Abstract
India harbors diverse types of wetlands spread over inland, coastal, marine, and high mountains. The diversity and distribution pattern over the large geographic region of India makes wetlands inventory a challenging and time-consuming activity. Satellite remote sensing, particularly the multispectral optical sensors, has been found useful for this purpose. IRS LISS III sensors with 23.5 m spatial resolution that provide multispectral images in green, red, NIR, and SWIR region were used to develop a methodology for wetland mapping. Various combinations of spectral indices, viz., NDWI, MNDWI, NDVI, and NDPI, were found suitable for wetland mapping. Besides wetland boundary, it was feasible to map three wetland structural components, viz., extent of water, aquatic vegetation, and water turbidity. Among the aquatic vegetation types, emergent and to some extent floating types could be mapped. Water quality was expressed in terms of three qualitative ratings. It was found essential to use two date data pertaining to wet and dry seasons to improve accuracy of classification and derive hydrological behavior of wetlands. The procedure was used to map wetlands of entire India at 1:50,000 scale using LISS III images of 2006–2007. LISS III image enabled mapping of wetlands of >2.25 ha. Smaller than this size were mapped as points. This chapter highlights the procedure used and the advantages and limitations of remote sensing technology for wetland mapping.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anon (1993) Directory of Indian wetlands, WWF India, New Delhi and AWB Kuala Limpur, xvi, p 264
Cowardin LM, Carter V, Golet FC, LaRoe ET (1979) Classification of wetlands and deepwater habitats of the United States. U S Department of Fish and Wildlife Service, Washington, DC
Elhadi A, Onisimo M, Denis R (2010) Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review. Wetl Ecol Manag 18:281–296
Finlayson CM, Davidson NC, Spiers AG, Stevenson NJ (1999) Global wetland inventory status and priorities. Mar Freshw Res 50:717–727
Finlayson CM, Davidson NC and Stevenson NJ (eds) (2001) Wetland inventory, assessment and monitoring: practical techniques and identification of major issues. In: Proceedings of Workshop 4, 2nd International Conference on Wetlands and Development, Dakar, Senegal, 8.14 1998, Supervising Scientist Report 161, Supervising Scientist, Darwin
Garg JK, Singh TS and Murthy TVR (1998) Wetlands of India, Project Report, RSAM/SAC/RESA/PR/01/98, p 240, Space Applications Centre, Ahmedabad
Ghermandi A, van den Bergh JCJM, Brander LM, de Groo HLF, Nunes P (2010) Values of natural and human-made wetlands: a meta-analysis. Water Resour Res 46:1–12
Gopal B, Sah M (1995) Inventory and classification of wetlands in India. Vegetatio 118:39–48
Griffith JA (2002) Geographic techniques and recent applications of remote sensing to landscape-water quality studies. Water Air Soil Pollut 138:181–197
Hardisky MA, Gross MF, Klemas V (1986) Remote sensing of coastal wetlands. Bioscience 36:453–460
Jensen JR, Hodgson ME, Christensen E, Halkard E, Mackey J, Tinney LR, Shartiz R (1986) Remote sensing inland wetlands: a multispectral approach. Photogramm Eng Remote Sens 52:87–100
Ji L, Geng X, Sun K, Zhao Y, Gong P (2015) Target detection method for water mapping using landsat 8 OLI/TIRS imagery. Water 7:794–817
Lacaux JP, Tourre YM, Vignolles C, Ndione JA, Lafaye M (2007) Classification of ponds from high-spatial resolution remote sensing: application to Rift valley fever epidemics in Senegal. Remote Sens Environ 106:66–74
Lee KH, Lunetta RS (1996) Wetland detection methods. In: Lyon JG, McCarthy J (eds) Wetland and environmental applications of GIS. Lewis Publishers, New York, pp 249–284
Lei J, Zhang L, Wylie B (2009) Analysis of dynamic thresholds for the normalised difference water index. Photogramm Eng Remote Sens 75:1307–1317
Lillesand TM, Keifer RW (1987) Remote sensing and image interpretation. Wiley, New York
Lulla K (1983) The Landsat satellites and selected aspects of physical geography. Prog Phys Geogr 7:1–45
McFeeters SK (1996) The use of Normalised Difference Water Index (NDWI) in the delineation of open water features. Int J Remote Sens 17:1425–1432
MoEF (1995) Wetlands of India: a directory. ministry of environment and forests. Government of India, New Delhi
MoEF (2012) Wetlands of India: a directory. Ministry of environment and forests. Government of India, New Delhi
Murthy TVR, Patel JG, Panigrahy S and Parihar JS (eds) ( 2013) National Wetland Atlas: wetlands of International Importance under Ramsar Convention, Space Applications Centre (ISRO), Ahmedabad, p 230, ISBN:978-93-82760-00-9.
