Vegetation phenology is the study of recurring plant life cycle stages, seasonality which is
linked to many ecosystem processes and is an important proxy of climate and environmental …

For mapping, quantifying and monitoring regional and global forest health, satellite remote
sensing provides fundamental data for the observation of spatial and temporal forest …

This study aims to develop a deep learning based classification framework for remotely
sensed time series. The experiment was carried out in Yolo County, California, which has a …

Dense time series of Landsat 8 and Sentinel-2 imagery are creating exciting new
opportunities to monitor, map, and characterize temporal dynamics in land surface …

Accurate crop mapping provides important and timely information for decision support on the
estimation of crop production at large scale. Most existing crop-specific cover products …

Many time-series smoothing methods can be used for reducing noise and extracting plant
phenological parameters from remotely-sensed data, but there is still no conclusive …

Vegetation phenology is the study of the timing of seasonal events that are considered to be
the result of adaptive responses to climate variations on short and long time scales. In the …

Plant phenology regulates ecosystem services at local and global scales and is a sensitive
indicator of global change. Estimates of phenophase transition dates, such as the start of …

An innovative phenology-based classification method was developed to map corn and
soybean in multiple years using training data limited to a single year. Unlike traditional …

For the two of the most important agricultural commodities, soybean and corn, remote
sensing plays a substantial role in delivering timely information on the crop area for …