TY - GEN
T1 - Unsupervised Classification of Aviris-NG Hyperspectral Images
AU - Cui, Kangning
AU - Plemmons, Robert J.
PY - 2021
Y1 - 2021
N2 - In hyperspectral imaging for remote sensing, learning from unlabeled data by unsupervised methods is very challenging and it is the subject of considerable recent interest since the collection of large datasets by aircraft, UAVs and satellites has become ubiquitous. We experiment with unsupervised endmember extraction and classification of hyperspectral data collected over India by NASA's AVIRIS-NG airborne remote sensor. We have downloaded some of this data from the NASA-JPL portal in Pasadena, CA, for the purpose of studying land cover and land usage, and especially forests, in India. We report on results from our experiments with unsupervised endmember-based methods and clustering methods for classifying images from a mixed forest region that we selected from the Shoolpaneshwar Wildlife Sanctuary in Western In-dia. Randomized numerical methods are used to speed up the large-scale computations.
AB - In hyperspectral imaging for remote sensing, learning from unlabeled data by unsupervised methods is very challenging and it is the subject of considerable recent interest since the collection of large datasets by aircraft, UAVs and satellites has become ubiquitous. We experiment with unsupervised endmember extraction and classification of hyperspectral data collected over India by NASA's AVIRIS-NG airborne remote sensor. We have downloaded some of this data from the NASA-JPL portal in Pasadena, CA, for the purpose of studying land cover and land usage, and especially forests, in India. We report on results from our experiments with unsupervised endmember-based methods and clustering methods for classifying images from a mixed forest region that we selected from the Shoolpaneshwar Wildlife Sanctuary in Western In-dia. Randomized numerical methods are used to speed up the large-scale computations.
KW - clustering
KW - endmembers
KW - forests
KW - India
KW - randomized computations
KW - unlabeled AVIRIS-NG data
KW - Unsupervised hyperspectral classification
UR - http://www.scopus.com/inward/record.url?scp=85112804639&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85112804639&origin=recordpage
U2 - 10.1109/WHISPERS52202.2021.9484006
DO - 10.1109/WHISPERS52202.2021.9484006
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781665411745
T3 - Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
BT - 2021 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
PB - IEEE
T2 - 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS 2021)
Y2 - 24 March 2021 through 26 March 2021
ER -