• Corpus ID: 163158286

Remote Sensing for Mineral Exploration – A Decade Perspective 1997-2007

@inproceedings{2007RemoteSF,
  title={Remote Sensing for Mineral Exploration – A Decade Perspective 1997-2007},
  author={},
  year={2007},
  url={https://api.semanticscholar.org/CorpusID:163158286}
}

• Published 2007
• Geology, Environmental Science

The years between 1997 and 2007 saw significant advances in remote sensing technology for mineral exploration. The successful launch of the ASTER instrument in 1999 brought with it the ability to map mineral zoning and quartz occurrences within alteration systems. This took remote sensing from the age of the ambiguous “TM anomaly” into the age of mineral mapping from space. While ASTER has rapidly become the workhorse of geologic remote sensing, high spatial resolution satellite image and high… 

The years between 1997 and 2007 saw significant advances in remote sensing technology for mineral exploration. The successful launch of the ASTER instrument in 1999 brought with it the ability to map mineral zoning and quartz occurrences within alteration systems. This took remote sensing from the age of the ambiguous “TM anomaly” into the age of mineral mapping from space. While ASTER has rapidly become the workhorse of geologic remote sensing, high spatial resolution satellite image and high spectral resolution airborne imaging have also advanced. Sub-meter multispectral satellite systems allow near airphoto quality imagery to be acquired anywhere in the world. The “open skies” policy of the satellite operators permits high resolution image acquisitions to be undertaken in locations where it was not possible before. Although slower to be embraced by the exploration community, airborne hyperspectral data that is capable of mapping individual mineral species and chemical substitutions within individual minerals has progressed to the point of being an operational commercial technology. With the improvements in spectral resolution have come advances in the processing of the remote sensing data. The results of remote sensing data analysis have progressed from highly qualitative anomaly identification to quantitative mineral species mapping.