Remote Predictive Mapping 3. Optical Remote Sensing - A Review for Remote Predictive Geological Mapping in Northern Canada

被引:0
作者
Harris, J. R. [1 ]
Wickert, L. [2 ]
Lynds, T. [1 ]
Behnia, P. [1 ]
Rainbird, R. [1 ]
Grunsky, E. [1 ]
McGregor, R.
Schetselaar, E. [1 ]
机构
[1] Geol Survey Canada, Ottawa, ON K1A 0EP, Canada
[2] McMaster Univ, Sch Geog & Earth Sci, Hamilton, ON L8S 4K1, Canada
关键词
HYPERSPECTRAL DATA; BAFFIN-ISLAND; TRANSFORMATION; INTEGRATION; EXTRACTION;
D O I
暂无
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Optical remotely sensed data have broad application for geological mapping in Canada's North. Diverse remote sensors and digital image processing techniques have specific map-ping functions, as demonstrated by numerous examples and associated interpretations. Moderate resolution optical sensors are useful for discriminating rock types, whereas sensors that offer increased spectral resolution (i.e. hyperspectral sensors) allow the geologist to identify certain rock types (mainly different types of carbonates, Fe-bearing rocks, sulphates and hydroxyl(clay-) bearing rocks) as opposed to merely discriminating between them. Increased spatial resolution and the ability to visualize the earth's surface in stereo are now offered by a host of optical sensors. However, the usefulness of optical remote sensing for geological mapping is highly dependent on the geologic, surficial and biophysical environment, and bedrock predictive mapping is most successful in areas not obscured by thick drift and vegetation/lichen cover, which is typical of environments proximal to coasts. In general, predictive mapping of surficial materials has fewer restrictions. Optical imagery can be enhanced in a variety of ways and fused with other geoscience datasets to produce imagery that can be visually interpreted in a GIS environment. Computer processing techniques are useful for undertaking more quantitative analyses of imagery for mapping bedrock, surficial materials and geomorphic or glacial features.
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页码:49 / 83
页数:35
相关论文
共 42 条
[1]  
[Anonymous], 5433 GEOL SURV CAN
[2]   Spectral properties of foliose and crustose lichens based on laboratory experiments [J].
Bechtel, R ;
Rivard, B ;
Sánchez-Azofeifa, A .
REMOTE SENSING OF ENVIRONMENT, 2002, 82 (2-3) :389-396
[3]  
Bowers TL, 1996, PHOTOGRAMM ENG REM S, V62, P1379
[4]  
BUDKEWITSCH P, 2000, OR DEP WORKSH NEW ID, P1
[5]  
Clark RN, 1999, Remote sensing for the earth science. Manual of remote sensing, V3, P3, DOI DOI 10.1111/J.1945-5100.2004.TB00079.X
[6]  
Crosta A.P., 1989, P 7 THEM C REM SENS, P1173
[7]  
CUDAHY T, 2002, ASTER WORKSH ANN M G
[8]  
Fulton R.J., 1995, SURFICIAL MAT CANADA
[9]   A TRANSFORMATION FOR ORDERING MULTISPECTRAL DATA IN TERMS OF IMAGE QUALITY WITH IMPLICATIONS FOR NOISE REMOVAL [J].
GREEN, AA ;
BERMAN, M ;
SWITZER, P ;
CRAIG, MD .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1988, 26 (01) :65-74
[10]  
Grunsky E. E., 2006, 5153 GEOL SURV CAN