Abstract
Wetland inventories especially on their spatial extent are a prerequisite for management and conservation of any wetland. The advancement in geospatial techniques has offered a wide range of methodological applications to prepare the inventories and to understand the dynamics of wetlands. The freely available Landsat imagery has been widely used in extracting spatial and temporal information about wetlands. The literature suggests that wetland has declined all over the globe over the past few decades. This study aims to prepare land use/land cover information of three wetlands of Punjab (Harike, Ropar, and Nangal) through direct on screen digitization and through digital processing using automatic digital indices as well. Evaluation of the performance of two band indices, normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) is also taken up in the present study. Landsat data of two periods-1990/91 and of 2018 are used for the study to perform two band indices. The result indicates that the NDWI and MNDWI are less time consuming and serve the purpose of mapping and monitoring wetlands with higher accuracy.
Similar content being viewed by others
References
Adam, E., Mutanga, O., & Rugege, D. (2010). Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: A review. Wetland Ecology and Management,18(3), 281–296.
Allen, Y. C., Couvillion, B. R., & Barras, J. A. (2012). Using multi-temporal remote sensing imagery and inundation measures to improve land change estimates in coastal wetlands. Estuaries and Coasts,35(1), 190–200.
Ashtekar, A. S., Mohammed-Aslam, M. A., & Moosvi, A. R. (2019). Utility of normalized difference water index and GIS for mapping surface water dynamics in sub-upper Krishna Basin. Journal of the Indian Society of Remote Sensing. https://doi.org/10.1007/s12524-019-01013-6.
Bassi, N., Kumar, M. D., Sharma, A., & Pardha-Saradhi, P. (2014). Status of wetlands in India: A review of extent, ecosystem benefits, threats and management strategies. Journal of Hydrology,2, 1–19.
Behera, M. D., Chitale, V. S., Shaw, A., Roy, P. S., & Murthy, M. S. R. (2012). Wetland monitoring, serving as an index of land use change—A study in Samaspur Wetlands, Uttar Pradesh, India. Journal of the Indian Society of Remote Sensing,40(2), 287–297. https://doi.org/10.1007/s12524-011-0139-6.
Brraich, O. S., & Jangu, S. (2016). Comparative account of accumulation of heavy metals and structural alterations in scales of five fish species from Harike Wetland, India. Iranian Journal of Ichthyology,3(4), 275–282.
Campbell, J. B. (2007). Introduction to remote sensing (4th ed.). New York: The Guilford Press.
Chen, L., Jin, Z., Michishita, R., Cai, J., Yue, T., Chen, B., et al. (2014). Dynamic monitoring of wetland cover changes using time-series remote sensing imagery. Ecological Information,24, 17–26.
Chen, X. L., Zhao, H. M., Li, P. X., & Yin, Z. Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment,104(2), 133–146.
Chitra, K. P. (2016). How Kerala is destroying its Wetlands, Amendment to Kerala Conservation of Paddy Land & Wetland Act 2008. Economic and Political Weekly. 51(22). https://www.epw.in/journal/2016/22/reports-states/how-kerala-destroying-its-wetlands.html
Choi, M., & Han, S. (2013). Remote sensing imageries for land cover and water quality dynamics on the west coast of Korea. Environment Monitoring and Assessment,185(11), 9111–9124.
Chopra, R., Verma, V. K., & Sharma, P. K. (2001). Mapping, monitoring and conservation of Harike Wetland ecosystem, Punjab, India, through remote sensing. International Journal of Remote Sensing,22(1), 89–98.
Dong, Z., Wang, Z., Liu, D., Song, K., Li, L., Jia, M., et al. (2014). Mapping wetland areas using Landsat-derived NDVI and LSWI: A case study of West Songnen Plain, Northeast China. Journal of the Indian Society of Remote Sensing,42(3), 1–8. https://doi.org/10.1007/s12524-013-0357-1.
Douglas, S. H., Bernier, J. C., & Smith, K. E. L. (2018). Analysis of multi-decadal wetland changes, and cumulative impact of multiple storms 1984 to 2017. Wetlands Ecology and Management,26(6), 1121–1142.
ENVIS. (2015). Wetland of Punjab, Punjab ENVIS Centre. http://www.indiaenvironmentportal.org.in/files/Wetlands%20of%20Punjab.pdf.
Gallant, A. L. (2015). The challenges of remote monitoring of wetlands. Remote Sensing,7(8), 10938–10950. https://doi.org/10.3390/rs70810938.
