###### Abstract  
Due to global warming, changes in plant phenology such as an early leaf spreading period in spring, a late abscission period in autumn, and growing season extension are commonly seen. Here, near-earth remote sensing images were used to monitor the canopy phenology of _Populus fomentosa_ B301 in planted forests under full drip irrigation, full furrow irrigation, and no irrigation (rain fed). Experiments were conducted to collect phenological data across a growing season. Continuous canopy images were used to calculate different vegetation indices; the key phenological period was determined via the double logistic model and the curvature method. The effects of irrigation methods and precipitation in the rainy season on tree growth changes and key phenological periods were analyzed. The results showed that: (1) The green chromatic coordinate (GCC) conformed to the vegetation index of the tree species canopy phenological study. (2) During the phenological period throughout the year, the GCC reaching peak time (MOE) of the canopy phenology of _Populus fomentosa_ B301 was the same in the three methods, while the time of shedding at the end of the growing season without irrigation (preset point 1) was 8 days longer than with full drip irrigation (preset point 3), and 7 days faster than with full furrow irrigation (preset point 5). (3) In the preliminary rainy season, different irrigation volumes induced different growth changes and phenological periods of the trees, resulting in different data of vegetation indicators under different growth conditions. (4) During the rainy season, the precipitation had different effects on cultivating _P. fomentosa_ B301 using the three methods, that is, high precipitation could increase the growth rate of the fully irrigated area, otherwise the growth rate of this tree species was increased in full drip irrigation areas. Precipitation was lower and irregular, and the growth rate of this species was faster than the other two irrigation methods in the non-irrigated area, which was more adaptable to external environmental changes. The internal growth mechanism of the phenological changes in different areas of the planted forests was influenced by the different cultivation methods. Moreover, the collected phenological data provide a basis for the study of plant phenology with large data sets and deepens our understanding of the phenology of planted forests in response to climate change. [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] Remote Sensing Images Used to Determine the Unprocessed Characteristics of the Canopy of _Populus fomentosa_ B301 under Three Methods of Irrigation [PERSON] 1,2,3,5,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,12,13,14,15,16,17,18,19,12,13,14,15,16,17,18,19,12,13,14,15,16,17,19,18,1  
period, and the period from 2015 to 2019 was the warmest five years since complete meteorological observation records have been available. As our understanding of such warming has deepened, phenology has been found to be closely associated with the study of global climate change [1]. Phenology is the traditional discipline of studying the seasonal activities of flora and fauna, considering environmental factors as driving forces. Plant phenology, a natural phenomenon in which plants are annually affected by biological and environmental factors [2], is the growth and development rhythm formed by a plant's long-term adaptation to seasonal changes. Affected by global warming, plant phenology has become a significant and sensitive indicator of global climate change, particularly changes in start of season (SOS), for which the period of decline has become a study hotspot [3]. Nevertheless, the characteristic changes in plant phenology are subject to multiple environmental factors, which are often mutually interdependent. Therefore, it is ideal to implement controlled experiments to test the theoretical phenological hypotheses. By controlling the gradient changes in one or more influencing factors (temperature, moisture, light, etc.