This tutorial is designed to provide an overview of selected methods for analysis of imaging spectrometer data. "Calibration " to reflectance is a prerequisite for most analysis approaches. A brief review of both empirical and model-based methods for recovery of apparent surface reflectance from the data is presented. Data analysis methods discussed include single pixel spectrum analysis, both empirical and feature based approaches to spectral classification of imaging spectrometer data, and the use of linear spectral unmixing to determine abundances of materials occurring with sub-pixel distributions. 1
Abstract: Principles of the hyperspectral analysis for identification of the material comp...
Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in ...
Surface reflectance spectra retrieved from remotely sensed hyperspectral imaging data using radiativ...
Abstract—Imaging spectrometers collect unique data sets that are simultaneously a stack of spectral ...
KEY WORDS: imaging spectrometer, dark current, spectral and radiometric data correction. The paper p...
Spectral imaging has been extensively applied in many fields, including agriculture, environmental m...
Hyperspectral imaging is concerned with the measurement, analysis, and interpretation of spectra acq...
Spectral Imaging or Chemical Imaging is the determination of the chemical identity of species and th...
Hyperspectral Imaging is a method of collecting and processing the information across pre-defined el...
Estimates of spectrometer bandpass, sampling interval, and signal-to-noise ratio required for identi...
Spectral data reduction is a crucial step, as so important as the acquisition process. Rigor shall b...
This paper presents a software calibration/characterization utility aimed to automatically perform ...
We are comparing three methods of mapping analysis tools for imaging spectroscopy data. The purpose ...
Several techniques are becoming common in the analysis of imaging spectrometer data that can lead to...
hyperspectral remote sensing, spectroscopy, absorption feature analysis, contextual analysis, mappin...
Abstract: Principles of the hyperspectral analysis for identification of the material comp...
Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in ...
Surface reflectance spectra retrieved from remotely sensed hyperspectral imaging data using radiativ...
Abstract—Imaging spectrometers collect unique data sets that are simultaneously a stack of spectral ...
KEY WORDS: imaging spectrometer, dark current, spectral and radiometric data correction. The paper p...
Spectral imaging has been extensively applied in many fields, including agriculture, environmental m...
Hyperspectral imaging is concerned with the measurement, analysis, and interpretation of spectra acq...
Spectral Imaging or Chemical Imaging is the determination of the chemical identity of species and th...
Hyperspectral Imaging is a method of collecting and processing the information across pre-defined el...
Estimates of spectrometer bandpass, sampling interval, and signal-to-noise ratio required for identi...
Spectral data reduction is a crucial step, as so important as the acquisition process. Rigor shall b...
This paper presents a software calibration/characterization utility aimed to automatically perform ...
We are comparing three methods of mapping analysis tools for imaging spectroscopy data. The purpose ...
Several techniques are becoming common in the analysis of imaging spectrometer data that can lead to...
hyperspectral remote sensing, spectroscopy, absorption feature analysis, contextual analysis, mappin...
Abstract: Principles of the hyperspectral analysis for identification of the material comp...
Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in ...
Surface reflectance spectra retrieved from remotely sensed hyperspectral imaging data using radiativ...