Gallant, A. L., Kaya, S. G., White, L., Brisco, B., Roth, M. F., Sadinski, W., et al. (2014). Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data. Water,6(3), 694–722.
Government of Punjab. (2009). Department of Forest and Wildlife Preservation (Forest Branch) Notification no: 34/2/2009-FT-5/7069. Dated 10.08.2009.
Guo, Q., Pu, R., Li, J., & Cheng, J. (2017). A weighted normalized difference water index for water extraction using Landsat imagery. International Journal of Remote Sensing,38(19), 5430–5445.
Jain, S. K., Sarkar, A., & Garg, V. (2008). Impact of declining trend of flow on Harike Wetland, India. Water Resource Management,22(4), 409–421.
Jia, M., Wang, Z., Li, L., Song, K., Ren, C., Liu, B., et al. (2014). Mapping China’s mangroves based on an object-oriented classification of Landsat imagery. Wetlands,34(2), 277–283.
Jia, J., Yang, N., Zhang, C., Yue, A., Yang, J., & Zhu, D. (2013). Object-oriented feature selection of high spatial resolution images using an improved relief algorithm. Mathematical and Computer Modelling,58(3–4), 619–626.
Johnston, R. M., & Barson, M. M. (1993). Remote sensing of Australian Wetlands: An evaluation of Landsat TM data for inventory and classification. Marine & Freshwater Research,44(2), 235–252.
Kumar, G. (2019). Wetlands in socio-economic and geographical contexts: A study of Harike, Ropar and Nangal Wetlands. Unpublished Ph.D. dissertation, Central University of Punjab.
Kumar, G., & Kaur, A. (2018). Status of wetlands in Punjab: A review on policy frameworks. Asian Journal of Multidimensional Research (AJMR),7(10), 169–177.
Kumar, V., Sharma, A., Chawla, A., Bhardwaj, R., & Thukral, A. K. (2016). Water quality assessment of river beas, India, using multivariate and remote sensing techniques. Environmental Monitoring and Assessment,188(3), 1–10.
Ladhar, S. S. (2002). Status of ecological health of wetlands in Punjab, India. Aquatic Ecosystem Health and Management,5(4), 457–465.
Li, W. B., Du, Z. Q., Ling, F., Zhou, D. B., Wang, H. L., Gui, Y. M., et al. (2013). A comparison of land surface water mapping using the normalized difference water index from TM, ETM plus and ALI. Remote Sensing,5, 5530–5549.
Mabwoga, S. O., Chawla, A., & Thukral, A. K. (2010). Assessment of water quality parameters of the Harike Wetland in India, a Ramsar Site, using IRS LISS IV satellite data. Environmental Monitoring Assessment,170(1–4), 117–128. https://doi.org/10.1007/s10661-009-1220-2.
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(7), 1425–1432.
Mertes, L. A. K., Smith, M. O., & Adams, J. B. (1993). Estimating suspended sediment concentrations in surface waters of the Amazon river wetlands from Landsat images. Remote Sensing of Environment,43(3), 281–301.
Millennium Ecosystem Assessment Report. (2005). Ecosystems and human well-being: Wetlands and water synthesis. World Resources Institute, Washington, DC. https://www.millenniumassessment.org/documents/document.358.aspx.pdf.
Mizuochi, H., Hiyama, T., Ohta, T., & Nasahara, K. (2014). Evaluation of the surface water distribution in north-central namibia based on MODIS and AMSR series. Remote Sensing,6(8), 7660–7682.
Ndayisaba, F., Nahayo, L., Guo, H., Bao, A., Kayiranga, A., Karamage, F., et al. (2017). Mapping and monitoring the Akagera wetland in Rwanda. Sustainability,9(2), 174.
O’Grady, D., Leblanc, M., & Bass, A. (2014). The use of radar satellite data from multiple incidence angles improves surface water mapping. Remote Sensing of Environment,140, 652–664.
Ozesmi, S. L., & Bauer, M. E. (2002). Satellite remote sensing of wetlands. Wetland Ecology and Management,10(5), 381–402.
Panigrahy, S., Murthy, T., Patel, J., & Singh, T. (2012). Wetlands of India: Inventory and assessment at 1: 50,000 scale using geospatial techniques. Current Science,102(6), 852–856.
Petus, C., Lewis, M., & White, D. (2013). Monitoring temporal dynamics of great artesian basin wetland vegetation, Australia, using MODIS NDVI. Ecological Indicators,34, 41–52.
Prigent, C., Matthews, E., Aires, F., & Rossow, W. B. (2001). Remote sensing of global wetland dynamics with multiple satellite data sets. Geophysical Research Letters,28(24), 4631–4634.
