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Quantitative evaluation of lineament extraction potential using TM data.

TMデータによるリニアメント抽出能力の定量的評価
Authors: IWASHITA, Atsushi; SHIMODA, Haruhisa; SAKATA, Toshibumi;

Quantitative evaluation of lineament extraction potential using TM data.

Abstract

Lineament and geological information extraction from Remote Sensing data is important for the analysis of natural resources exploration. It is understand that lineaments are mostly reflecting the fractures of subsurface. These fractures sometimes work for the migration and stratigraphic trap of petroleum from deeper portion of source rocks.From this point of view, In this paper, the quantitative evaluation using extracted lineaments pattern from Landsat TM has been studied. Two Laplacian types of edge enhancement processing were applied to compare the effect of enhancement. Lineaments were extracted by two interpretors from 9 processed images, and those extracted lineaments were analyzed statistically.As the results, those lineamets were remarkably appeared defferently depending upon the features of each studied areas and edge enhancement parameters. Maximum cumlative length of extracted lineaments were nominaly appeared from simply enhanced images. Medium length of lineaments were also appeared from enhanced images.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold