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Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis
The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world’s largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa Ri...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5057129/ https://www.ncbi.nlm.nih.gov/pubmed/27725748 http://dx.doi.org/10.1038/srep35129 |
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author | Alonzo, Michael Van Den Hoek, Jamon Ahmed, Nabil |
author_facet | Alonzo, Michael Van Den Hoek, Jamon Ahmed, Nabil |
author_sort | Alonzo, Michael |
collection | PubMed |
description | The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world’s largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to “peer through” atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km(2) of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson’s r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events. |
format | Online Article Text |
id | pubmed-5057129 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-50571292016-10-24 Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis Alonzo, Michael Van Den Hoek, Jamon Ahmed, Nabil Sci Rep Article The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world’s largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to “peer through” atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km(2) of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson’s r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events. Nature Publishing Group 2016-10-11 /pmc/articles/PMC5057129/ /pubmed/27725748 http://dx.doi.org/10.1038/srep35129 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Alonzo, Michael Van Den Hoek, Jamon Ahmed, Nabil Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis |
title | Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis |
title_full | Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis |
title_fullStr | Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis |
title_full_unstemmed | Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis |
title_short | Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis |
title_sort | capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5057129/ https://www.ncbi.nlm.nih.gov/pubmed/27725748 http://dx.doi.org/10.1038/srep35129 |
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