Data/hora: 14/06/2024 00:21:04

Biblioteca(s): | Embrapa Solos.
Data corrente: | 10/01/2007
Data da última atualização: | 04/10/2016
Autoria: | MOTA, G. L. A.; FEITOSA, R. Q.; COUTINHO, H. L. C.; LIEDTKE, C. E.; MÜLLER, S; PAKZAD, K.; MEIRELLES, M. S. P.
Afiliação: | Guilherme L. A. Mota, PUC-RIO/UERJ; Raul Q. Feitosa, PUC-RIO/UERJ; HEITOR LUIZ DA COSTA COUTINHO, CNPS; Claus-Eberhard Liedtke, University of Hannover; Sönke Müller, University of Hannover; Kian Pakzad, University of Hannover; MARGARETH GONCALVES SIMOES, CNPS.
Título: | Multitemporal fuzzy classification model based on class transition possibilities.
Ano de publicação: | 2007
Fonte/Imprenta: | ISPRS Journal of Photogrammetry & Remote Sensing, Amsterdam, v. 62, n. 3, p. 186-200, Aug. 2007.
DOI: | 10.1016/j.isprsjprs.2007.04.001
Idioma: | Inglês
Conteúdo: | This paper proposes a new method to model temporal knowledge and to combine it with spectral and spatial knowledge within an integrated fuzzy automatic image classification framework for land-use land-cover map update applications. The classification model explores not only the object features, but also information about its class at a previous date. The method expresses temporal class dependencies by means of a transition diagram, assigning a possibility value to each class transition. A Genetic Algorithm (GA) carries out the class transition possibilities estimation. Temporal and spectral/spatial classification results are combined by means of fuzzy aggregation. The improvement achieved by the use of multitemporal knowledge rather than a pure monotemporal approach was assessed in a real application usingLANDSATimages from MidwestBrazil. The experiments showed that the use of temporal knowledge markedly improved the classification performance, in comparison to a conventional single-time classification. A further observation was that multitemporal knowledge may subsume the knowledge related to steady spatial attributes whose values do not significantly change over time.
Palavras-Chave: | Interpretação multitemporal; Lógica Fuzzy.
Thesagro: | Sensoriamento Remoto.
Categoria do assunto: | P Recursos Naturais, Ciências Ambientais e da Terra
Registro original: | Embrapa Solos (CNPS)
Exemplares: | CNPS - (12747-1) - UPC - AP - DD -  -  - 2008.00010 - DIS