The task of monitoring of the growing season change dates is solved traditionally using ground meteorological observations. The time frames of the growing seasons are allocated when the surface air temperature transition through a particular marker value (e.g., +5 °C or +10 °C) is observed. When the ground observation network is sparse, such an approach leads to significant local distortions in the estimations of the change dates and duration of the growing seasons. In addition, the allocation of growing seasons based only on observation of air temperature comfortable for vegetation growth does not take into account physiological characteristics of various vegetation species. Application of satellite imagery makes it possible to estimate vegetation cover parameters and characterize phytomass state and growth. It is possible to recognize beginning and ending of vegetation growth and some other phenological changes, as in recent decades the use of satellite imagery time series became available, which are collected using repeated satellite imaging. The authors of the paper investigate the use of Normalized Difference Water Index (NDWI) derived from satellite imagery to allocate framing dates of the growing seasons. The paper describes and characterizes various approaches to the implementation of analysis methods used by researchers to assess annual graphs of vegetation indices (particularly NDWI) with the aim of identifying of the growing season characteristics. The typification of these methods proposed by the authors is given. Concluded the possibility of application of the proposed typification as the basis for vegetation indices analysis methodology development in order to assess the characteristics of the growing seasons.