Title
Impact of Reducing Polarimetric SAR Input on the Uncertainty of Crop Classifications Based on the Random Forests Algorithm.
Abstract
Although the use of multidate polarimetric synthetic aperture radar (SAR) data for highly accurate land cover classification has been acknowledged in the literature, the high dimensionality of the data set remains a major issue. This study presents two different strategies to reduce the number of features in multidate SAR data sets: an accuracy-oriented reduction and an efficiency-oriented reducti...
Year
DOI
Venue
2012
10.1109/TGRS.2012.2189012
IEEE Transactions on Geoscience and Remote Sensing
Keywords
Field
DocType
Agriculture,Scattering,Correlation,Vegetation,Radio frequency,Accuracy,Uncertainty
Data set,Feature selection,Synthetic aperture radar,Remote sensing,Artificial intelligence,Contextual image classification,Random forest,Land cover,Computer vision,Radar imaging,Algorithm,Mathematics,Data reduction
Journal
Volume
Issue
ISSN
50
10
0196-2892
Citations 
PageRank 
References 
17
0.97
26
Authors
5
Name
Order
Citations
PageRank
Lien Loosvelt1301.82
Jan Peters2301.82
Henning Skriver326420.52
Bernard De Baets42994300.39
Niko E. C. Verhoest515619.13