Integrating soil heavy metal risk into ecological quality assessment: The pollution-enhanced remote sensing...

Soil contamination by hazardous heavy metals (e.g., As, Hg, Cd, Cu, Ni, Pb, and Zn) in polymetallic mining areas poses severe risks to ecosystem integrity and human health. Conventional Remote Sensing Ecological Indices (e.g., RSEI) rely primarily on physical surface features, thus failing to capture the "invisible" chemical toxicity and site-specific ecological risk (RI) associated with heavy metals. To overcome this disconnect between spectral indices and soil geochemical hazards, this study proposes a Pollution-Enhanced Remote Sensing Ecological Index (PE-RSEI). Using the Shizhuyuan mining area as a case study, a Remote Sensing Potential Ecological Risk Index (RRI) was first constructed by coupling 94 field soil samples with long-term multispectral imagery (1997-2024) via Random Forest regression. The RRI model achieved high accuracy (R² = 0.86) in reflecting the spatiotemporal distribution of surface heavy metal risks, but it remains a data-driven index and does not directly quantify absolute concentrations or chemical speciation. Subsequently, the RRI was integrated into the RSEI framework to generate the PE-RSEI, allowing for a dynamic assessment of ecological quality partially constrained by heavy metal pollution. Results indicate that while the overall ecological condition showed slight recovery, high-risk degradation zones remain concentrated in active mining and built-up areas (16 km²). Compared to the traditional RSEI, PE-RSEI demonstrated superior robustness, with a 21.6% increase in information density and reduced temporal variance, although its reliability depends on sampling density, heavy metal types, and regression methods.This study provides a novel, scalable, and quantitative framework for preliminary monitoring of hazardous material risks in mining regions, offering critical data support for pollution control and land reclamation, and providing a scientific basis for informed ecological management in areas affected by heavy metal contamination.