## 1 Introduction  
As a major component of terrestrial ecosystems, vegetation plays an important role in material cycling and energy flows, and provides irreplaceable service functions that maintain the wellbeing of our planet and all the creatures that inhabit it. These function services include food provision, climate regulation, carbon sequestration, timber production, biodiversity preservation, and soil protection [1; 2; 3; 4; 5; 6; 7; 8]. Vegetation growth affects the ecological balance, the terrestrial carbon cycle, water circulation, and other biochemical processes [2; 9]. Thus, information about the spatial-temporal dynamics of regional and global vegetation is a fundamental need in order to facilitate the better management of our planet ecosystem, provide effective support for environmental sustainability and ensure the safety of agricultural production; these have become emerging issues in the field of environmental studies [2; 5; 10]. With the rapid advancement of remote sensing technology, global-scale land surface parameters, derived from long time series of remote sensing observations, have provided a good description of vegetation changes [11; 12; 13]. Leaf area index (LAI), defined as one-half the total developed area of green leaves per unit horizontal surface area, can serve as a proxy for detecting vegetation greenness and serves as a measure of the amount of vegetation that is vertically distributed [14; 15; 16; 17; 18; 19]. Fractional vegetation cover (FVC), defined as the projected area of aboveground vegetation per unit ground area, can characterize the horizontal density of land surface vegetation and reflect plant community structure [20; 21; 22]. In addition, gross primary productivity (GPP) is the photosynthetic carbon assimilation by land plants per unit space and time, and can serve as an indicator of vegetation productivity [23; 24; 25]. Based on remote sensing products of these parameters at regional and global scales, scholars around the world have used different methods to study spatial-temporal changes in vegetation greenness (related to canopy structure) and vegetation productivity (related to canopy function) [26; 27; 28], such as trend analysis and spatial autocorrelation analysis. Vegetation growth, production and distribution are highly reliant on--and sensitive to--natural and anthropogenic factors, such as precipitation, temperature, water resources, farming, and urban expansion. The condition of the global vegetation is constantly changing at various spatial and temporal scales, driven by natural and anthropogenic factors [29; 30; 31]. The response of vegetation dynamics to differences in environmental factors varies significantly across regions, according to the regional climate conditions, water availability, and land cover [32; 33]. As the tenth largest river basin in the world, the natural conditions of the Amur River Basin (ARB), a transboundary basin in eastern Eurasia, vary greatly from region to region. In addition, the impact intensity of human activities on the ground vegetation has varied considerably under the influence of different national policies, lifestyles, and economic development [34; 35; 36; 37; 38]. In recent decades, significant climate changes have been observed in the ARB, where an annual mean temperature warming rate of about 0.34 \({}^{\circ}\)C/10a for 1975-2004 was reported, which is approximately 2.5 times higher than that for the 1891-2004 period [39]. Regional climatic characteristics and dramatic climate change govern the spatial-temporal changes of vegetation in the basin. In the context of changes in climatic and hydrological factors, the continued intensification of agricultural activities, driven by the large demand for food and economic development, affects the vegetation dynamics in the ARB and threatens the ecosystem [40; 41; 42]. Most previous studies have used correlation analyses and regression models to reveal the factors driving changes in vegetation dynamics in the whole basin or sub-basins of the ARB.