01966naa a2200241 a 450000100080000000500110000800800410001902400410006010000190010124501090012026000090022952011930023865000250143165300340145665300180149070000190150870000230152770000190155070000150156970000150158470000240159977301010162313391842016-10-04       2007    bl uuuu     u00u1 u    #d7 a10.1016/j.isprsjprs.2007.04.0012DOI1 aMOTA, G. L. A.  aMultitemporal fuzzy classification model based on class transition possibilities.h[electronic resource]  c2007  aThis 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.  aSensoriamento Remoto  aInterpretação multitemporal  aLógica Fuzzy1 aFEITOSA, R. Q.1 aCOUTINHO, H. L. C.1 aLIEDTKE, C. E.1 aMÜLLER, S1 aPAKZAD, K.1 aMEIRELLES, M. S. P.  tISPRS Journal of Photogrammetry & Remote Sensing, Amsterdamgv. 62, n. 3, p. 186-200, Aug. 2007.