Advertisement

Journal of the Indian Society of Remote Sensing

, Volume 47, Issue 12, pp 2027–2045 | Cite as

A WebGIS-Based Study for Managing Mangroves of Godavari Wetland, Andhra Pradesh, India

  • K. JayakumarEmail author
  • V. Selvam
  • V. R. Prabavathy
Research Article
  • 40 Downloads

Abstract

The mangroves of the Godavari are well known as the first largest mangrove wetland in the state of Andhra Pradesh and the second largest in the Eastern Coast of India. Mangroves of Godavari provide multiple benefits to local communities, but they were threatening this wetland since 1980. The objective of this work is to map and monitor the mangroves and analyze the changes over the period of 74 years and incorporate geospatial data of the study area into a WebGIS platform. This WebGIS is an exceptional and cost-effective solution that would lead a valuable decision-making process for the public, significant versatile asset which would bring the mangroves to improve operations, increase collaboration and promote tourism, research and development through the internet. Topographic maps and satellite images have been used to map mangroves wetland and developed WebGIS by using open source and incorporated geospatial information of mangroves into it. As it acts as a standards-based platform for digital analysis, data management and mapping and monitoring mangroves, resulting stakeholders to access everywhere via web browser at any time. This is an innovative technique and is attempted here for the first time to manage mangroves; it can store a massive volume of geospatial data on the server, which reduces time, manpower and expense and control duplication of data. Apart from this, it has also allowed users for visualizing, editing, manipulating, interacting and disseminating geospatial data. The result revealed that 12 geospatial data from 1938 to 2012 were made available that showed changes in mangroves extent and distribution, and also a gradual increase in mangrove covers has been noticed from 2004 onwards. It may be concluded that a WebGIS-based study on mangrove wetland is useful to manage mangroves by mangrove management authorities and to regulate the mangrove development activities and formulating new policies for the better planning and management in order to guide for the sustainable mangrove of forests.

