6533b85bfe1ef96bd12bb6be
RESEARCH PRODUCT
A Simple Fusion Method for Image Time Series Based on the Estimation of Image Temporal Validity
Gloria BordognaGabriele CandianiPascal PonceletAgnès BéguéMar BisquertMaguelonne Teisseiresubject
TeledeteccióComputer scienceforêt tropicalehttp://aims.fao.org/aos/agrovoc/c_714remote sensingSimple (abstract algebra)K01 - Foresterie - Considérations généralesBiomassehttp://aims.fao.org/aos/agrovoc/c_6498validationUtilisation des terresEucalyptusFusionQhttp://aims.fao.org/aos/agrovoc/c_14093http://aims.fao.org/aos/agrovoc/c_9000094Plantation forestièreséquestration du carbonehttp://aims.fao.org/aos/agrovoc/c_926http://aims.fao.org/aos/agrovoc/c_1070http://aims.fao.org/aos/agrovoc/c_25409http://aims.fao.org/aos/agrovoc/c_4182P01 - Conservation de la nature et ressources foncièresSpectrométriePhénologiehttp://aims.fao.org/aos/agrovoc/c_2683TélédétectionScienceImage (mathematics)Cartographie de l'occupation du solhttp://aims.fao.org/aos/agrovoc/c_24904TermodinàmicaCouverture végétalehttp://aims.fao.org/aos/agrovoc/c_7283http://aims.fao.org/aos/agrovoc/c_1666http://aims.fao.org/aos/agrovoc/c_8176http://aims.fao.org/aos/agrovoc/c_3048MODIS; Landsat; validation; remote sensingRemote sensingChangement climatiqueSeries (mathematics)business.industryCiències de la terraPattern recognitionVégétationhttp://aims.fao.org/aos/agrovoc/c_331583Constraint (information theory)http://aims.fao.org/aos/agrovoc/c_5774SpectroradiometerMODISSatelliteGeneral Earth and Planetary SciencesArtificial intelligenceU30 - Méthodes de recherchebusinessLandsatdescription
High-spatial-resolution satellites usually have the constraint of a low temporal frequency, which leads to long periods without information in cloudy areas. Furthermore, low-spatial-resolution satellites have higher revisit cycles. Combining information from high- and low- spatial-resolution satellites is thought a key factor for studies that require dense time series of high-resolution images, e.g., crop monitoring. There are several fusion methods in the bibliography, but they are time-consuming and complicated to implement. Moreover, the local evaluation of the fused images is rarely analyzed. In this paper, we present a simple and fast fusion method based on a weighted average of two input images (H and L ), which are weighted by their temporal validity to the image to be fused. The method was applied to two years (2009-2010) of Landsat and MODIS (MODerate Imaging Spectroradiometer) images that were acquired over a cropped area in Brazil. The fusion method was evaluated at global and local scales. The results show that the fused images reproduced reliable crop temporal profiles and correctly delineated th e boundaries between two neighboring fields. The great est advantages of the proposed method are the execution time and ease of use, which allow us to obtain a fused image in less than five minutes.
year | journal | country | edition | language |
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2015-01-12 | Remote Sensing; Volume 7; Issue 1; Pages: 704-724 |