122
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

Change analysis of water area and flood mapping using a novel water index 2020 (WI2020) for Landsat imagery

& ORCID Icon
Pages 6391-6408 | Received 03 Jan 2021, Accepted 25 May 2021, Published online: 21 Jun 2021
 

Abstract

The present study deals with Landsat data for the change analysis and flood mapping using water class extraction. Among the various available bands, the most suitable band combination is identified using class separability analysis and a novel water index (WI2020) is proposed for the extraction of water. The proposed index is able to separate the water class from other land features and performs better than NDWI. The index-based results are also validated through supervised classification and used for change analysis and flood mapping. The change analysis is done in two ways, viz., from the year 2000 to 2020 in a span of 5 years in a periodic manner and from the year 2014 to 2020 in a continuous manner. The flood mapping is done on the images of 2014 and 2016 along with the pre-flood and post-flood situations with the help of WI2020 which gives quantitatively satisfactory results.

Acknowledgement

The first author is thankful to Ministry of Education, Government of India for providing the financial assistance.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability

The data that support the findings of this study are openly available at https://earthexplorer.usgs.gov/.

Additional information

Funding

This work was supported by the Ministry of Human Resource Development.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access
  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart
* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.