NNRMS (2005) NNRMS Standards: a national standard for EO images, Thematic and Cartographic Maps, GIS Databases and Spatial Outputs, ISRO Bangalore publication, p 201
Panigrahy S, Murthy TVR, Patel JG, Singh TS (2012) Wetlands of India: inventory and assessment at 1: 50,000 scale using geospatial techniques. Curr Sci 102:852–856
Panigrahy S, Patel JG, Parihar JS (eds) (2013) National Wetland Atlas: high altitude lakes of India. Space Applications Centre, ISRO, Ahmedabad, p 108 ISBN:978-93-82760-00-9
Patel JG, Murthy TVR, Singh TS, Panigrahy S (2009) Analysis of the distribution pattern of wetlands in India in relation to climate change. ISPRS Archives XXXVIII-8/W3 Workshop Proceedings: Impact of Climate Change on Agriculture, pp 282–287
Patel JG, Panigrahy S, Parihar JS (2015) National wetland database and information system: a step towards integrated planning for conservation of wetlands in India. J Geomatics 9:184–192
Prasad SN, Ramachandra TV, Ahalya N, Sengupta T, Kumar A, Tiwari AK, Vijayan VS, Vijayan L (2002) Conservation of wetlands of India – a review. Trop Ecol 43:173–186
Prigent C, Matthews E, Aires F, Rossow WB (2001) Remote sensing of global wetland dynamics with multiple satellite datasets. Geophys Res Lett 28:4631–4634
SAC (2011) National Wetland Atlas, India, SAC/EPSA/ABHG/NWIA/ATLAS/34/2011, Space Applications Centre (ISRO), Ahmedabad, p 306
Scott DA, Jones TA (1995) Classification and inventory of wetlands: a global overview. Vegetatio 118:3–16
Sohn Y, Rebello NS (2002) Supervised and unsupervised spectral angle classifiers. Photogramm Eng Remote Sens 68:127–128
Stacy LO, Marvin EB (2002) Satellite remote sensing of wetlands. Wetl Ecol Manag 10:381–402
Townshend JR, Justice CO (1986) Analysis of dynamics of African vegetation using the normalised difference vegetation index. Int J Remote Sens 7:1435–1445
Wilen BO, Bates MK (1995) The US fish and wildlife service’s wetland inventory project. Vegetatio 118:153–169
Woistencroft JA, Hussain SA, Varshney CK (1989) India: introduction. In: Scott DA (ed) A directory of Asian Wetlands. IUCN, World Conservation Union, Switzerland, pp 367–505
Xu H (2006) Modification of Normalised Difference Water Index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27:3025–3033
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer (India) Pvt. Ltd.
About this chapter
Cite this chapter
Panigrahy, S. (2017). Mapping of Wetlands using Satellite Remote Sensing Data: Indian Experience. In: Prusty, B., Chandra, R., Azeez, P. (eds) Wetland Science . Springer, New Delhi. https://doi.org/10.1007/978-81-322-3715-0_22
Download citation
DOI: https://doi.org/10.1007/978-81-322-3715-0_22
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-3713-6
Online ISBN: 978-81-322-3715-0
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)