A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fr...
In order to understand the characteristics of the data collected by hyperspectral imaging systems, i...
We present the results of an analysis that combines coarse and fine spatial resolution remote sensin...
This work demonstrates the development and implementation of a Fully Constrained Least Squares (FCLS...
The complexity of pixel composition of orbital images has been commonly referred to the spectral mix...
This report documents the algorithms used in the program MIXMOD to analyse mixed pixel data (assumin...
Researchers in remote sensing have attempted to increase the accuracy of land cover information extr...
Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mappi...
In the region covered by variable amounts of vegetation, pixel spectra received by remotely-sensed s...
Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mappi...
Hyperspectral imagery collected from airborne or satellite sources inevitably suffers from spectral ...
International audienceIn this paper we present a framework to generate a land cover classification f...
Linear spectral mixture models can be standardized by using endmembers that span the global mixing s...
International audienceHyperspectral imagery collected from airborne or satellite sources inevitably ...
As an important indicator of anthropogenic impacts on the Earth’s surface, it is of great necessity ...
Knowledge of land cover type and vegetation condition at continental-to-global scales is critical fo...
In order to understand the characteristics of the data collected by hyperspectral imaging systems, i...
We present the results of an analysis that combines coarse and fine spatial resolution remote sensin...
This work demonstrates the development and implementation of a Fully Constrained Least Squares (FCLS...
The complexity of pixel composition of orbital images has been commonly referred to the spectral mix...
This report documents the algorithms used in the program MIXMOD to analyse mixed pixel data (assumin...
Researchers in remote sensing have attempted to increase the accuracy of land cover information extr...
Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mappi...
In the region covered by variable amounts of vegetation, pixel spectra received by remotely-sensed s...
Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mappi...
Hyperspectral imagery collected from airborne or satellite sources inevitably suffers from spectral ...
International audienceIn this paper we present a framework to generate a land cover classification f...
Linear spectral mixture models can be standardized by using endmembers that span the global mixing s...
International audienceHyperspectral imagery collected from airborne or satellite sources inevitably ...
As an important indicator of anthropogenic impacts on the Earth’s surface, it is of great necessity ...
Knowledge of land cover type and vegetation condition at continental-to-global scales is critical fo...
In order to understand the characteristics of the data collected by hyperspectral imaging systems, i...
We present the results of an analysis that combines coarse and fine spatial resolution remote sensin...
This work demonstrates the development and implementation of a Fully Constrained Least Squares (FCLS...