Agrophenology Indicators from Remote Sensing: State of the Art

Monitoring phenology at a regional, national or at a global scale is recognized by the scientific community as very important for many practical applications and notably for climate change studies. Phenological observations are classically realised for specific plant species in botanical garden or in small study areas or fields all over the world and sometimes date back to the 19 century. Although these observations are very interesting for studying the trends in phenology over time and their drivers, they are punctual and provide therefore only little information on its spatial variability. In this context, remote sensing information and especially low resolution sensors through their broad spatial resolution can provide additional information on phenology and allow creating dynamic maps of vegetation development. Different remote-sensed indicators for assessing vegetation phenology, for the most part based on smoothed NDVI curves, have already been proposed in various studies. These indicators are computed on moving averages, NDVI thresholds, logistic curves or maximum rate of changes. The phenological metrics directly derived from RS information are generally the start and the end of the growing season and also the moment of maximum greenness. Other RS phenological indicators are often derived from these metrics as, for example, the length of the growing season. RS phenological metrics can also be used as input variables in dynamic simulation models. These models unfortunately failed in non-optimal conditions (e.g. in case of damaging frost, hail, drought...). Remote sensing data could possibly be used to re-calibrate and re-adjust these models.