A Comparison of Change Detection Analyses Using Different Band Algebras for Baraila Wetland with Nasa’s Multi-Temporal Landsat Dataset


Wetlands are those landscapes which are saturated with water or covered by water either perennially or for a major part of the year. Due to transforming nature of the wetlands from aquatic to terrestrial, the related physical features are not easy to be monitored. With the recent advancement in Remote sensing technique, the feature extraction of wetland with the help of different satellite derived band algebras including Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Normalized Difference Moisture Index (NDMI) is being used by experts. The common diagnostic features of wetlands are surface water, swamps and aquatic vegetation. The present study is based on a comparison between these four indices. Baraila wetland of Vaishali district Bihar is selected as a site for the study because the surface water of this “BAT” shaped wetland has decreased rapidly in last half decade which is alarming for the related ecology and biodiversity.

Share and Cite:

Ashraf, M. and Nawaz, R. (2015) A Comparison of Change Detection Analyses Using Different Band Algebras for Baraila Wetland with Nasa’s Multi-Temporal Landsat Dataset. Journal of Geographic Information System, 7, 1-19. doi: 10.4236/jgis.2015.71001.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Xu, H. (2006) Modification of Normalized Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery. International Journal of Remote Sensing, 27, 3025-3033.
[2] Rundquist, D., Lawson, M., Queen, L. and Cerveny, R. (1987) The Relationship between the Timing of Summer-Season Rainfall Events and Lake-Surface Area. Water Resources Bulletin, 23, 493-508.
[3] Yu, J., Huang, Y. and Feng, X. (2001) Study on Water Bodies Extraction and Classification from SPOT Image. Journal of Remote Sensing, 5, 214-219.
[4] Du, Z., Linghu, B., Ling, F., Li, W., Tian, W., Wang, H., Gui, Y., Sun, B. and Zhang, X. (2012) Estimating Surface Water Area Changes Using Time-Series Landsat Data in the Qingjiang River Basin, China. Journal of Applied Remote Sensing, 6, Article ID: 063609. http://dx.doi.org/10.1117/1.JRS.6.063609
[5] McFeeters, S.K. (1996) The Use of the Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features. International Journal of Remote Sensing, 17, 1425-1432.
[6] Gao, B.C. (1996) NDWI—Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space. Remote Sensing of Environment, 58, 257-266.
[7] Wilson, E.H. and Sader, S.A. (2002) Detection of Forest Harvest Type Using Multiple Dates of Landsat TM Imagery. Remote Sensing of Environment, 80, 385-396.
[8] Rouse, J.W., Haas, R.H., Schell, J.A. and Deering, D.W. (1973) Monitoring Vegetation Systems in the Great Plains with ERTS (Earth Resources Technology Satellite). Proceedings of 3rd Earth Resources Technology Satellite Symposium, Greenbelt, 10-14 December, SP-351, 309-317.

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.