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Titolo:
FUZZY CLASSIFICATION OF SPATIALLY DEGRADED THEMATIC MAPPER DATA FOR THE ESTIMATION OF SUB-PIXEL COMPONENTS
Autore:
MASELLI F; RODOLFI A; CONESE C;
Indirizzi:
CNR,IATA,P DELLE CASCINE 18 I-50144 FLORENCE ITALY ACCADEMIA GEOG,CESIA I-50129 FLORENCE ITALY
Titolo Testata:
International journal of remote sensing
fascicolo: 3, volume: 17, anno: 1996,
pagine: 537 - 551
SICI:
0143-1161(1996)17:3<537:FCOSDT>2.0.ZU;2-B
Fonte:
ISI
Lingua:
ENG
Soggetto:
MAXIMUM-LIKELIHOOD CLASSIFICATION; REMOTELY SENSED DATA; PRIOR PROBABILITIES; LAND COVER; REPRESENTATION; COEFFICIENT; MEMBERSHIP; AGREEMENT; ACCURACY; IMAGES;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Science Citation Index Expanded
Citazioni:
32
Recensione:
Indirizzi per estratti:
Citazione:
F. Maselli et al., "FUZZY CLASSIFICATION OF SPATIALLY DEGRADED THEMATIC MAPPER DATA FOR THE ESTIMATION OF SUB-PIXEL COMPONENTS", International journal of remote sensing, 17(3), 1996, pp. 537-551

Abstract

Fuzzy classification procedures are hypothesized to provide more class membership information than hard methods as well as specific insights about sub-pixel components. This hypothesis is investigated in the present work using ancillary and spatially degraded Thematic Mapper (TM) data of a wide valley in central Italy. Hard and fuzzy modified maximum likelihood classifications (MLC) were applied to the data set. Fuzzy membership grades were found to be related to class cover proportions for each degraded pixel. Also, fuzzy probabilities were able to provide more precise estimates of class distribution, as measured by Kappa coefficients of agreement, with respect to hard attributions. Further analysis showed that this improvement was chiefly due to a better characterization of mixed, uncertainly attributable pixels. These results are of great interest for definition of the cases for which the fuzzy approach is appropriate.

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Documento generato il 20/09/20 alle ore 06:26:26