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Title: Temporal multispectral and 3D analysis of Cerro de Pasco, Peru

Abstract

Mining operations across the world often lead to contamination of land, water resources, ecosystems and in some cases, entire communities.Results of recent health and ground sampling studies revealed extensive lead contamination within the populace and around the City of Cerro de Pasco, Peru. Tailings excavated from a large open pit zinc mine in the center of the city have been aggregated in four large stockpiles within close proximity to neighborhoods, schools, and hospitals. Visual comparison of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) imagery from 2001 and Sentinel-2 imagery from 2018 suggests a size increase in one tailing stockpile in particular near the neighborhood of Paragsha. Due to ongoing mining efforts, the hypothesis motivating the work presented here is that Pb-bearing minerals would be detectable through multispectral analysis, an increase in Pb mineral percent abundance would be observed and tailing stockpile volume would be detectable between 2001 and 2016. This hypothesis is tested using Spectral Angle Mapper (SAM), Adaptive Coherence Estimator (ACE), and Jeffries-Matusita distance calculation on ASTER (2001) and Sentinel-2 (2018) VNIR and SWIR bands. Volume and area estimate of tailing stockpiles were calculated using a photogrammetrically derived point cloud. SAM detected the presence of five Pb-bearing mineralsmore » around Cerro de Pasco and Paragsha. The results of the temporal SAM analysis displayed an increase of approximately 17% of Pb-bearing minerals around the greater Cerro de Pasco city area and approximately 11% for the neighborhood of Paragsha. Jeffries-Matusita distance results suggest clear correlation between contamination sources and affected locations. Total tailing stockpile volume was measured to be approximately 200,300,000 m3. Volume for Pile 4 was estimated to have increased by approximately 46,000,000 m3 between 2001 and 2018. Lastly, these presented results will hopefully inspire and guide future remote sensing campaigns, perhaps involving a UAV or aircraft-based hyperspectral instrument.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [2];  [3]
  1. Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. Univ. of Tennessee, Knoxville, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1606695
Alternate Identifier(s):
OSTI ID: 1692051
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Science of the Total Environment
Additional Journal Information:
Journal Volume: 706; Journal Issue: C; Journal ID: ISSN 0048-9697
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; multispectral analysis; ASTER; Sentinel-2; Pb contamination

Citation Formats

Melton, Chad A., Hughes, David C., Page, David L., and Phillips, Michael S.. Temporal multispectral and 3D analysis of Cerro de Pasco, Peru. United States: N. p., 2019. Web. https://doi.org/10.1016/j.scitotenv.2019.135640.
Melton, Chad A., Hughes, David C., Page, David L., & Phillips, Michael S.. Temporal multispectral and 3D analysis of Cerro de Pasco, Peru. United States. https://doi.org/10.1016/j.scitotenv.2019.135640
Melton, Chad A., Hughes, David C., Page, David L., and Phillips, Michael S.. Mon . "Temporal multispectral and 3D analysis of Cerro de Pasco, Peru". United States. https://doi.org/10.1016/j.scitotenv.2019.135640. https://www.osti.gov/servlets/purl/1606695.
@article{osti_1606695,
title = {Temporal multispectral and 3D analysis of Cerro de Pasco, Peru},
author = {Melton, Chad A. and Hughes, David C. and Page, David L. and Phillips, Michael S.},
abstractNote = {Mining operations across the world often lead to contamination of land, water resources, ecosystems and in some cases, entire communities.Results of recent health and ground sampling studies revealed extensive lead contamination within the populace and around the City of Cerro de Pasco, Peru. Tailings excavated from a large open pit zinc mine in the center of the city have been aggregated in four large stockpiles within close proximity to neighborhoods, schools, and hospitals. Visual comparison of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) imagery from 2001 and Sentinel-2 imagery from 2018 suggests a size increase in one tailing stockpile in particular near the neighborhood of Paragsha. Due to ongoing mining efforts, the hypothesis motivating the work presented here is that Pb-bearing minerals would be detectable through multispectral analysis, an increase in Pb mineral percent abundance would be observed and tailing stockpile volume would be detectable between 2001 and 2016. This hypothesis is tested using Spectral Angle Mapper (SAM), Adaptive Coherence Estimator (ACE), and Jeffries-Matusita distance calculation on ASTER (2001) and Sentinel-2 (2018) VNIR and SWIR bands. Volume and area estimate of tailing stockpiles were calculated using a photogrammetrically derived point cloud. SAM detected the presence of five Pb-bearing minerals around Cerro de Pasco and Paragsha. The results of the temporal SAM analysis displayed an increase of approximately 17% of Pb-bearing minerals around the greater Cerro de Pasco city area and approximately 11% for the neighborhood of Paragsha. Jeffries-Matusita distance results suggest clear correlation between contamination sources and affected locations. Total tailing stockpile volume was measured to be approximately 200,300,000 m3. Volume for Pile 4 was estimated to have increased by approximately 46,000,000 m3 between 2001 and 2018. Lastly, these presented results will hopefully inspire and guide future remote sensing campaigns, perhaps involving a UAV or aircraft-based hyperspectral instrument.},
doi = {10.1016/j.scitotenv.2019.135640},
journal = {Science of the Total Environment},
number = C,
volume = 706,
place = {United States},
year = {2019},
month = {12}
}