

Author: Chaussard Estelle Kerosky Sara
Publisher: MDPI
E-ISSN: 2072-4292|8|2|100-100
ISSN: 2072-4292
Source: Remote Sensing, Vol.8, Iss.2, 2016-01, pp. : 100-100
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
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.
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