Open Collections

Spectral Index Monitoring for Temporal Changes in Mining Areas

Tailings and Mine Waste Conference (2023 : Vancouver, B.C.); University of British Columbia. Norman B. Keevil Institute of Mining Engineering

Mining activities impact land cover, vegetation, and soil properties, which require effective monitoring approaches. The remote sensing technique offers a valuable tool for monitoring and analyzing temporal changes in mine sites in light of spectral indices. This study focuses on analyzing temporal changes in spectral indices at mine sites in Alberta, Canada, and the tailings dam failure site in Brumadinho, Brazil, using Sentinel-2 and Landsat-8 satellite imagery. In this study, spectral indices, including the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), the Normalized Difference Moisture Index (NDMI), and the Modified NDWI (MNDWI) are derived using the Google Earth Engine (GEE). Trend analysis and change detection algorithms are employed to assess the spectral and temporal variations in these spectral indices. The results reveal the changes in vegetation health, water presence, and moisture in mining areas. This integrated approach supports effective monitoring and decision-making in the mining industry and provides quantitative guidance for the safe operation and closure of mine sites. The study advances remote sensing techniques for efficient mine site monitoring and has broader applications in environmental and geotechnical contexts. It contributes to sustainable mining practices and remote sensing advancements for environmental assessments in Canada and worldwide.

Text

2023-12-08

Attribution-NonCommercialNoDerivatives 4.0 International

http://hdl.handle.net/2429/86840

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/4.0/