Real-time and short-term predictions of spring phenology in North America from VIIRS data

L Liu, X Zhang, Y Yu, W Guo - Remote Sensing of Environment, 2017 - Elsevier
Real-time prediction of vegetation phenology is critical for assisting crop monitoring, natural
resource management, and land modeling in weather prediction systems. However, due to
the lack of timely available satellite datasets and the inherent noise in time series, little
attention has been paid to real-time and short-term predictions of vegetation phenology. The
successful launch of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument
onboard operational Suomi National Polar-orbiting Partnership (Suomi NPP) satellite makes …

Real-time and short-term predictions of spring phenology in North America from VIIRS data.

LLL Liu LingLing, ZXY Zhang XiaoYang… - 2017 - cabidigitallibrary.org
Real-time prediction of vegetation phenology is critical for assisting crop monitoring, natural
resource management, and land modeling in weather prediction systems. However, due to
the lack of timely available satellite datasets and the inherent noise in time series, little
attention has been paid to real-time and short-term predictions of vegetation phenology. The
successful launch of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument
onboard operational Suomi National Polar-orbiting Partnership (Suomi NPP) satellite makes …
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