to 0.076 in southern districts (e.g., District 10). A north–south transect analysis confirmed a steep ecological gradient across the city. EGI integrated vegetation structure, soil exposure, moisture, thermal conditions, and built-up characteristics within a unified PCA–fuzzy framework. It provides a broader diagnostic representation of urban ecological greenness. Zonal statistics depicted the spatial variation of EGI across Tehran’s 22 administrative districts. Despite the limitations of this study, such as using single-season and 30 m resolution satellite data, the EGI provides a quantitative framework for monitoring urban ecology. It represents a potentially useful tool for cities facing rapid urbanization and ecological greenness changes. Based on this case study, the EGI framework has the potential to be used as an integrated environmental quality assessment tool. The EGI integrating multiple ecological dimensions that may complement established indices such as the Remote Sensing-based Ecological Index (RSEI) in complex urban environments. Generalization of the EGI requires independent validation across additional urban contexts.