Table 1. Design of the factorial experiment.

X means that the variant was used to study the respective topic of each row. LSTM = LSTM model using the full depth of the Landsat time series and climate data; LSTM_perm = LSTM model but the temporal patterns of both the predictive and the target variables were randomly permuted while instantaneous relationships between predictive and target variables were kept; LSTM_msc = LSTM model but the Landsat time series for each band were replaced by their mean seasonal cycle, while using the actual values of air temperature (T_air), precipitation (P), global radiation (Rg), and vapor pressure deficit (VPD); LSTM_annual = LSTM model but the Landsat time series for each band were replaced by their annual mean, while using the actual values of T_air, P, Rg, and VPD, RF = Random Forest model using the actual values of the Landsat time series and climate data.

	LSTM	LSTMperm	LSTMmsc	LSTMannual	RF
Temporal feature extraction/Memory effects	X	X			X
Vegetation interannual seasonal variation	X		X
Vegetation interannual variability	X			X
Comparision to non-dynamic method	X				X