The latitudinal gradient of the start of the growing season (SOS) and the end of the growing season (EOS) were quantified in Alaska (61°N to 71°N) using satellite-based and ground-based datasets. The Alaskan evergreen needleleaf forests are sparse and the understory vegetation has a substantial impact on the satellite signal. We evaluated SOS and EOS of understory and tundra vegetation using time-lapse camera images. From the compar- ison of three SOS algorithms for determining SOS from two satellite datasets (SPOT-VEGETATION and Terra- MODIS), we found that the satellite-based SOS timing was consistent with the leaf emergence of the forest under- story and tundra vegetation. The ensemble average of SOS over all satellite algorithms can be used as a measure of spring leaf emergence for understory and tundra vegetation. In contrast, the relationship between the ground- based and satellite-based EOSs was not as strong as that of SOS both for boreal forest and tundra sites because of the large biases between those two EOSs (19 to 26 days). The satellite-based EOS was more relevant to snow- fall events than the senescence of understory or tundra. The plant canopy radiative transfer simulation suggested that 84–86% of the NDVI seasonal amplitude could be a reasonable threshold for the EOS determination. The lat- itudinal gradients of SOS and EOS evaluated by the satellite and ground data were consistent and the satellite- derived SOS and EOS were 3.5 to 5.7 days degree−1 and −2.3 to −2.7 days degree−1, which corresponded to the spring (May) temperature sensitivity of − 2.5 to − 3.9 days °C− 1 in SOS and the autumn (August and Septem- ber) temperature sensitivity of 3.0 to 4.6 days °C− 1 in EOS. This demonstrates the possible impact of phenology in spruce forest understory and tundra ecosystems in response to climate change in the warming Artic and sub- Arctic regions.