Vol. 5 (08) pp. 638-649 DOI: 10.21474/IJAR01/5101

VISUAL INTERPRETATION METHODS OF LAND USE/LAND COVER CHANGES & ANALYSIS USING GIS & REMOTE SENSING TECHNOLOGY: A CASE STUDY OF GOMUKHI RIVER BASIN OF TAMILNADU, INDIA.

, and
  • Centre for Remote Sensing, Bharathidasan University, Tiruchirappalli- 620023.
69 Downloads 291 Views
Crossref

Download Full Paper (PDF)

Abstract

The proper watershed or river basin development of a management strategy requires accurate measurement of the past and present land use/land cover changes of study area. These land use/land cover parameters determine the hydrological and ecological processes taking place in with a watershed area. This study done by satellite image of Landsat -7ETM+ in 2006, 2010, 2016 using Arc GIS 10.1 software and update the year of 2016image is using Geo Eye data. The Gomukhi river basin classified into NRSC level-2 land use /land cover classes Viz. crop land, fallow land, plantation, dense forest ,open forest ,degraded forest ,land with scrub, land without scrub, rivers/lakes(water bodies),settlement(Built Up land),and barren rocky. The overall analysis of study area the years of 2006 to 2016 land use land cover classes of viz., crop land (11.95%), plantation (1.57%) and dense forest (0.09%) is decreasing. And also fallow land (9.64%), open forest (0.47%), degraded forest (0.70%), land with scrub (1.41%), land without scrub (0.86%), rivers/lakes (0.15% and settlement (1.48%) respectively, barren rocky no changes accruing the study area. The land use /land cover classes transformation posed a serious threat to river basin or watershed resources. Here proper river basin planning and management is required or else these land use /land cover resources will soon be lost and no longer be able to play their role in socio economic based sustainable development of the study area.

Keywords

How to Cite This Article

V.Govindaraj, C.Lakshumanan and P.Ramki. (2017); VISUAL INTERPRETATION METHODS OF LAND USE/LAND COVER CHANGES & ANALYSIS USING GIS & REMOTE SENSING TECHNOLOGY: A CASE STUDY OF GOMUKHI RIVER BASIN OF TAMILNADU, INDIA., International Journal of Advanced Research (IJAR), 5 (08), 638-649, ISSN 2320-5407. DOI: https://doi.org/10.21474/IJAR01/5101

Corresponding Author

V.GOVINDARAJ
Centre for Remote Sensing, Bharathidasan University, Tiruchirappalli- 620023

