Land Cover Change detection of Medchal Mandal and Its Surroundings Using SAGA Software
DOI:
https://doi.org/10.48165/Keywords:
Land cover change matrix, Landsat images, Medchal Mandal and its surroundings, SAGAAbstract
Land cover change detection is more important to understand the present scenario of the geographical condition of the region, for this analyses SAGA (System for Automated Geoscientific Analysis) software used for calculates the change detection between two different years such as 2008 to 2017. In this study, we collected Landsat 8 and Landsat 5 satellite images with 30m resolution. The change detection classified based on k means cluster analysis in saga software. The clusters are a wasteland, Cultural waste, Follow land, barren land, Water, uncultivated land, cultivated misc and tree, other follow land and the Net area sown. Each one have 87,34,70, 20,23,77,53,53 and 89 km2 in 2008 and 79,51,47,31,41,68,50,60,and 89 km2 in 2017. Change matrix method detected 16% of changes in the study area. Colour occupation is the main resources for classification of this study for that we used unsupervised classification. The changes mainly occur in and around of national highway (NH 44). The major land cover changes are in the center portion of the study area and towards the south-east and North West small changes.
Downloads
References
. Fisher, P. F., and Unwin, D. J., eds. Representing GIS. Chichester, England: John Wiley & Sons (2005).
. Blaschke T, Object-based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote sensing 65(2010): 2-16.
. Carlson, T.N.; Azofeifa, S.G.A. Satellite Remote Sensing of Land Use changes in and around San Jose´, Costa Rica. Remote Sensing of Environment, 70(1999): 247–256.
. Gao J Digital Analysis of Remotely Sensed Imagery. McGraw-Hill Companies, Inc, New York, USA (2009).
. Almutairi, A., Warner, T.A. Change Detection Accuracy And Image Properties: A Study Using Simulated Data. Remote Sensing 2(6), (2010):1508–1529 CrossRef, Google Scholar [6]. Guerschman J.P.; Paruelo, J.M.; Bela, C.D.; Giallorenzi, M.C.; Pacin, F. Land cover
classification in the Argentine Pampas using multi-temporal Landsat TM data. International Journal of Remote Sensing, 24, (2003) 3381–3402.
. Balakeristanan ML, Md Said MA Land Use Land Cover Change Detection Using Remote Sensing Application for Land Sustainability. American Institute of Physics 1482(2012): 425- 430.
. Lu, D., and Mausel, P. Change Detection Techniques. Remote Sensing 25(20), (2004): 2365– 2407 CrossRef, Google Scholar
. Singh A. Review Article Digital change detection techniques using remotely-sensed data. International Journal of Remote Sensing 10: (1989): 989-1003.
. Smits, P.C., Dellepiane, S.G. and Schowengerdt, R.A., Quality assessment of image classification algorithms for land-cover mapping: A review and a proposal for a cost-based approach. International journal of remote sensing, 20 (8), (1999): 1461−1486.
. Butt A., Shabbir R., Ahmad S.S., Aziz N., Nawaz M., Shah M.T.A. Land cover classification and change detection analysis of Rawal watershed using remote sensing data J. Biol. Environ. Sci., 6 (1) (2015): 236-248.
. Michael L.Treglia An Introduction to GIS Using QGIS (v.2.12.2) (2017). https://mltconsecol.github.io/QGIS-Tutorial/QGIS- p.30 .
. Conrad, O., Bechtel, B., Bock, M., Dietrich, H., Fischer, E., Gerlitz, L., Wehberg, J., Wichmann, V., and Böhner, J. (2015): System for Automated Geoscientific Analyses (SAGA) v. 2.1.4, Geosci. Model Dev., 8, 1991-2007, doi:10.5194/gmd-8-1991-2015.
. Svidzinska, D. Methods of Geoecological Research: A Geoinformational Tutorial with the Open Source GIS SAGA. Kyiv, Logos, 402p. (in Ukrainian) (2014).
. Friedman, H. P., & Rubin, J. On some invariant criteria for grouping data. Journal of the American Statistical Association, 62, (1967):1158-1178.
. Radke, R.J. Image Change Detection Algorithms: A Systematic Survey. IEEE Trans. Image Process. 14(3), (2005): 294–307. CrossRef, MathSciNet, Google Scholar
. Alphan H, Doygun H, Unlukaplan YI Classification comparison of land cover using multitemporal Landsat and ASTER imagery: the case of Kahramanmaraş, Turkey. Environ Monit Assess 151(2009): 327-336.
. Czapla-Myers, J.S. Anderson N.J., Biggar, S.F. Early ground-based vicarious calibration results for Landsat 8 OLI Proceedings of SPIE, (2013): 8866
. Markham B. L., Seiferth J. C., Smid J., Barker J. L., "Lifetime responsivity behavior of the Landsat-5 thematic mapper", Proc. SPIE, 3427, (1998): 420-431.
. Naresh, D. Rajesh, V and Madhu, T. Integrated flood risk mapping and landuse/ landcover at local scale by using GIS in dhulapally region, IJEP 38(12): 1056-1063 (2018).
. Naresh Kumar, D, Nune sandeep, S. Jyothi and Madhu, T. Significant changes on landuse/ land cover by using remote sensing and GIS analysis-review, IJESC, vol.7, Issue No.3, (2017),5433-5435
. Storey, James, Michael Choate, and Kenton Lee. "Landsat 8 Operational Land Imager On Orbit Geometric Calibration and Performance." Remote Sensing 6, no. 11 (2014): 11127-11152. [23]. Gao J., and Liu Y. Determination of land degradation causes in Tongyu County, Northeast China via land cover change detection Int. J. Appl. Earth Obs. Geoinf., 12 (1), (2010): pp. 9-16 [24]. Mas J.F., Monitoring land-cover changes A comparison of change detection techniques. International Journal of Remote Sensing 20: (1999): 139-152.
. Tucker M, Asik O Detecting Land Use Changes at the Urban Fringe from Remotely Sensed Images in Ankara, Turkey. Geocarto International 17: (2002): 47-52.
. Treitz P, and Rogan J Remote sensing for mapping and monitoring land cover and land-use change. Progress in Planning 61: (2004): 269-279.