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Showing 1 to 3 of 3 for “"Linear spectral unmixing"”.

  1. Manifold learning based spectral unmixing of hyperspectral remote sensing data

    <p>Nonlinear mixing effects inherent in hyperspectral data are not properly represented in linear spectral unmixing models. Although direct nonlinear unmixing models provide capability to capture nonlinear phenomena, they are difficult to formulate and the results are not always generalizable. …

    purdue-thes Repository record for Manifold learning based spectral unmixing of hyperspectral remote sensing data (opens in a new tab)

  2. Suitability of Aster and SRTM dems, and satellite imagery in detailed geomorphological mapping in Dzanani Area of Makhado Local Municipality, Limpopo Province, Republic of South Africa

    Detailed geomorphological mapping is important for monitoring environmental phenomena, it is therefore crucial that the methods employed for mapping are accurate. The basis of remote sensing for geomorphological work is moving from the consideration of whether satellite data are accurate for …

    venda Repository record for Suitability of Aster and SRTM dems, and satellite imagery in detailed geomorphological mapping in Dzanani Area of Makhado Local Municipality, Limpopo Province, Republic of South Africa (opens in a new tab)

  3. Discriminating and mapping soil variability with hyperspectral reflectance data.

    … developing new mapping methodologies from hyperspectral remote sensing and reflectance spectroscopy. The spatially continuous and rich spectral information of hyperspectral data provides a powerful diagnostic tool for mapping and monitoring the earth’s surface materials. Similarly, reflectance …

    adelaide Repository record for Discriminating and mapping soil variability with hyperspectral reflectance data. (opens in a new tab)