Chandrama Dey

Publications

• Mixed Pixel Analysis for Flood Mapping Using Extended Support Vector Machine

  Chandrama Dey, Xiuping Jia, D. Fraser, L.Wang

  2009 Digital Image Computing: Techniques and Applications, Melbourne; 01/2009

  This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the inf... [more] This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the ‘wet’ areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

• Decision Fusion for Reliable Flood Mapping Using Remote Sensing Images

  Chandrama Dey, Dr. Xiuping Jia, Dr. Don Fraser

  DICTA, Canberra, Australia; 01/2008

  Flood extent mapping is a basic tool for flood damage assessment, which can be done by digital classification techniques using satellite imageries, including the data recorded by radar and optical sensors. However, converting the data into the information we need is not a straightforward task. One o... [more] Flood extent mapping is a basic tool for flood damage assessment, which can be done by digital classification techniques using satellite imageries, including the data recorded by radar and optical sensors. However, converting the data into the information we need is not a straightforward task. One of the great challenges involved in the data interpretation is to separate the permanent water bodies and flooding regions, including both the fully inundated areas and the wet areas where trees and houses are partly covered with water. This paper adopts the decision fusion technique to combine the mapping results from radar data and the NDVI data derived from optical data. An improved capacity in terms of identifying the permanent or semi-permanent water bodies from flood inundated areas has been achieved. Computer software tools Multispec and Matlab were used.

• Decision Fusion for Reliable Flood Mapping Using Remote Sensing Images.

  Chandrama Dey, Xiuping Jia, Donald Fraser

  Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, DICTA 2008, Canberra, ACT, Australia, 1-3 December 2008; 01/2008