Keywords

Mangroves WebGIS Spatial datasets Anthropogenic Open source 

Notes

References

  1. Coastal Zones of India. (2012). Space applications centre—ISRO, Ahmedabad.Google Scholar
  2. Dahdouh-Guebas, F. (2002). The use of Remote Sensing and GIS in the sustainable management of Tropical Coastal Ecosystems. Environment, Development and Sustainability,4, 93–112.CrossRefGoogle Scholar
  3. Dahdouh-Guebas, F., Verheyden, A., De Genst, W., Hettiarachchi, S., & Koedam, N. (2000). Four decade vegetation dynamics in Sri Lankan mangroves as detected from sequential aerial photography: A case study in Galle. Bulletin of Marine Science,67(2), 741–759.Google Scholar
  4. Forest Survey of India. (2011). India state of forest report. Dehradun: Ministry of Environment and Forests, Government of India.Google Scholar
  5. Fromard, F., Vega, C., & Proisy, C. (2004). Half a century of dynamic coastal change affecting mangrove shorelines of French Guiana. A case study based on remote sensing data analyses and field surveys. Marine Geology,208, 265–280.CrossRefGoogle Scholar
  6. Giri, C., Ochieng, E., Tieszen, L. L., Zhu, Z., Singh, A., Loveland, T., et al. (2011). Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography,20(1), 154–159.CrossRefGoogle Scholar
  7. Gnanappahzam, L. (2007). A remote sensing and GIS based decision support system for effective management of Pichavaram mangrove wetland, South India. Ph.D. thesis, University of Madras, Chennai, Tamil Nadu, India.Google Scholar
  8. Ishtiaque, A., Myint, S. W., & Wang, C. (2016). Examining the ecosystem health and sustainability of the world’s largest mangrove forest using multi-temporal MODIS products. Science of the Total Environment,569–570, 1241–1254.CrossRefGoogle Scholar
  9. Jayakumar, K. (2014). Remote sensing and GIS application in the management of Godavari mangrove wetland, Andhra Pradesh, South India. Ph.D. thesis, University of Madras, Chennai, Tamil Nadu, India.Google Scholar
  10. Jayakumar, K. (2019). Managing mangrove forests using open source-based WebGIS. In R. R. Krishnamurthy, et al. (Eds.), Coastal management: Global challenges and innovations (pp. 301–321). Candic Janco: Academic Press.CrossRefGoogle Scholar
  11. Jayakumar, K., & Malarvannan, S. (2015). A WebGIS based decision support system for land use and land cover changes: A case study of Tiruvallur block, Tamil Nadu. International Journal of Earth Science and Engineering,8(4), 1892–1898.Google Scholar
  12. Jayakumar, K., & Malarvannan, S. (2016). An assessment of shoreline changes over the Northern Tamil Nadu Coast using open source based WebGIS techniques. The Journal of Coastal Conservation,20(5), 477–487.CrossRefGoogle Scholar
  13. Jayakumar, K., Malarvannan, S., Suresh, V. M., Balasooriya, & N. W. B. (2016). A WebGIS based study for managing of Mangroves of Krishna Delta, Andhra Pradesh, India. In Final proceedings of 6th international symposium, South Eastern University of Srilanka, Sirlanka.Google Scholar
  14. Jayanthi, M., Ravichandran, P., & Ponniah, A. G. (2010). Status of mangroves in relation to Brackishwater aquaculture development in Tamil Nadu. Chennai: Central Institute of Brackishwater Aquaculture.Google Scholar
  15. Kathiresan, K., & Rajendran, N. (2005). Coastal mangrove forests mitigated tsunami. Estuarine, Coastal and Shelf Science,65, 601–606.CrossRefGoogle Scholar
  16. Lucas, R. M., Ellison, J. C., Mitchell, A., Donnelly, B., Finlayson, M., & Milne, A. K. (2002). Use of stereo aerial photography for quantifying changes in the extent and height of mangroves in tropical Australia. Wetlands Ecology and Management,10, 161–175.CrossRefGoogle Scholar
  17. Miller, S. D., Goulden, M. L., Menton, M. C., Rocha, H. R., Freitas, H. C., Figueira, A. M. S., et al. (2004). Biometric and micrometeorological measurements of tropical forest carbon balance. Ecological Applications,14, 114–126.CrossRefGoogle Scholar
  18. Panigrahy, S., Murthy, T. V. R., Patel, J. G., & Singh, T. S. (2012). Wetlands of India: Inventory and assessment at 1:50,000 scale using geospatial techniques. Current Science,106(6), 852–856.Google Scholar
  19. Proisy, C., Couteron, P., & Fromard, F. (2007). Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images. Remote Sensing of Environment,109, 379–392.CrossRefGoogle Scholar
  20. Ramasubramanian, R., Gnanappazham, L., Ravishankar, T., & Navamuniyammal, M. (2006). Mangroves of Godavari—Analysis through remote sensing approach. Wetlands Ecology and Management,14, 29–37.CrossRefGoogle Scholar
  21. Ravishankar, T., Gnanappazham, L., Ramasubramaniam, R., Sridhar, D., Navamuniyammal, M., & Selvam, V. (2004). Atlas of mangrove wetlands of India. Part II—Andhra Pradesh (p. 136). Chennai: M. S. Swaminathan Research Foundation.Google Scholar
  22. Satyanarayana, B. (2007). Application of remote sensing: An approach for distinguishing vegetation structure and decadal changes in mangroves. Kuala Terengganu: University Malaysia Terengganu.Google Scholar
  23. Satyanarayana, B., Thierry, B., Lo Seen, D., Raman, A. V., & Muthusankar, G. (2001). Remote sensing in mangrove research—Relationship between vegetation indices and dendrometric parameters: A case for Coringa, East coast of India. In Final proceedings of the 22nd Asian conference on remote sensing, National University of Singapore, Singapore (pp. 567–572).Google Scholar
  24. Selvam, V., Eganathan, P., Karunagaran, V. M., Ravishankar, T., & Ramasubramanian, R. (2004). Mangrove plants of Tamil Nadu. Chennai: M. S. Swaminathan Research Foundation.Google Scholar
  25. Selvam, V., Ravichandran, K. K., Gnanappazham, L., & Navamuniyammal, M. (2003). Assessment of community-based restoration of Pichavaram mangrove wetland using remote sensing data. Current Science,85(6), 794–798.Google Scholar
  26. Sesli, F. A. (2010). Mapping and monitoring temporal changes for coastline and coastal area by using aerial data images and digital photogrammetry: A case study from Samsun, Turkey. International Journal of the Physical Sciences,5(10), 1567–1575.Google Scholar
  27. Seto, K. C., & Fragkias, M. (2007). Mangrove conversion and aquaculture development in Vietnam: A remote sensing-based approach for evaluating the Ramsar Convention on Wetland. Global Environmental Change,17(3–4), 486–500.CrossRefGoogle Scholar
  28. Spalding, M., Kainuma, M., & Collins, L. (2010). World Atlas of Mangrove. A collaborative project of ITTO, ISME, FAO, UNEP-WCMC, UNESCO-MAB, UNU-INWEH, TNC. London: Earthscan.Google Scholar
  29. Tran, T. V., Tien Thi Xuan, A., Phan, N. H., Dahdouh-Guebas, F., & Koedam, N. (2014). Application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau, Vietnam. Biogeosciences,11, 3781–3795.CrossRefGoogle Scholar
  30. Twumasi, Y. A., & Merem, E. C. (2006). GIS and remote sensing applications in the assessment of change within a coastal environment in the Niger Delta Region of Nigeria. International Journal of Environmental Research and Public Health,3(1), 98–106.CrossRefGoogle Scholar
  31. Upadhyay, V. P., Ranjan, R., & Singh, J. S. (2002). Human-mangrove conflicts: The way out. Current Science,83(11), 1328–1336.Google Scholar
  32. Van Lavieren, H., Spalding, M., Alongi, D., Kainuma, M., Clusener-Godt, M., & Adeel, Z. (2012). Securing the future of mangroves: A policy brief. UNU-INWEH, UNESCO-MAB with ISME, ITTO, FAO, UNEP-WCMC, TNC. London: Earthscan.Google Scholar

Copyright information

© Indian Society of Remote Sensing 2019

Authors and Affiliations

  1. 1.Centre for Remote Sensing and GeoinformaticsSathyabama Institute of Science and TechnologySholinganallur, ChennaiIndia
  2. 2.Coastal System ResearchM. S. Swaminathan Research FoundationChennaiIndia
  3. 3.MicrobiologyM. S. Swaminathan Research FoundationChennaiIndia

Personalised recommendations