A Comparison of Four Common Atmospheric Correction Methods
Mahiny, Abdolrassoul; Turner, B J
Description
Four atmospheric correction methods, two relative and two absolute, were compared in this study. Two of the methods (PIF and RCS) were relative approaches; COST is an absolute image-based method and 6S, an absolute modeling method. The methods were applied to the hazy bands 1 through 4 of a Landsat TM scene of the year 1997, which was being used in a change detection project. The effects of corrections were studied in woodland patches. Three criteria, namely (a) image attributes; (b) image...[Show more]
dc.contributor.author | Mahiny, Abdolrassoul | |
---|---|---|
dc.contributor.author | Turner, B J | |
dc.date.accessioned | 2015-12-07T22:52:40Z | |
dc.identifier.issn | 0099-1112 | |
dc.identifier.uri | http://hdl.handle.net/1885/27518 | |
dc.description.abstract | Four atmospheric correction methods, two relative and two absolute, were compared in this study. Two of the methods (PIF and RCS) were relative approaches; COST is an absolute image-based method and 6S, an absolute modeling method. The methods were applied to the hazy bands 1 through 4 of a Landsat TM scene of the year 1997, which was being used in a change detection project. The effects of corrections were studied in woodland patches. Three criteria, namely (a) image attributes; (b) image classification results, and (c) landscape metrics, were used for comparing the performance of the correction methods. Average pixel values, dynamic range, and coefficient of variation of bands constituted the first criterion, the area of detected vegetation through image classification was the second criterion, and patch and landscape measures of vegetation the third criterion. Overall, the COST, RCS, and 6S methods performed better than PIF and showed more stable results. The 6S method produced some negative values in bands 2 through 4 due to the unavailability of some data needed in the model. Having to use only a single set of image pixels for normalization in the PIF method and the difficulty of selecting such samples in the study area may be the reasons for its poor performance. | |
dc.publisher | American Society for Photogrammetry and Remote Sensing | |
dc.source | Photogrammetric Engineering and Remote Sensing | |
dc.subject | Keywords: Atmospheric movements; Data acquisition; Image classification; Normal distribution; Pixels; Atmospheric correction methods; Change detection project; Image attributes; Landscape measures; Remote sensing; atmospheric correction; comparative study; detectio | |
dc.title | A Comparison of Four Common Atmospheric Correction Methods | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.identifier.citationvolume | 73 | |
dc.date.issued | 2007 | |
local.identifier.absfor | 080106 - Image Processing | |
local.identifier.ariespublication | u9205081xPUB51 | |
local.type.status | Published Version | |
local.contributor.affiliation | Mahiny, Abdolrassoul, Gorgan University of Agriculture and Natural Resources | |
local.contributor.affiliation | Turner, B J, College of Medicine, Biology and Environment, ANU | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.issue | 4 | |
local.bibliographicCitation.startpage | 361 | |
local.bibliographicCitation.lastpage | 368 | |
dc.date.updated | 2015-12-07T12:31:56Z | |
local.identifier.scopusID | 2-s2.0-33947707210 | |
Collections | ANU Research Publications |
Download
File | Description | Size | Format | Image |
---|---|---|---|---|
01_Mahiny_A_Comparison_of_Four_Common_2007.pdf | 788.66 kB | Adobe PDF |
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.
Updated: 17 November 2022/ Responsible Officer: University Librarian/ Page Contact: Library Systems & Web Coordinator