Skip to main content
SpringerLink
Log in

Exploring 16 years changing dynamics for land use/land cover in Pearl City (Thoothukudi) with spatial technology

  • Published:
Spatial Information Research Aims and scope Submit manuscript

Abstract

Land use land cover (LU/LC) changes over the period are essential to understand the development of human activities within a region to define the impact of anthropogenic and natural activities. The virtual assessment of LU/LC changes between 2000 and 2016 is carried out in Pearl City (Thoothukudi) using Remote-Sensing data and GIS tool. This change detection is done by 15 m resolution cloud-free Advanced Spaceborne Thermal Emission and Reflection Radiometer data captured during the year 2000 and 2016. The dynamic changes depict the major land use features like settlements, saltpan, crop land, vegetation, barren and water body from satellite data through supervised classifications of a maximum likelihood algorithm. The classified images highlight a series of constructive results in settlement (4.30%), vegetation (4.00%), saltpan (0.24%) and pessimistic results in barren land (−7.68%), crop land (−0.64%) and water body (−0.23%) respectively. The study recommends that urbanization of settlement land usage is highly mobilized in Thoothukudi coastal areas.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Lambin, E. F., & Meyfroidt, P. (2011). Global land use change, economic globalization, and the looming land scarcity. Proceedings of the National Academy of Sciences, 108(9), 3465–3472.

    Article  Google Scholar 

  2. Wolter, P. T., Johnston, C. A., & Niemi, G. J. (2006). Land use land cover change in the US Great Lakes basin 1992 to 2001. Journal of Great Lakes Research, 32(3), 607–628.

    Article  Google Scholar 

  3. Erle, E., & Pontius, R. (2007). Land-use and land-cover change. In C. J. Cleveland (Ed.), Encyclopedia of earth. Washington, D.C.: Environmental Information Coalition, National Council for Science and the Environment. http://www.eoearth.org/article/Landuse_and_landcover_change.

  4. Meyer, W. B., & Turner, B. L. (1992). Human population growth and global land-use/cover change. Annual Review of Ecology and Systematics, 23, 39–61.

    Article  Google Scholar 

  5. Houghton, R. A. (2003). Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000. Tellus B, 55(2), 378–390.

    Google Scholar 

  6. Houghton, R. A., Hackler, J. L., & Lawrence, K. T. (1999). The US carbon budget: Contributions from land-use change. Science, 285(5427), 574–578.

    Article  Google Scholar 

  7. Ramankutty, N., & Foley, J. A. (1998). Characterizing patterns of global land use: An analysis of global croplands data. Global Biogeochemical Cycles, 12(4), 667–685.

    Article  Google Scholar 

  8. Townshend, J., Latham, J., Justice, C. O., Janetos, A., Conant, R., Arino, O., et al. (2011). International coordination of satellite land observations: Integrated observations of the land. In B. Ramachandran, C. O. Justice, & M. J. Abrams (Eds.), Land remote sensing and global environmental change, Remote sensing and digital image processing (Vol. 11, pp. 835–856). Springer. doi:10.1007/978-1-4419-6749-36.

  9. Khan, M. M. H., Bryceson, I., Kolivras, K. N., Faruque, F., Rahman, M. M., & Haque, U. (2015). Natural disasters and land-use/land-cover change in the southwest coastal areas of Bangladesh. Regional Environmental Change, 15(2), 241–250.

    Article  Google Scholar 

  10. Giri, C., Zhu, Z., & Reed, B. (2005). A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets. Remote Sensing of Environment, 94(1), 123–132.

    Article  Google Scholar 

  11. Pandey, P. C., Sharma, L. K., & Nathawat, M. S. (2012). Geospatial strategy for sustainable management of municipal solid waste for growing urban environment. Environmental Monitoring and Assessment, 184(4), 2419–2431.

    Article  Google Scholar 

  12. Anderson, J. R. (1976). A land use and land cover classification system for use with remote sensor data (Vol. 964). Washington, D.C.: US Government Printing Office.