Article Analytics

References

  1. Ashraf, A., 2013. Changing Hydrology of the Himalayan Watershed. Current Perspectives in Contaminant Hydrology and Water Resources Sustainability. Intech, Islamabad.
  2. Bazgeera, S., Sharma, P.K., Maheya, R.K., Hundala, S.S., Sood, A., 2008. Assessment of land use changes using remote sensing and GIS and their implications on climatic variability for Balachaur watershed in Punjab, India. Desert 12, 139?147.
  3. Boori, M.S., Vozˇenı?lek, V., Choudhary, K., 2015. Land use/cover disturbance due to tourism in Jesenı?ky Mountain, Czech Republic: a remote sensing and GIS based approach. Egypt. J. Remote Sens. Space Sci. 18 (1), 17?26. http://dx.doi.org/10.1016/ejrs.2014.12.002
  4. Butt, A., Shabbir, R., Ahmad, S.S., Aziz, N., Nawaz, M., Shah, M.T.A., 2015. Land cover classification and change detection analysis of Rawal watershed using remote sensing data. J. Biol. Environ. Sci. 6 (1), 236?248.
  5. Caruso, G., Rounsevell, M.D.A., Cojacarus, G., 2005. Exploring a spatiodynamicneighborhood-based model of residential behaviour in the Brussels peri-urban area. Int. J. Geograph. Inf. Sci. 19, 103?123.
  6. Dietzel, C., Herold, M., Hemphill, J.J., Clarke, K.C., 2005. Spatialtemporal dynamics in California?s central Valley: empirical links to urban theory. Int. J. Geograph. Inf. Sci. 19, 175?195.
  7. Fortin, M.J., Boots, B., Csillag, F., Remmel, T.K., 2003. On the role of spatial stochastic models in understanding landscape indices in ecology. Oikos 102, 203?212.
  8. Ford-Robertson, F.C. (ed). 1971. Terminology of Forest Science, Technology Practice and Products. Society of American Foresters, Washington, DC.
  9. Gajbhiye, S., Sharma, S.K., 2012. Land use and land cover change detection of Indra river watershed through remote sensing using multi-temporal satellite data. Int. J. GeomaticsGeosci. 3, 89?96.
  10. HaglerBailly, 2007. Environmental baseline study of Margala and Margala north blocks. MOL Pakistan Oil and Gas Company BV, Islamabad.
  11. Hu, H.B., Liu, H.Y., Hao, J.F., An, J., 2012. Analysis of land use change characteristics based on remote sensing and GIS in the Jiuxiang river watershed. Int. J. Smart Sens. Intell. Syst. 5, 811?823.
  12. Iqbal, M.F., Khan, I.A., 2014. Spatiotemporal land use land cover change analysis and erosion risk mapping of Azad Jammu and Kashmir, Pakistan. Egypt. J. Remote Sens. Space Sci. 17,209?229.
  13. Kearns, F.R., Kelly, N.M., Carter, J.L., Resh, V.H., 2005. A method for the use of landscape metrics in freshwater research and management. Landscape Ecol. 20, 113?125.
  14. Ministry of Rural development & NRSC (2011), Wastelands Atlas of India-2011, National Remote Sensing Centre, ISRO, Hyderabad.
  15. NRSA, (2006), Manual of National Land Use Land Cover Mapping Using Multi-Temporal Satellite Data, Department of Space, Hyderabad
  16. NRSA, (2007), Manual of National Wastelands Monitoring Using Multitemporal Satellite Data, Department of Space, Hyderabad.
  17. NRSC (2014), Land Use / Land Cover database on 1:50,000 scale, Natural Resources Census Project, LUCMD, LRUMG, RSAA, National Remote Sensing Centre, ISRO, Hyderabad
  18. Parker, D., Meretsky, V., 2004. Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics. Agric. Ecosyst. Environ. 101, 233?250.
  19. 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. Egypt. J.Remote Sens. Space Sci. 18, 77?84.
  20. Rawat, J.S., Biswas, V., Kumar, M., 2013a. Changes in land use/cover using geospatial techniques: a case study of Ramnagar town area, district Nainital, Uttarakhand, India. Egypt. J. Remote Sens. Space Sci. 16, 111?117.
  21. Stewart, T.J., Janssen, R., van Herwijnen, M., 2004. A genetic algorithm approach to multiobjective land use planning. Comput. Oper. Res. 31, 2293?2313.
  22. Singh, P., Gupta, A., Singh, M., 2014. Hydrological inferences from watershed analysis for water resource management using remote sensing and GIS techniques. Egypt. J. Remote Sens. Space Sci. 17, 111?121.
  23. Tanvir, A., Shahbaz, B., Suleri, A., 2006. Analysis of myths and realities of deforestation in northwest Pakistan: implications for forestry extension. Int. J. Agric. Biol. 8, 107?110.
  24. Turner, M.G., Gardner, R.H., O?Neill, R.V., 2001. Landscape Ecology in Theory and Practice Pattern and Process. Springer- Verlag, New York.
  25. 1973. International Classification and Mapping of Vegetation. Paris.
  26. Wang, X., Zheng, D., Shen, Y., 2008. Land use change and its driving forces on the Tibetan Plateau during 1990?2000. Catena 72, 56?66.
  27. Wani, S.P., Sreedevi, T.K., Reddy, T.S.V., Venkateswarlu, B., Prasad, C.S., 2008. Community watersheds for improved livelihoods through consortium approach in drought prone rain-fed areas. J. Hydrol. Res. Dev. 23, 55?77.

Similar Articles

Creative Commons Attribution 4.0 This work is licensed under a Creative Commons Attribution 4.0 International License.