{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,19]],"date-time":"2026-04-19T07:56:08Z","timestamp":1776585368259,"version":"3.51.2"},"reference-count":29,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2013,12,2]],"date-time":"2013-12-02T00:00:00Z","timestamp":1385942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Multi-temporal satellite imagery can be composited over a season (or other time period) to produce imagery which is representative of that period, using techniques which will reduce contamination by cloud and other problems. For the purposes of vegetation monitoring, a commonly used technique is the Maximum NDVI Composite, used in conjunction with variety of other constraints. The current paper proposes an alternative based on the medoid (in reflectance space) over the time period (the medoid is a multi-dimensional analogue of the median), which is robust against extreme values, and appears to be better at producing imagery which is representative of the time period. For each pixel, the medoid is always selected from the available dates, so the result is always a single observation for that pixel, thus preserving relationships between bands. The method is applied to Landsat TM\/ETM+ imagery to create seasonal reflectance images (four per year), with the aim being a regular time series of reflectance values which captures the variability at seasonal time scales. Analysis of the seasonal reflectance values suggests that resulting temporal image composites are more representative of the time series than the maximum NDVI seasonal composite.<\/jats:p>","DOI":"10.3390\/rs5126481","type":"journal-article","created":{"date-parts":[[2013,12,3]],"date-time":"2013-12-03T03:18:09Z","timestamp":1386040689000},"page":"6481-6500","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":237,"title":["Seasonal Composite Landsat TM\/ETM+ Images Using the Medoid (a Multi-Dimensional Median)"],"prefix":"10.3390","volume":"5","author":[{"given":"Neil","family":"Flood","sequence":"first","affiliation":[{"name":"Joint Remote Sensing Research Program, School of Geography, Planning and Environmental Management, University of Queensland, St Lucia, QLD 4072, Australia"},{"name":"Department of Science, Information Technology, Innovation and the Arts, 41 Boggo Rd, Dutton Park, QLD 4102, Australia\u00a0"}]}],"member":"1968","published-online":{"date-parts":[[2013,12,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1080\/01431168608948945","article-title":"Characteristics of maximum-value composite images from temporal AVHRR data","volume":"7","author":"Holben","year":"1986","journal-title":"Int. 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