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A hybrid approach for water body identification from satellite images using NDWI mapping and histogram of gradients

  • S.I. : Multifaceted Intelligent Computing Systems (MICS)
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Abstract

Application of different water identification indices and their modified form with a threshold is a common practice in surface water identification from multispectral images. Implementation of the statistical features of water present in such images to improve the accuracy of existing approaches is a novel application. A dynamic threshold selection is more suitable for the detection of sediment–water. In consideration of the facts, the present study proposed a hybrid approach for automatic surface water detection. Fuzzy c-means, NDWI, and a statistical feature: gradient are used to classify and therefore identify surface water. The study area, the river basin of Sundarban, is chosen due to its nature of water bodies such as wide rivers, narrow water streams, and sediment–water. The algorithm works with minimum human interaction. The method is validated by applying on Sentinal-2 and WorldView-2 images having a spatial resolution of 10 m and 0.46 m, respectively, and is found the accuracy is 97%.

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Authors and Affiliations

  1. Dr. B.C.Roy Engineering College, Durgapur, India

    Tanmoy Halder

  2. Department of Computer Science and Engineering, Assam University Silchar, Silchar, India

    Ramen Pal, Sunita Sarkar, Somnath Mukhopadhyay & Nishtha Roy

  3. RRSC-East, NRSC, ISRO, Kolkata, India

    Debasish Chakraborty

  4. Department of Computer Science, Burdwan University, Burdwan, India

    Sunil Karforma

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  1. Tanmoy Halder
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  2. Debasish Chakraborty
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  3. Ramen Pal
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Halder, T., Chakraborty, D., Pal, R. et al. A hybrid approach for water body identification from satellite images using NDWI mapping and histogram of gradients. Innovations Syst Softw Eng (2021). https://doi.org/10.1007/s11334-021-00414-6

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