Next Article in Journal
Spatio-Temporal Variation and Impact Factors for Vegetation Carbon Sequestration and Oxygen Production Based on Rocky Desertification Control in the Karst Region of Southwest China
Previous Article in Journal
An Assessment of the Cultivated Cropland Class of NLCD 2006 Using a Multi-Source and Multi-Criteria Approach
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2016, 8(2), 100; doi:10.3390/rs8020100

Characterization of Black Sand Mining Activities and Their Environmental Impacts in the Philippines Using Remote Sensing

1
Department of Geology, State University of New York at Buffalo, Buffalo, NY 14260, USA
2
Department of Political Science, University of California, San Diego, La Jolla, CA 92110, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Zhong Lu and Prasad Thenkabail
Received: 20 October 2015 / Revised: 31 December 2015 / Accepted: 20 January 2016 / Published: 28 January 2016
View Full-Text   |   Download PDF [12459 KB, uploaded 28 January 2016]   |  

Abstract

Magnetite is a type of iron ore and a valuable commodity that occurs naturally in black sand beaches in the Philippines. However, black sand mining often takes place illegally and increases the likelihood and magnitude of geohazards, such as land subsidence, which augments the exposure of local communities to sea level rise and to typhoon-related threats. Detection of black sand mining activities traditionally relies on word of mouth, while measurement of their environmental effects requires on-the-ground geological surveys, which are precise, but costly and limited in scope. Here we show that systematic analysis of remote sensing data provides an objective, reliable, safe, and cost-effective way to monitor black sand mining activities and their impacts. First, we show that optical satellite data can be used to identify legal and illegal mining sites and characterize the direct effect of mining on the landscape. Second, we demonstrate that Interferometric Synthetic Aperture Radar (InSAR) can be used to evaluate the environmental impacts of black sand mining despite the small spatial extent of the activities. We detected a total of twenty black sand mining sites on Luzon Island and InSAR ALOS data reveal that out of the thirteen sites with coherence, nine experienced land subsidence at rates ranging from 1.5 to 5.7 cm/year during 2007–2011. The mean ground velocity map also highlights that the spatial extent of the subsiding areas is 10 to 100 times larger than the mining sites, likely associated with groundwater use or sediment redistribution. As a result of this subsidence, several coastal areas will be lowered to sea level elevation in a few decades and exposed to permanent flooding. This work demonstrates that remote sensing data are critical in monitoring the development of such activities and their environmental and societal impacts. View Full-Text
Keywords: black sand mining; magnetite; Philippines; optical remote sensing; InSAR; subsidence black sand mining; magnetite; Philippines; optical remote sensing; InSAR; subsidence
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Chaussard, E.; Kerosky, S. Characterization of Black Sand Mining Activities and Their Environmental Impacts in the Philippines Using Remote Sensing. Remote Sens. 2016, 8, 100.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top