Ramsar Convention Secretariat. (2010). Wetland inventory: A Ramsar framework for wetland inventory and ecological character description. Gland: Ramsar Convention Secretariat.
Ramsar Convention Secretariat. (2016). The fourth Ramsar strategic plan 2016–2024. Ramsar handbook for the wise use of wetlands, 5th edn, Vol. 2. Ramsar Convention Secretariat, Gland, Switzerland. https://www.ramsar.org/sites/default/files/hb2_5ed_strategic_plan_2016_24_e.pdf.
Rokni, K., Ahmad, A., Selamat, A., & Hazini, S. (2014). Water feature extraction and change detection using multitemporal Landsat imagery. Remote Sensing,6(5), 4173–4189.
Rouse, J. W., Jr., Haas, R., Schell, J., & Deering, D. (1974). Monitoring vegetation systems in the great plains with ERTS. Washington, DC: NASA Special Publication.
Ryu, J. H., Won, J. S., & Min, K. D. (2002). Waterline extraction from Landsat TM data in a tidal flat—A case study in Gomso Bay, Korea. Remote Sensing of Environment,83(3), 442–456.
SAC. (2011). National wetland atlas. http://saconenvis.nic.in/publication%5CNWIA_National_atlas.pdf.
Seenivasa, R. (2013). National wetland atlas of India: A review and some inferences. Economic & Political Weekly,48(18), 120–124.
Singh, K. V., Setia, R., Sahoo, S., Prasad, A., & Pateriya, B. (2015). Evaluation of NDWI and MNDWI for assessment of waterlogging by integrating digital elevation model and groundwater level. Geocarto International,30, 650–661.
Son, N. T., Chen, C. F., Chang, N. B., & Chen, C. R. (2015). Mangrove mapping and change detection in Ca Mau Peninsula, Vietnam, using Landsat data and object-based image analysis. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,8(2), 503–510.
Tiwana, N. S., Jerath, N., Saxena, S. K., & Vivek, S. (2008). Conservation of Ramsar Sites in Punjab. In Proceedings of Taal: The 12th World Lake conference (pp. 1463–1469).
Verma, V. K., Chopra, R., Sharma, P. K., & Charanjit, S. (1998). Integrated resource study for conservation and management of Ropar wetland ecosystem, Punjab. Journal of the Indian Society of Remote Sensing,26(4), 185–195.
Widney, S., Klein, A. K., Hackney, C., & Craft, C. (2018). The value of wetlands for water quality improvement: An example from the St. Johns River Watershed, Florida. Wetlands Ecology and Management,26, 265–276.
Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing,27, 3025–3033.
Xue, Z., Lyu, X., Chen, Z., Zhang, Z., Jiang, M., Zhang, K., et al. (2018). Spatial and temporal changes of wetlands on the qinghai-tibetan plateau from the 1970s to 2010s. Chin. Geogr. Sci, 28, 935–945. https://doi.org/10.1007/s11769-018-1003-1.
Yan, D., Wang, X., Zhu, X., Huang, C., & Li, W. (2017). Analysis of the Use of NDWIgreen and NDWIred for Inland Water Mapping in the Yellow RiverBasin Using Landsat-8 OLI Imagery. Remote Sensing Letters, 8(10), 996–1005.
Zha, Y., Gao, J., & Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing,24(3), 583–594.
Zhang, Y., Lu, D., Yang, B., Sun, C. & Sun, M. (2011). Coastal wetland vegetation classification with a Landsat Thematic Mapper image. International Journal of Remote Sensing, 32, 545–561.
Acknowledgments
The United States Geological Survey (https://earthexplorer.usgs.gov/) is thankfully acknowledged for providing Landsat images free of cost. The National Remote Sensing Agency, Hyderabad, is acknowledged for providing satellite images. The first author is thankful to the UGC for granting research fellowship. The authors are grateful to the Central University of Punjab for providing necessary infrastructural facilities. The constructive comments of the anonymous reviewers are gratefully acknowledged.
Author information
Authors and Affiliations
Contributions
The First author mapped the land use classes of the wetlands and conducted the ground verification at various locations. The second author performed the digital classifications and wrote the manuscript. Both the authors equally participated in revision process.
Corresponding authors
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Kumar, G., Singh, K.K. Mapping and Monitoring the Selected Wetlands of Punjab, India, Using Geospatial Techniques. J Indian Soc Remote Sens 48, 615–625 (2020). https://doi.org/10.1007/s12524-020-01104-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12524-020-01104-9