Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping
Hyperspectral images have wide applications in the fields of geology, mineral exploration, agriculture, forestry and environmental studies etc. due to their narrow band width with numerous channels. However, these images commonly suffer from atmospheric effects, thereby limiting their use. In such a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2017-07-01
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| Series: | Geoscience Frontiers |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674987116300603 |
| _version_ | 1797726436547624960 |
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| author | Nisha Rani Venkata Ravibabu Mandla Tejpal Singh |
| author_facet | Nisha Rani Venkata Ravibabu Mandla Tejpal Singh |
| author_sort | Nisha Rani |
| collection | DOAJ |
| description | Hyperspectral images have wide applications in the fields of geology, mineral exploration, agriculture, forestry and environmental studies etc. due to their narrow band width with numerous channels. However, these images commonly suffer from atmospheric effects, thereby limiting their use. In such a situation, atmospheric correction becomes a necessary pre-requisite for any further processing and accurate interpretation of spectra of different surface materials/objects. In the present study, two very advance atmospheric approaches i.e. QUAC and FLAASH have been applied on the hyperspectral remote sensing imagery. The spectra of vegetation, man-made structure and different minerals from the Gadag area of Karnataka, were extracted from the raw image and also from the QUAC and FLAASH corrected images. These spectra were compared among themselves and also with the existing USGS and JHU spectral library. FLAASH is rigorous atmospheric algorithm and requires various parameters to perform but it has capability to compensate the effects of atmospheric absorption. These absorption curves in any spectra play an important role in identification of the compositions. Therefore, the presence of unwanted absorption features can lead to wrong interpretation and identification of mineral composition. FLAASH also has an advantage of spectral polishing which provides smooth spectral curves which helps in accurate identification of composition of minerals. Therefore, this study recommends that FLAASH is better than QUAC for atmospheric correction and correct interpretation and identification of composition of any object or minerals. |
| first_indexed | 2024-03-12T10:45:29Z |
| format | Article |
| id | doaj.art-4bb6f73d744e4415b5fc2e8cf146dbaf |
| institution | Directory Open Access Journal |
| issn | 1674-9871 |
| language | English |
| last_indexed | 2024-03-12T10:45:29Z |
| publishDate | 2017-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Geoscience Frontiers |
| spelling | doaj.art-4bb6f73d744e4415b5fc2e8cf146dbaf2023-09-02T07:34:12ZengElsevierGeoscience Frontiers1674-98712017-07-018479780810.1016/j.gsf.2016.06.004Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mappingNisha Rani0Venkata Ravibabu Mandla1Tejpal Singh2Centre for Disaster Mitigation and Management (CDMM), VIT University, Vellore, IndiaOSGST-Lab, Department of Environmental, Water Resources Engineering, School of Civil and Chemical Engineering, VIT University, Vellore, IndiaCSIR-Central Scientific Instruments Organisation, Chandigarh, IndiaHyperspectral images have wide applications in the fields of geology, mineral exploration, agriculture, forestry and environmental studies etc. due to their narrow band width with numerous channels. However, these images commonly suffer from atmospheric effects, thereby limiting their use. In such a situation, atmospheric correction becomes a necessary pre-requisite for any further processing and accurate interpretation of spectra of different surface materials/objects. In the present study, two very advance atmospheric approaches i.e. QUAC and FLAASH have been applied on the hyperspectral remote sensing imagery. The spectra of vegetation, man-made structure and different minerals from the Gadag area of Karnataka, were extracted from the raw image and also from the QUAC and FLAASH corrected images. These spectra were compared among themselves and also with the existing USGS and JHU spectral library. FLAASH is rigorous atmospheric algorithm and requires various parameters to perform but it has capability to compensate the effects of atmospheric absorption. These absorption curves in any spectra play an important role in identification of the compositions. Therefore, the presence of unwanted absorption features can lead to wrong interpretation and identification of mineral composition. FLAASH also has an advantage of spectral polishing which provides smooth spectral curves which helps in accurate identification of composition of minerals. Therefore, this study recommends that FLAASH is better than QUAC for atmospheric correction and correct interpretation and identification of composition of any object or minerals.http://www.sciencedirect.com/science/article/pii/S1674987116300603Atmospheric correctionHyperspectral dataRadianceReflectanceFLAASHQUAC |
| spellingShingle | Nisha Rani Venkata Ravibabu Mandla Tejpal Singh Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping Geoscience Frontiers Atmospheric correction Hyperspectral data Radiance Reflectance FLAASH QUAC |
| title | Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping |
| title_full | Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping |
| title_fullStr | Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping |
| title_full_unstemmed | Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping |
| title_short | Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping |
| title_sort | evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping |
| topic | Atmospheric correction Hyperspectral data Radiance Reflectance FLAASH QUAC |
| url | http://www.sciencedirect.com/science/article/pii/S1674987116300603 |
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