Title :
A Comparison of Forest Classification using Hyperion and AVIRIS Hyperspectral Imagery
Author :
Cipar, John ; Cooley, Thomas ; Lockwood, Ronald
Author_Institution :
Space Vehicles Directorate, Air Force Res. Lab., Hanscom AFB, MA
fDate :
July 31 2006-Aug. 4 2006
Abstract :
We test how well a cluster-based unsupervised classification algorithm separates forest land covers. Our test data, Hyperion and AVIRIS images taken in northern Virginia during autumn, provide two spectrally distinct land covers: pine forests and senescent deciduous forests. We find that the algorithm successfully separates these land covers for AVIRIS data that has been spatially aggregated to simulate 30-m Hyperion GSD. The algorithm does not successfully separate the land covers for the Hyperion data.
Keywords :
forestry; geophysical signal processing; image classification; vegetation mapping; AVIRIS hyperspectral imagery; Hyperion GSD; Hyperion hyperspectral imagery; cluster based unsupervised classification algorithm; forest classification; forest land covers; northern Virginia; pine forests; senescent deciduous forests; Aircraft; Classification algorithms; Clustering algorithms; Hyperspectral imaging; Hyperspectral sensors; Laboratories; Signal to noise ratio; Spatial resolution; Testing; Vegetation mapping;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on
Conference_Location :
Denver, CO
Print_ISBN :
0-7803-9510-7
DOI :
10.1109/IGARSS.2006.506
