Abstract
Determination and identification of land use–land cover (LULC) of urban area have become very challenging issue in planning a city development. In this paper, we report application of four classifiers to identify LULC using remote sensing data. In our study, LISS-III image dataset of February 2015, obtained from NRSC Hyderabad, India, for the region of Aurangabad city (India) has been used. It was found that all classifiers provided similar results for water body, whereas significant differences were detected for regions related to residential, rock, barren land and fallow land. The average values from these four classifiers are satisfactory in agreement with Toposheet obtained from the Survey of India.
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Acknowledgements
The authors would like to acknowledge (1) UGC–BSR fellowships (2) DST_FIST and (3) UGC-SAP(II)DRS Phase-I and Phase-II F.No.-3-42/2009 and 4-15/2015/DRS-II for Laboratory Facility to Department of CS & IT, Dr. B.A.M. University, Aurangabad(MS), India.
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Nagne, A.D., Dhumal, R., Vibhute, A., Kale, K.V., Mehrotra, S.C. (2017). Comparative Analysis of Different Land Use–Land Cover Classifiers on Remote Sensing LISS-III Sensors Dataset. In: Behera, H., Mohapatra, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 556. Springer, Singapore. https://doi.org/10.1007/978-981-10-3874-7_49
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DOI: https://doi.org/10.1007/978-981-10-3874-7_49
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