    Google Scholar 

  13. Kumaravel, S., Gurugnanam, B., Bagyaraj, M., Venkatesan, S., Suresh, M., & Dharanirajan, K. (2013). Monitoring land cover changes in the parts of east cost of Tamilnadu and Pondicherry Union Territory using geospatial technology. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 2(4), ISSN: 2278–3075.

  14. Paudel, B., Zhang, Y. L., Li, S. C., Liu, L. S., Wu, X., & Khanal, N. R. (2016). Review of studies on land use and land cover change in Nepal. Journal of Mountain Science, 13(4), 643–660.

    Article  Google Scholar 

  15. Samanta, S., & Pal, D. K. (2016). Change detection of land use and land cover over a period of 20 years in Papua New Guinea. Natural Science, 8(03), 138.

    Article  Google Scholar 

  16. Rawat, J. S., & Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1), 77–84.

    Article  Google Scholar 

  17. Cohen, W. B., & Goward, S. N. (2004). Landsat’s role in ecological applications of remote sensing. BioScience, 54(6), 535–545.

    Article  Google Scholar 

  18. Tehrany, M. S., Pradhan, B., & Jebuv, M. N. (2014). A comparative assessment between object and pixel-based classification approaches for land use/land cover mapping using SPOT 5 imagery. Geocarto International, 29(4), 351–369.

    Article  Google Scholar 

  19. Rajesh, S. V. J. S. S., Rao, B. P., & Niranjan, K. (2017). Pennar (Somasila) to Cauvery (Grand Anicut) inter basin water transfer impact assessment on land use/land cover environment. Journal of Water Resource and Protection, 9(04), 393.

    Article  Google Scholar 

  20. Oyinloye, M. A. A., & Kufoniyi, O. (2013). Application of IKONOS satellite images in monitoring of urban landuse change in Ikeja, GRA, Lagos, Nigeria. International Journal of Engineering Science Invention, 2(5), 1–10.

    Google Scholar 

  21. Lu, D., Hetrick, S., & Moran, E. (2010). Land cover classification in a complex urban-rural landscape with QuickBird imagery. Photogrammetric Engineering & Remote Sensing, 76(10), 1159–1168.

    Article  Google Scholar 

  22. Waske, B., & Braun, M. (2009). Classifier ensembles for land cover mapping using multitemporal SAR imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 64(5), 450–457.

    Article  Google Scholar 

  23. Thenkabail, P. S., Schull, M., & Turral, H. (2005). Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data. Remote Sensing of Environment, 95(3), 317–341.

    Article  Google Scholar 

  24. Szuster, B. W., Chen, Q., & Borger, M. (2011). A comparison of classification techniques to support land cover and land use analysis in tropical coastal zones. Applied Geography, 31(2), 525–532.

    Article  Google Scholar 

  25. Yüksel, A., Akay, A. E., & Gundogan, R. (2008). Using ASTER imagery in land use/cover classification of eastern Mediterranean landscapes according to CORINE land cover project. Sensors, 8(2), 1237–1251.

    Article  Google Scholar 

  26. Kesgin, B., Esbah, H., & Kurucu, Y. (2009). Comparison of pixel-based and object-based classification methods in detecting land use/land cover dynamics. In Remote sensing for a changing Europe: Proceedings of the 28th symposium of the European association of remote sensing laboratories, Istanbul, Turkey, 2–5 June 2008 (p. 173). IOS Press.

  27. Nagamani, K., & Ramachandran, S. (2003). Land use/land cover in pondicherry using remote sensing and GIS. In Proceedings of the third international conference on environment and health, Chennai, India (pp. 15–17).

  28. Wilkie, D. S., & Finn, J. T. (1996). Remote sensing imagery for natural resources monitoring: A guide for first-time users. New York City: Columbia University Press.

