Title
Comparison and combination of multiband classifiers for landsat urban land cover mapping
Abstract
In this paper we provide a first assessment of the characterization of an urban and suburban area using, Landsat multispectral data. We first analyze classification algorithms, in particular the spectral angle mapper and the fuzzy ARTMAP neural networks, may help in recognizing the classes of urban land cover. Then, we try and combine he classification maps using and comparing different existing approaches, like majority voting and opinion pools, and proposing a new one, named best partial accuracy combination.
Year
DOI
Venue
2005
10.1109/IGARSS.2005.1525655
Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. Proceedings. 2005 IEEE International
Keywords
Field
DocType
image sensors,satellites,remote sensing,neural network,image resolution,majority voting,spatial resolution,image analysis
Computer vision,Satellite,Image sensor,Computer science,Remote sensing,Artificial intelligence,Image resolution,Land cover
Conference
Volume
ISSN
ISBN
4
2153-6996
0-7803-9050-4
Citations 
PageRank 
References 
2
0.58
3
Authors
4
Name
Order
Citations
PageRank
Gianni Lisini120721.99
Fabio Dell'Acqua247857.84
Giovanna Trianni39010.92
P. Gamba431331.71