Cloud and cloud shadow masking using multi-temporal cloud masking algorithm in tropical environmental

Candra, D. S., Phinn, S. and Scarth, P. (2016). Cloud and cloud shadow masking using multi-temporal cloud masking algorithm in tropical environmental. In: XXIII ISPRS Congress, Commission II. 23rd International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Congress, ISPRS 2016, Prague, Czech Republic, (95-100). 12 - 19 July 2016. doi:10.5194/isprsarchives-XLI-B2-95-2016


Author Candra, D. S.
Phinn, S.
Scarth, P.
Title of paper Cloud and cloud shadow masking using multi-temporal cloud masking algorithm in tropical environmental
Conference name 23rd International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Congress, ISPRS 2016
Conference location Prague, Czech Republic
Conference dates 12 - 19 July 2016
Convener ISPRS
Proceedings title XXIII ISPRS Congress, Commission II   Check publisher's open access policy
Journal name The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences   Check publisher's open access policy
Place of Publication London, United Kingdom
Publisher International Society for Photogrammetry and Remote Sensing
Publication Year 2016
Sub-type Fully published paper
DOI 10.5194/isprsarchives-XLI-B2-95-2016
Open Access Status DOI
ISSN 1682-1750
2194-9034
Volume 41
Issue B2
Start page 95
End page 100
Total pages 6
Collection year 2017
Language eng
Abstract/Summary A cloud masking approach based on multi-temporal satellite images is proposed. The basic idea of this approach is to detect cloud and cloud shadow by using the difference reflectance values between clear pixels and cloud and cloud shadow contaminated pixels. Several bands of satellite image which have big difference values are selected for developing Multi-temporal Cloud Masking (MCM) algorithm. Some experimental analyses are conducted by using Landsat-8 images. Band 3 and band 4 are selected because they can distinguish between cloud and non cloud. Afterwards, band 5 and band 6 are used to distinguish between cloud shadow and clear. The results show that the MCM algorithm can detect cloud and cloud shadow appropriately. Moreover, qualitative and quantitative assessments are conducted using visual inspections and confusion matrix, respectively, to evaluate the reliability of this algorithm. Comparison between this algorithm and QA band are conducted to prove the reliability of the approach. The results show that MCM better than QA band and the accuracy of the results are very high.
Keyword Cloud
Cloud shadow
Landsat-8
Multitemporal cloud masking algrithm
Multitemporal images
Tropical environmental
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Created: Sun, 05 Mar 2017, 01:00:36 EST by Web Cron on behalf of Learning and Research Services (UQ Library)