Advanced ecosystem restoration: Blending phytoremediation with satellite-based and non-imaging based remote sensing in the Himalayas of PIN Valley National Park, India

Heavy metal pollution poses significant threats to global ecosystems, impacting biodiversity, soil and water quality, and human health. Traditional remediation methods often fall short, especially in ecologically sensitive regions. In response, phytoremediation offers a sustainable solution, leveraging plant species that naturally absorb heavy metals. This study explores the effectiveness of phytoremediation in Pin Valley National Park, Himachal Pradesh, India, integrating advanced remote sensing techniques—proximal, airborne, and space-borne data collection—to assess contamination levels and monitor environmental changes from 2010 to 2023. Proximal sensing utilized a spectroradiometer for high-resolution spectral data collection, while drones facilitated vast coverage, and satellites (Landsat-8, Landsat-9, and Sentinel-2) provided extensive temporal and spatial data. Vegetation and environmental health were analyzed using various indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge (NDRE), and Soil-Adjusted Vegetation Index (SAVI). These indices indicated plant vigor and environmental degradation. The Heavy Metal Index, Iron-Oxide Index, and Hydrothermal Index measured contamination levels, revealing significant correlations between heavy metal concentrations and vegetation stress markers. Results indicated a notable relationship between high NDVI values and low heavy metal concentrations, underscoring the efficacy of phytoremediation. Species like Indian mustard (Brassica juncea) and hemp (Cannabis sativa) emerged as key players in metal uptake, with Brassica juncea showing biomass lead accumulation of up to 2,500 mg/kg and Cannabis sativa exhibiting cadmium uptake of 900 mg/kg. The study identified minimal levels of heavy metals, such as Yttrium (3-11 ppb), Strontium (20-32 ppb), and Cadmium (0.045-0.170 ppb), across site locations.The application of remote sensing technology enabled precise mapping of metal concentrations and plant health, optimizing phytoremediation efforts. Longitudinal data revealed increasing NDVI values in reclaimed areas, rising from 0.35 to 0.65, indicating improved vegetation health and cover. Corresponding reductions in Heavy Metal Index values confirmed a decrease in contamination levels. This underscores remote sensing's critical role in ongoing environmental monitoring—rapidly identifying contamination hotspots, optimizing plant selection, and efficient resource allocation while ensuring reliable results across various scales. In conclusion, this research validates the effectiveness of combining phytoremediation with remote sensing technologies to address heavy metal contamination. The study’s framework is adaptable to various ecological contexts and contaminant profiles, highlighting its potential as a practical tool for environmental restoration worldwide. The findings contribute significantly to academic knowledge while offering actionable insights for policymakers and environmental managers dedicated to preserving ecosystems and promoting ecological resilience and sustainability. Continued refinement of these technologies will enhance global efforts to combat heavy metal pollution and support sustainable land management practices.

Keywords: Environmental Monitoring, Metal contamination, Phytoremediation, Pin Valley NP, Hyperspectral, Normalized Difference Red Edge Index (NDRE), Normalized Difference Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Strontium, Rubidium, Yttrium