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بناء قاعدة بيانات لاستكشاف المعادن بالاعتماد على التحسس النائي فائق الدقة الطيفية == Building Geodatabase for Mineral Investigation Based on Hyperspectral Remote Sensing
Author name:
سامر محمد جواد سيفي
Supervisor name:
محمد مجبل صالح | خالد ابراهيم حسون
General topic:
Civil Engineering
Specific topic:
Geomatics Engineering
Degree:
Master
University:
University of Technology - Department Of Civil Engineering - Geomatics Engineering Branch
Language:
English
University location:
Baghdad
Key words:
- remote sensing
- Erdas software
- SAM values
- ASD
- GIS
Abstract:
Soil minerals are essential substances in many industries that meet the needs of the community, so it is necessary to investigate these minerals and know where they are. The method of mineral investigation requires great field work for the great human effort, a long period of time and the seriousness of the work and its problems. The aim of this research is to build geodatabase for mineral based on hyperspectral remot sensing, the advantages of this aim are to reduce the cost , time , and human effort in mineral investigation , also use this database by researcher , investmenter and the some orgnazations. In this research, the hyperspectral image produced by the Hyperion sensor on EO-1 satellite was used, where the EO-1 was launched in 2000 by NASA agency. This image has covered the area in dimensions(7.7km*100km) and was selected to locate an area to the west of holy Karbala province – Iraq, which is considered a strategic area because of its content at initial materials are used in many types of important industrial, and it is located on the road linking three provinces with neighbor countries. The remote investigation of this region was done using the Erdas imagine software for processing and analysis the hyperspectral image, where this processing have including:- bad band removal, georefrecing image, and atmospheric correction, while the analysis including the mineral detection and distribution in twelve sites in the study area that showed the nine types of mineral according to the spectrum curve of the image. After that identifying the minerals by using the SAM technique, this technique is the match between spectral curve of the point in the image with spectrum curve of minerals in spectrum library . To check the mineral types in an image , the ground truth must be done by using ASD test, then x-ray test was used for more check the results. The results of SAM technique by ASD test appeare there are eight minerals are matching with spectral curve of ASD test as well as the SAM values in software of eight minerals will depended because the ASD test was prove the existing minerals in the field . According to these result the researcher create a spatial geodatabase for spatial distribution SAM minerals and prove that the (Microcline (Feldspar) (K,Na)AlSi_3O_8) mineral has highest value of SAM site two with coordinate (396633.94E , 3611113.91N), appendix(E) show the figures of spatial distribution SAM of mineral map , these maps was producd by Arcmap depending on a geodatabase of them represented by attribute table including the location of points and minerals content.
Full text:
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Summary:
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