    Google Scholar 

  29. Soundranayagam, J. P., Sivasubramanian, P., Chandrasekar, N., & Durairaj, K. S. P. (2011). An analysis of land use pattern in the industrial development city using high resolution satellite imagery. Journal of Geographical Sciences, 21(1), 79–88.

    Article  Google Scholar 

  30. Jamal, J. A. (2011). Dynamic land use/cover change modelling: Geosimulation and multiagent-based modelling. Berlin: Springer Science & Business Media.

    Google Scholar 

  31. Giri, C. P. (Ed.). (2012). Remote sensing of land use and land cover: Principles and applications. Boca Raton: CRC Press.

    Google Scholar 

  32. Ninomiya, Y., Fu, B., & Cudahy, T. J. (2005). Detecting lithology with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral thermal infrared “radiance-at-sensor” data. Remote Sensing of Environment, 99(1), 127–139.

    Article  Google Scholar 

  33. Shalaby, A., & Tateishi, R. (2007). Remote sensing and GIS for mapping and monitoring land cover and land-use changes in the Northwestern coastal zone of Egypt. Applied Geography, 27(1), 28–41.

    Article  Google Scholar 

  34. Otukei, J. R., & Blaschke, T. (2010). Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms. International Journal of Applied Earth Observation and Geoinformation, 12, S27–S31.

    Article  Google Scholar 

  35. Dean, A. M., & Smith, G. M. (2003). An evaluation of per-parcel land cover mapping using maximum likelihood class probabilities. International Journal of Remote Sensing, 24(14), 2905–2920.

    Article  Google Scholar 

  36. Richards, J. A., & Richards, J. A. (1999). Remote sensing digital image analysis (Vol. 3). Berlin et al.: Springer.

    Book  Google Scholar 

  37. Landgrebe, D. A. (2003). Signal theory methods in multispectral remote sensing (p. 508). New York: Wiley.

    Book  Google Scholar 

  38. He, C., Wei, A., Shi, P., Zhang, Q., & Zhao, Y. (2011). Detecting land-use/land-cover change in rural–urban fringe areas using extended change-vector analysis. International Journal of Applied Earth Observation and Geoinformation, 13(4), 572–585.

    Article  Google Scholar 

  39. Wang, Y. (Ed.). (2009). Remote sensing of coastal environments. Boca Raon: CRC Press.

    Google Scholar 

  40. Rosenfield, G. H., & Fitzpatrick-Lins, K. (1986). A coefficient of agreement as a measure of thematic classification accuracy. Photogrammetric Engineering and Remote Sensing, 52(2), 223–227.

    Google Scholar 

  41. Lu, D., Mausel, P., Brondizio, E., & Moran, E. (2004). Change detection techniques. International Journal of Remote Sensing, 25(12), 2365–2401.

    Article  Google Scholar 

  42. Selvam, S. (2012). Use of remote sensing and GIS techniques for land use and land cover mapping of Tuticorin Coast, Tamil Nadu. Universal Journal of Environmental Research and Technology, 2(4), 233–241.

    Google Scholar 

Download references

Acknowledgements

The authors are thankful to the Annamalai University for permitting us to work on this topic and Department of Forest, Government of Tamil Nadu for giving permission to conduct field work and to all well-wishers for their invariable support and suggestion throughout the period of study.

Author information

Authors and Affiliations

  1. Department of Earth Sciences, Annamalai University, Chidambaram, Tamil Nadu, India

    T. Immanuvel David, M. V. Mukesh, S. Kumaravel, G. Ramesh & R. Premkumar

Authors
  1. T. Immanuvel David
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. V. Mukesh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. Kumaravel
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. G. Ramesh
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. R. Premkumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. V. Mukesh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Immanuvel David, T., Mukesh, M.V., Kumaravel, S. et al. Exploring 16 years changing dynamics for land use/land cover in Pearl City (Thoothukudi) with spatial technology. Spat. Inf. Res. 25, 547–554 (2017). https://doi.org/10.1007/s41324-017-0120-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41324-017-0120-8

Keywords

Search

Navigation