Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 42 for “"hyperspectral data"”.
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Improving Identification of Area Targets by Integrated Analysis of Hyperspectral Data and Extracted Texture Features
Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture features on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the VNIR-SWIR portion of the electromagnetic spectrum. Haralick texture …
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Analysing the influence of TNT on Southern African trees grass and shrubs using in-situ hyperspectral data
… TNT from leaking landmines can be detected using hyperspectral remote sensing of plant foliage, with the aim of being an area reduction aid. Increasing concentrations of TNT was administered to a study sample of five species of trees, five species of grasses and four species of shrubs, and …
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The discrete wavelet transform as a precursor to leaf area index estimation and species classification using airborne hyperspectral data
… a critical challenge for effective analysis of hyperspectral data for vegetation applications. Discrete wavelet transform (DWT), through multiresolution analysis, offers oppurtunities both to reduce dimension and convey information at multiple spectral scales. In this study, we investigated the …
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Development of Ground-Level Hyperspectral Image Datasets and Analysis Tools, and their use towards a Feature Selection based Sensor Design Method for Material Classification
… Separately, in the field of remote sensing, the hyperspectral camera has been used to perform classification tasks on natural and man-made objects from typically aerial or satellite platforms. Hyperspectral data is characterized by a very fine spectral resolution, resulting in a significant …
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Map-guided hyperspectral image superpixel segmentation using semi-supervised partial membership latent Dirichlet allocation
… However, because of the high dimensionality of hyperspectral imagery, these regular superpixel segmentation algorithms often do not perform well in hyperspectral imagery. Although there are some authors who have modified some regular superpixel segmentation algorithms to fit the hyperspectral …
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Ground-Based Hyperspectral Imaging and Data Analysis for Near-Vertical Outcrop Surfaces
… remote sensing technology have expanded outcrop data collection and analysis capabilities creating new opportunities to carry out geological studies in greater detail. Until recently, the hyperspectral data used in geology were acquired mostly from airborne platforms along with some from …
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RANDOM PROJECTION AND SVD METHODS IN HYPERSPECTRAL IMAGING
Hyperspectral imaging provides researchers with abundant information with which to study the characteristics of objects in a scene. Processing the massive hyperspectral imagery datasets in a way that efficiently provides useful information becomes an important issue. In this thesis, we consider …
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The Assessment of habitat condition and consevation status of lowland British woodlands using earth observation techniques.
… as identified in the literature. Airborne hyperspectral data (visible and near-infrared) and small footprint LiDAR capturing both discrete-return (DR) and full-waveform (FW) data were acquired simultaneously, under both leaf-on and leaf-off conditions in 2010. For the combined leaf-on and …
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Data driven estimation of soil and vegetation attributes using airborne remote sensing
… and food security. However, most of the soil data available globally are of coarse resolutions at scales of 1:5 million and lack quantitative information for modeling and land management decisions at field or catchment scales. Thus the need for a spatially contiguous quantitative soil …
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Non-invasive estimation of skin chromophores using Hyperspectral Imaging
… can potentially mitigate these consequences. Hyperspectral imaging (HSI) has shown promise as a non-invasive technique to analyze skin lesions. Images taken of human skin using a hyperspectral camera are a result of numerous elements in the skin. Being a turbid, inhomogeneous material, the …
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Non-invasive Estimation of Skin Chromophores Using Hyperspectral Imaging
… can potentially mitigate these consequences. Hyperspectral imaging (HSI) has shown promise as a non-invasive technique to analyze skin lesions. Images taken of human skin using a hyperspectral camera are a result of numerous elements in the skin. Being a turbid, inhomogeneous material, the …
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Superpixels for Hyperspectral Image Analysis
… optical imaging sensors, hyperpsectral data has become increasingly popular, necessitating development of algorithms for robust image analysis with such data. This thesis contributes methods that efficiently and robustly exploits superpixels for hyperspectral data. We study and quantify …
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Fast algorithms for wavelet-based analysis of hyperspectral signatures
Hyperspectral sensors promise great improvements in the quality of information gathered for remote sensing applications. However, they also present a huge challenge to data storage and computing systems. Thus there is a great need for reliable compression schemes, as well as analysis tools that can …
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Analysis of forest areas by advanced remote sensing systems based on hyperspectral and LIDAR data
… composition, trees stem volume, height, etc. Hyperspectral and LIDAR remote sensing data can provide useful information to the identification of these attributes: hyperspectral data with their dense sampling of the spectral signatures are important for the classification of tree spe-cies, …
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DeepGeoMap
… deep learning improved the way remote sensing data is processed. The classification of hyperspectral data is no exception. 2D or 3D convolutional neural networks have outperformed classical algorithms on hyperspectral image classification in many cases. However, geological hyperspectral image …
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Evaluation and Application of a New Shape-sensitive Metric Useful for Characterizing Both Spectral Curves and Lidar Waveforms
<p>This dissertation seeks to investigate hyperspectral and waveform LiDAR datasets through a new analytical framework called Moment Distance method that uses a metric derived from the shape of the curve (spectral or waveform). In the case of hyperspectral data, the shape of the reflectance curve …
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Deep learning applications in hyperspectral imaging for agriculture: image reconstruction and model design for quality prediction
Non-invasive techniques, such as hyperspectral imaging (HSI), are crucial for analyzing the detailed chemical and structural composition of agricultural products. By capturing both spectral and spatial information simultaneously, HSI enables advanced analysis of key quality attributes in …
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Variations in modelled and measured hyperspectral remote sensing reflectance
Measurements of hyperspectral surface reflectance, with a spectral range of 350-800nm and sampling interval of 3.3nm, were made in Scottish coastal waters, the Bristol Channel and the Atlantic Ocean. Analysis of the shape of these spectra by normalisation and differentiation revealed three …
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Advances in the Hyperspectral Imaging Microscope Spectrometer Method, and Application for Measuring the Spectral Reflectance of Light Absorbing Aerosols from the South Cascades, Colorado Rockies, and Iceland
… optical properties (Kaspari et al., 2014). A new hyperspectral imaging microscope spectrometer (HIMS) method was recently developed to measure LAA spectral reflectance at the particle scale. The objectives for this study are to do the following: 1. Advance the HIMS method by determining the …
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