To make the best use of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data an investigator needs to know the ratio of signal to random variability or noise (S/N ratio). The signal is land-cover dependent and decreases with both wavelength and atmospheric absorption and random noise comprises sensor noise and intra-pixel variability. The three existing methods for estimating the S/N ratio are inadequate as typical laboratory methods inflate, while dark current and image methods deflate the S/N ratio. We propose a new procedure called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intra-pixel variability using the semi-variogram...
An assessment of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) performance was made fo...
Five flight lines of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired over...
While much of traditional remote sensing in agricultural research was limited to the visible and ref...
The focus of the workshop was the assessment of data quality by the AVIRIS project. Summaries of 16 ...
Automated techniques were developed for the extraction and characterization of absorption features f...
Data from several AVIRIS flight lines were examined to assess instrument stability and response. Bot...
Low-altitude Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery of a corn...
Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data collected over a geologically diver...
After engineering flights aboard the NASA U-2 research aircraft in the winter of 1986 to 1987 and sp...
The potential of airborne imaging spectrometry for assessing and monitoring natural resources is stu...
Atmospheric correction of imaging spectroscopy data is required for quantitative analysis. Different...
Online access for this thesis was created in part with support from the Institute of Museum and Libr...
Remotely sensed data are affected by system (sensor and platform), and scene related effects. For qu...
There are many factors which reduce the accuracy of classification of objects in the satellite remot...
The AVIRIS instrument has been designed to do high spectral resolution remote sensing of the Earth. ...
An assessment of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) performance was made fo...
Five flight lines of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired over...
While much of traditional remote sensing in agricultural research was limited to the visible and ref...
The focus of the workshop was the assessment of data quality by the AVIRIS project. Summaries of 16 ...
Automated techniques were developed for the extraction and characterization of absorption features f...
Data from several AVIRIS flight lines were examined to assess instrument stability and response. Bot...
Low-altitude Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery of a corn...
Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data collected over a geologically diver...
After engineering flights aboard the NASA U-2 research aircraft in the winter of 1986 to 1987 and sp...
The potential of airborne imaging spectrometry for assessing and monitoring natural resources is stu...
Atmospheric correction of imaging spectroscopy data is required for quantitative analysis. Different...
Online access for this thesis was created in part with support from the Institute of Museum and Libr...
Remotely sensed data are affected by system (sensor and platform), and scene related effects. For qu...
There are many factors which reduce the accuracy of classification of objects in the satellite remot...
The AVIRIS instrument has been designed to do high spectral resolution remote sensing of the Earth. ...
An assessment of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) performance was made fo...
Five flight lines of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired over...
While much of traditional remote sensing in agricultural research was limited to the visible and ref...