THÃS EE - CESBIO - UniversitÃ© Toulouse III - Paul Sabatier

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Chapitre 3. Article 1Additional error (%)Additional error due to ambiguity - p(B)=0.58L=17 L=2L=46 L=8L=165L=32L=6443210-40 -35 -30 -25 -20 -15Ambiguity ratio (dB)Figure 7. Effect of A on the additional error due to ambiguityThe error also varies with ∆r and I 1,B . Figure 8 shows the additional error when a=-17dB, forfour values of I 1,B from -20dB to -5dB, as a function of ∆r and L. For sufficiently high valuesof both ∆r and L, the additional error is negligible (below 2%). When the class separability ispoor (∆r
Chapitre 3. Article 1In summary, ambiguities can have a critical impact on the performance of the classificationmethods when the ambiguity ratio is high (a=-17dB), if the class separability is low and/or ifthe number of looks is low. For a given SAR system, the methods should therefore be appliedonly when the classes are highly separable. Further simulations show that when the ambiguityis better than -30dB, the additional error is however limited to 6% in the very worst case,including poorly separable classes.B. Impact of the temporal samplingIn both methods, it is generally implicitly supposed that the class separability, measured by∆r, is due mostly to the outstanding behaviour of the intensity ratio (TC or PR) of one class ofinterest, which reaches peculiar values in time, while the intensity ratio of the other classremains relatively constant around its typical value. We suppose here that the class of interestis class B, and that its intensity ratio is remarkable because of its high values (r B >r A ).In some applications, the outstanding radiometric behaviour of class B is caused by a pointevent, and lasts forever after the event. In that case, the timing of the data acquisitions is notvery important, provided one date is available after the event for the PR method, and one datebefore and one after for the TC method. Events such as deforestation or urbanization wouldbe illustrative of this category.In other situations, the outstanding behaviour of class B is caused by a phenomenon, whichlasts for a finite period during which the intensity ratio of class B expresses its particularity,and then stops. Applications such as crop monitoring or flood monitoring, are concerned bythis approach. The ∆r parameter then represents the theoretical optimal class separabilityobtained when data are acquired at the optimal dates. In the multitemporal case introduced inII.D., the value of the observed class separability will depend on the timing of the availableacquisitions, and on the temporal backscattering profiles of the two classes during the periodwhen the phenomenon occurs. The temporal sampling of the acquisitions is an importantparameter in this case, as a high observation frequency will increase the probability to haveoptimal dates in the available dataset.In this sub-section, temporal backscattering profiles are modelled to simulate the typicalbehaviour of the two classes likely to be involved in classification schemes based on thetemporal change or the polarization ratio. These modelled profiles are then used to assess theeffect of the observation frequency on the classification performance.1) Theoretical data modelWe model here the backscattering profiles of the two classes during the period when thephenomenon occurs, which is assumed to last for c days.a) Temporal change methodWe illustrate the case corresponding for class B to a temporal backscattering increase, i.e. apositive intensity ratio. Therefore the multitemporal classification feature is⎡ Ip,dj⎤rTC, multi= max ⎢ ⎥ , where p is the polarization and (di) i=1:N represent the dates in thei,j>i⎢⎣Ip,di ⎥⎦available time-series, as suggested in II.D.1.88
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AbstractBecause of the importance o
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que Monique, Delphine et Maud à l
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Enfin, dans le cadre d’un troisi
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6.2. Perspectives..................
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Liste des tableauxTableau 1. Liste
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Chapitre 1. Introduction générale
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Chapitre 6. Conclusion généraleLa
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Chapitre 6. Conclusion généraleco
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Annexe A. Rapport final du projet
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Annexe B. Présentation du projet
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Bibliographie[1] United Nations Dep
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[29] Lee J.-S., Grunes M.R., Pottie
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THÃS EE - CESBIO - UniversitÃ© Toulouse III - Paul Sabatier