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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #340086
Title: Toward daily monitoring of vegetation conditions at field scale through fusing data from multiple sensors

Author
item Gao, Feng

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 3/31/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Vegetation monitoring requires remote sensing data at fine spatial and temporal resolution. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for crop and rangeland monitoring. The Landsat satellite series provides medium spatial resolution (30m) imagery which is well suited to capturing surface details at field scale, but a long revisit cycle (16-day) has limited its use in describing daily surface changes. Data fusion approaches provide an alternative way to utilize observations from multiple sensors so that the fused results can provide higher value than can an individual sensor alone. In addition, more Landsat-like data are now available. The European Space Agency’s (ESA) Sentinel-2 data have similar/superior spatial resolution to Landsat and can be combined with the existing satellite data for continuous vegetation monitoring. In this presentation, several data fusion models/approaches will be discussed. Applications in crop phenology mapping and rangeland condition monitoring at 30-m spatial resolution will be presented and discussed.