Hyperspectral remote sensing thesis


hyperspectral remote sensing thesis

class-discriminant information remains a research topic open to further investigation. In the first part of the thesis, a thorough study on the analysis of the spectral information contained in the hyperspectral images is presented. The burst of informative content conveyed in the hyperspectral images permits an improved characterization of different land coverages. Further to this, the capability of remote sensing to discriminate between stresses with similar mode of action is explored. The main differences between the treatments were in the shape and positions of the peaks that identify the red-edge. Recent advances in sensor technology have led to an increased availability of hyperspectral remote sensing images with high spectral and spatial resolutions. The approach exploits the tree representation of an image, allowing us to avoid additional filtering steps prior to the threshold selection, making the process computationally effective. Other vegetation indices used in this study were the Chlorophyll Normalized Difference Index (Chl NDI the Pigment Specific Simple Ratio for chlorophyll a and b (pssra and pssrb) and the Physiological Reflectance Index (PRI). Chl NDI was sensitive to high soil CO2 concentration in maize and barley, sub-lethal herbicide treatment at 10 - 40 level in barley and was insensitive to both low CO2 in the barley and maize as well as 10 herbicide treatment in maize. CO2 treated maize had double peaks at 718 and 730nm, with secondary peaks at 707 and 794nm. Pssrb could detect high CO2 level in maize and barley and all levels (5-40) of herbicide treatments.

Barley treated with herbicide had early peaks (a day after treatment) at 697, 715 and 717nm with a shoulder at 759nm, as the experiment progressed (16 days after treatment) the stress became apparent and the peak remained stationary at 730nm, the magnitude decreased to 712nm. The outcome of this dissertation advances the state-of-the-art by proposing novel methodologies for accurate hyperspectral image classification, where the results obtained by extensive experimentation on various real hyperspectral data sets confirmed their effectiveness. Remote sensing of vegetation is regarded as a valuable tool for the detection and discrimination of stress, especially over large or sensitive regions.

PhD thesis, University of Nottingham. The canopy reflectances of the plants were further analysed using the blue (400-550nm) and red (550-750nm). Maize treated with herbicide had maximum peaks at 716 and 723nm, with the shoulder at 759 nm; the peaks were similar with the control plots but decreased in magnitude. Sani, Yahaya (2013 determination and monitoring of vegetation stress using hyperspectral remote sensing. Pssra was a good indicator of early CO2 stress in maize and high CO2 in barley as well as 10- 40 herbicide treatments. These images are composed by hundreds of contiguous spectral channels, covering a wide spectral range of frequencies, in which each pixel contains a highly detailed representation of the reflectance locke an essay of the materials present on the ground, and a better characterization in terms of geometrical detail. The red-edge first-derivative for barley treated with CO2 were composed of maximum peaks between 716 and 730nm and smaller peaks at 699 and 759nm, the control had peaks at 727 and 730 nm, with similar smaller peaks. Inspired by the concept of granulometry, the proposed approach defines a novel granulometric characteristic function, which provides information on the image decomposition according to a given measure. Falco, Nicola (2015 advanced Spectral and Spatial Techniques for Hyperspectral Image Analysis and Classification.

Hyperspectral remote sensing thesis
hyperspectral remote sensing thesis


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