{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T14:12:17Z","timestamp":1761919937620,"version":"build-2065373602"},"reference-count":19,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2015,1,12]],"date-time":"2015-01-12T00:00:00Z","timestamp":1421020800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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\u20132010) 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 the boundaries between two neighboring fields. The greatest 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.<\/jats:p>","DOI":"10.3390\/rs70100704","type":"journal-article","created":{"date-parts":[[2015,1,12]],"date-time":"2015-01-12T13:30:46Z","timestamp":1421069446000},"page":"704-724","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["A Simple Fusion Method for Image Time Series Based on the Estimation of Image Temporal Validity"],"prefix":"10.3390","volume":"7","author":[{"given":"Mar","family":"Bisquert","sequence":"first","affiliation":[{"name":"Laboratoire d'Informatique, de Robotique et de Micro\u00e9lectronique de Montpellier, 161 Rue Ada, 34090 Montpellier, France"},{"name":"Institute de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture, Unit\u00e9 Mixte de Recherche Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale, 500 Rue Jean Fran\u00e7ois Breton, 34093 Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6775-753X","authenticated-orcid":false,"given":"Gloria","family":"Bordogna","sequence":"additional","affiliation":[{"name":"Consiglio Nazionale delle Ricerhe, Istituto per il Rilevamento Elettromagnetico dell'Ambiente, Via Bassini 15, 20133 Milano, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9289-1052","authenticated-orcid":false,"given":"Agn\u00e8s","family":"B\u00e9gu\u00e9","sequence":"additional","affiliation":[{"name":"Centre de Coop\u00e9ration Internationale en Recherche Agronomique pour le D\u00e9veloppement, Unit\u00e9 Mixte de Recherche Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale, 500 Rue Jean Fran\u00e7ois Breton, 34093 Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5270-071X","authenticated-orcid":false,"given":"Gabriele","family":"Candiani","sequence":"additional","affiliation":[{"name":"Consiglio Nazionale delle Ricerhe, Istituto per il Rilevamento Elettromagnetico dell'Ambiente, Via Bassini 15, 20133 Milano, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maguelonne","family":"Teisseire","sequence":"additional","affiliation":[{"name":"Institute de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture, Unit\u00e9 Mixte de Recherche Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale, 500 Rue Jean Fran\u00e7ois Breton, 34093 Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pascal","family":"Poncelet","sequence":"additional","affiliation":[{"name":"Laboratoire d'Informatique, de Robotique et de Micro\u00e9lectronique de Montpellier, 161 Rue Ada, 34090 Montpellier, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,1,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.rse.2014.05.015","article-title":"Mapping short-rotation plantations at regional scale using MODIS time series: Case of eucalypt plantations in Brazil","volume":"152","author":"Dupuy","year":"2014","journal-title":"Remote Sens. 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