Promising selection using factor approximate method in the remote sensing interpretation
The information contained in remote sensing images is represented by various image signatures. How to analyse, extract and utilize these features to select a promising area is an important research subject in remote sensing geological interpretation. The paper discusses how to determine remote sensi...
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Published in | IGARSS '93 : 1993 International Geoscience and Remote Sensing Symposium (IGARSS '93) : better understanding of earth environment Vol. ol. 4; pp. 2096 - 2098 vol.4 |
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Main Authors | , |
Format | Conference Proceeding Journal Article |
Language | English |
Published |
IEEE
1993
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Subjects | |
Online Access | Get full text |
ISBN | 0780312406 9780780312401 |
DOI | 10.1109/IGARSS.1993.322041 |
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Summary: | The information contained in remote sensing images is represented by various image signatures. How to analyse, extract and utilize these features to select a promising area is an important research subject in remote sensing geological interpretation. The paper discusses how to determine remote sensing interpretation factors based on the analysis of the metallogenetic mechanism and how to establish the principle and method of favourable area selection using the factor approximate method. The restricted remote sensing factors can be defined as those image features (color, tone, size, shape, pattern and lamination) which are related with ore-controlling factors (such as lithology, stratigraphy, massif, fault, alteration and vein). The paper also focuses on the extraction, classification priority and order of remote sensing interpretation factors and geological genesis explanation. Finally, taking the Qixia area as an example the realization and procedures of the factor approximate method are explained in detail. The method has proven to be quick and efficient in gold promising districts selection.< > |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISBN: | 0780312406 9780780312401 |
DOI: | 10.1109/IGARSS.1993.322041 |