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Land Use Land Cover Change Detection using Remote Sensing and GIS in Srinagar, India

by Ritu Saini, Pradeep Aswal, Mohd Tanzeem, Sanyam S. Saini
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 46
Year of Publication: 2019
Authors: Ritu Saini, Pradeep Aswal, Mohd Tanzeem, Sanyam S. Saini
10.5120/ijca2019919385

Ritu Saini, Pradeep Aswal, Mohd Tanzeem, Sanyam S. Saini . Land Use Land Cover Change Detection using Remote Sensing and GIS in Srinagar, India. International Journal of Computer Applications. 178, 46 ( Sep 2019), 42-50. DOI=10.5120/ijca2019919385

@article{ 10.5120/ijca2019919385,
author = { Ritu Saini, Pradeep Aswal, Mohd Tanzeem, Sanyam S. Saini },
title = { Land Use Land Cover Change Detection using Remote Sensing and GIS in Srinagar, India },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2019 },
volume = { 178 },
number = { 46 },
month = { Sep },
year = { 2019 },
issn = { 0975-8887 },
pages = { 42-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number46/30863-2019919385/ },
doi = { 10.5120/ijca2019919385 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:53:19.382039+05:30
%A Ritu Saini
%A Pradeep Aswal
%A Mohd Tanzeem
%A Sanyam S. Saini
%T Land Use Land Cover Change Detection using Remote Sensing and GIS in Srinagar, India
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 46
%P 42-50
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Ecosystems in urban areas are strongly influenced by anthropogenic activities. Spatial-temporal transformations that occur in different classes of land use/cover like Built-up, Vegetation and Water are the key drivers of global change that reflects the territorial and socio-economic progress of an area and have significant implications for many policy issues. The current study uses a maximum likelihood classification method to map five different land use land cover classes in the openly available Landsat satellite images of 2008 and 2016 for selected urban boundaries of Srinagar, India. Pixel to pixel change detection strategy is implemented to find out the changes occurred in individual land use land cover class. The results are compared and illustrated in the form of graph and maps for providing an interactive visual representation for administrators and policymakers.

References
  1. Asmala, A. (2012), Analysis of Maximum likelihood classification on multispectral data. Applied Mathematical Sciences, 6(129-132), pp 6425-6436.
  2. Aswal, P., Saini R., and Ansari M. T., 2018. Spatio Temporal Monitoring of Urban Sprawl using GIS and Remote Sensing Technique. International Journal of Computer Applications 182(27):11-24, November 2018.
  3. Bauer, M., Loeffelholz, B. and Wilson, B., 2005, October. Estimation, mapping and change analysis of impervious surface area by Landsat remote sensing. In Proceedings, Pecora 16 Conference (pp. 23-27).
  4. Benediktsson, J.A., Swain, P.H. and Ersoy, O.K., 1990. Neural network approaches versus statistical methods in classification of multisource remote sensing data.
  5. Byrne, G.F., Crapper, P.F. and Mayo, K.K., 1980. Monitoring land-cover change by principal component analysis of multitemporal Landsat data. Remote sensing of Environment, 10(3), pp.175-184.
  6. Civco, D.L., Hurd, J.D., Wilson, E.H., Song, M. and Zhang, Z., 2002, April. A comparison of land use and land cover change detection methods. In ASPRS-ACSM Annual Conference.
  7. Clark, W.A., 1982. Recent research on migration and mobility: a review and interpretation. Progress in planning, 18, pp.1-56.
  8. Colwell J. E Weber F. P 1981. Forest change detection. Proceedings of the 15th International Symposium on Remote Sensing of Environment, Ann Arbor, MI, USA (Ann Arbor, MI: ERIM), pp. 839–852.
  9. Gong, P., 1993. Change detection using principal component analysis and fuzzy set theory. Canadian Journal of Remote Sensing, 19(1), pp.22-29.
  10. Hord, R.M., 1982. Digital image processing of remotely sensed data. Elsevier.
  11. Nelson, R.F., 1983. Detecting forest canopy change due to insect activity using Landsat MSS. Photogrammetric Engineering and Remote Sensing, 49(9), pp.1303-1314.
  12. Singh, A., 1986. Change detection in the tropical forest environment of north-eastern India using Landsat. Remote sensing and tropical land management, pp.237-254.
  13. Singh, A., 1989. Review article digital change detection techniques using remotely-sensed data. International journal of remote sensing, 10(6), pp.989-1003.
  14. Tiwari, A., Suresh, M., Jain, K., Shoab, M., Dixit, A. and Pandey, A., 2018. Urban Landscape Dynamics for Quantifying the Changing Pattern of Urbanisation in Delhi. Journal of Rural Development, 37(2), pp.399-412.
  15. Malila, W.A., 1980, January. Change vector analysis: an approach for detecting forest changes with Landsat. In LARS symposia (p. 385).
  16. Mas, J.F., 1999. Monitoring land-cover changes comparison of change detection techniques. International journal of remote sensing, 20(1), pp.139-152.
  17. Tiwari, A. and Dixit, A., 2015. Unmanned aerial vehicle and geospatial technology pushing the limits of development. American Journal of Engineering Research, 4, pp.16-21.
  18. Tiwari, A. and Jain, K., 2014. GIS Steering smart future for smart Indian cities. International Journal of Scientific and Research Publications, 4(8), pp.442-446.
  19. Tiwari, A., Suresh, M. and Rai, A.K., 2014. Ecological Planning for Sustainable Development with a Green Technology: GIS. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 3(3), pp.2278-1323.
  20. Howarth, P.J. and Wickware, G.M., 1981. Procedures for change detection using Landsat digital data. International Journal of Remote Sensing, 2(3), pp.277-291.
  21. Maktav, D., Erbek, F.S. and Jürgens, C., 2005. Remote sensing of urban areas. International Journal of Remote Sensing, 26(4), pp.655-659.
  22. Yeh, A.G.O. and Li, X., 2001. A constrained CA model for the simulation and planning of sustainable urban forms by using GIS. Environment and Planning B: Planning and Design, 28(5), pp.733-753.
  23. Weismiller, R.A., Kristof, S.J., Scholz, D.K., Anuta, P.E. and Momin, S.A., 1977. Change detection in coastal zone environments. Photogrammetric Engineering and Remote Sensing, 43(12), pp.1533-1539.
Index Terms

Computer Science
Information Sciences

Keywords

Land use Land Cover Change Detection Remote Sensing GIS

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