Results 191 to 200 of about 19,071 (245)

CholecInstanceSeg: A Tool Instance Segmentation Dataset for Laparoscopic Surgery. [PDF]

open access: yesSci Data
Alabi O   +6 more
europepmc   +1 more source

Validation of SMAP surface soil moisture products with core validation sites

open access: yesRemote Sensing of Environment, 2017
The NASA Soil Moisture Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the soil moisture retrieval algorithm performance.
Andreas Colliander   +2 more
exaly   +2 more sources

The Soil Moisture Active Passive (SMAP) Mission

open access: yesProceedings of the IEEE, 2010
The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey. SMAP will make global measurements of the soil moisture present at the
Dara Entekhabi   +2 more
exaly   +2 more sources

Joint Sentinel‐1 and SMAP data assimilation to improve soil moisture estimates [PDF]

open access: yesGeophysical Research Letters, 2017
SMAP (Soil Moisture Active and Passive) radiometer observations at similar to 40 km resolution are routinely assimilated into the NASA Catchment Land Surface Model to generate the 9 km SMAP Level-4 Soil Moisture product.
Hans Lievens, Qing Liu, G J M De Lannoy
exaly   +6 more sources

The SMAP and Copernicus Sentinel 1A/B microwave active-passive high resolution surface soil moisture product

Remote Sensing of Environment, 2019
Soil Moisture Active Passive (SMAP) mission of NASA was launched in January 2015. Currently, SMAP has an L-band radiometer and a defunct L-band radar with a rotating 6-m mesh reflector antenna.
Narendra N Das   +2 more
exaly   +2 more sources

A weakly coupled land surface analysis with SMAP radiance assimilation improves GEOS medium‐range forecasts of near‐surface air temperature and humidity

Quarterly Journal of the Royal Meteorological Society, 2023
The NASA Goddard Earth Observing System (GEOS) employs a hybrid four‐dimensional ensemble‐variational (Hybrid‐4DEnVar) atmospheric data assimilation system to provide global, near‐real time weather analysis and forecast products.
R. Reichle   +4 more
semanticscholar   +1 more source

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