Abstract
Detection of snow cover changes is vital for avalanche hazard analysis and flood flashes that arise due to variation in temperature. Hence, multitemporal change detection is one of the practical mean to estimate the snow cover changes over larger area using remotely sensed data. There have been some previous studies that examined how accuracy of change detection analysis is affected by different topography effects over Northwestern Indian Himalayas. The present work emphases on the intercomparison of different topography effects on discrimination performance of fuzzy based change vector analysis (FCVA) as change detection algorithm that includes extraction of change-magnitude and change-direction from a specific pixel belongs multiple or partial membership. The qualitative and quantitative analysis of the proposed FCVA algorithm is performed under topographic conditions and topographic correction conditions. The experimental outcomes confirmed that in change category discrimination procedure, FCVA with topographic correction achieved 86.8% overall accuracy and 4.8% decay (82% of overall accuracy) is found in FCVA without topographic correction. This study suggests that by incorporating the topographic correction model over mountainous region satellite imagery, performance of FCVA algorithm can be significantly improved up to great extent in terms of determining actual change categories.
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The authors would like to express their gratitude to the anonymous referees and the editor for their constructive comments and valuable suggestions, that helped to significantly improve the earlier version of manuscript. The authors are also thankful to NASA and United States Geological Survey (USGS) for making the MODIS and ASTER Global DEM version 2 data, respectively, available to us for research and educational purposes.
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Responsible Editor: A. P. Dimri.
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Singh, S., Talwar, R. An intercomparison of different topography effects on discrimination performance of fuzzy change vector analysis algorithm. Meteorol Atmos Phys 130, 125–136 (2018). https://doi.org/10.1007/s00703-016-0494-5
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DOI: https://doi.org/10.1007/s00703-016-0494-5