2016
DOI: 10.1016/j.rse.2015.11.032
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Abstract: New and previously unimaginable Landsat applications have been fostered by a policy change in 2008 that made analysis-ready Landsat data free and open access. Since 1972, Landsat has been collecting images of the Earth, with the early years of the program constrained by onboard satellite and ground systems, as well as limitations across the range of required computing, networking, and storage capabilities. Rather than robust on-satellite storage for transmission via high bandwidth downlink to a centralized sto… Show more

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Cited by 547 publications
(352 citation statements)
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References 37 publications
(47 reference statements)
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“…Our results along with those of others [26] demonstrate the capability of utilizing Landsat time series to further classify forest change events into more specific categories. The methodological opportunities here applied are a direct consequence of the richness of the Landsat archive over Canada, in contrast to many nations and regions globally where the application of these methods would be more limited [12,45]. Spectral metrics derived from Landsat time series provide a quantitative and spatially explicit opportunity to generate refined attribution detail related to forest harvest practices.…”
Section: Resultsmentioning
confidence: 99%
“…Our results along with those of others [26] demonstrate the capability of utilizing Landsat time series to further classify forest change events into more specific categories. The methodological opportunities here applied are a direct consequence of the richness of the Landsat archive over Canada, in contrast to many nations and regions globally where the application of these methods would be more limited [12,45]. Spectral metrics derived from Landsat time series provide a quantitative and spatially explicit opportunity to generate refined attribution detail related to forest harvest practices.…”
Section: Resultsmentioning
confidence: 99%
“…When remote sensing satellite orbits are designed, the satellite coverage may be considered in several ways including the number of observations in a given period and the revisit interval [7][8][9]. Previously, researchers have examined the number of observations in different periods for Landsat [10][11][12][13] and Sentinel-2 [14]. However, the revisit interval, i.e., the time period between consecutive observations of a surface location, has not been studied but is of considerable interest for terrestrial applications.…”
Section: Introductionmentioning
confidence: 99%
“…Most of these gaps are caused by missing imagery in the underlying Landsat archive [25], and therefore would not be avoided by applying an alternative water classification method on Landsat satellite imagery. Other gaps represent areas that are classified as non-valid by [16], e.g., cloud or shadow.…”
Section: Value Of a Mixed-methods Approachmentioning
confidence: 99%
“…Individual reservoirs had between 47% and 87% missing data across the 380 months; or, 74-98% pre-2000 and 18-77% from 2000 onwards. Gaps were concentrated in the period 1984-1999, indicative of gaps in the underlying USGS Landsat image archive [58] specifically over West and north Africa [25]. Data availability increased with latitude, likely being a result of decreasing cloud cover.…”
Section: Applications Of Reservoir Extent Data In Agricultural Landscmentioning
confidence: 99%
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