###### Abstract
The productivity of vegetation can be segregated into gross primary productivity (GPP) and net primary productivity (NPP), being conceptual frameworks developed in the course of scholars investigating plant productivity. GPP refers to the rate at which green plants in the ecosystem synthesize organic substances by assimilating carbon dioxide through photosynthesis and absorbing solar energy [23]. NPP represents the accumulation of organic matter per unit area and unit time, characterized as the portion of organic carbon fixed through photosynthesis, minus the part consumed through plant respiration [24]. Vegetation productivity reflects the process where plants absorb CO\({}_{2}\) from the atmosphere through photosynthesis, converting light energy to chemical energy, while accumulating organic dry matter. It embodies the production capability of terrestrial ecosystems under natural conditions, serving as an important ecological indicator for estimating Earth's carrying capacity and evaluating the sustainable development of ecosystems. It is also a primary metric for determining the carbon sink of ecosystems and regulating ecological processes [25]. Currently, there are numerous methods to estimate the primary productivity of forest vegetation, and the light use efficiency (LUE) model is the main method for estimating vegetation productivity based on remote sensing data. This principle was first proposed by [PERSON] while studying crop productivity. The LUE model has clear principles and simple calculation processes. The input data for the model can mostly be acquired through remote sensing and meteorological stations, and it offers high simulation accuracy, becoming a primary tool for regional and global vegetation productivity assessments [26]. The LUE model mainly encompasses methods such as the Carnegie-Ames-Stanford approach (CASA) model, the eddy covariance-light use efficiency (EC-LUE) model, the GLO-PEM model, and the photosynthesis model (VPM), among others. [PERSON] et al. utilized the CASA model to simulate the net primary productivity of vegetation in the Three River Source region of China from 1982 to 2012, and analyzed the main climatic and human driving factors [27]. [PERSON] et al. referred to the drought-stress improved-EC-LUE model to estimate the spatiotemporal distribution pattern of GPP in the Mao bamboo forest of Anji City [28]. [PERSON] et al. applied the GLO-PEM model to estimate the net primary productivity of the Iberian Peninsula for 15 years and studied its spatial and temporal variations and the quantitative relationship between NPP, precipitation, and air temperature [21]. Although many scientific studies have used light use efficiency models to study vegetation productivity, currently most LUE models directly simulate the GPP, with only the CASA and GLO-PEM models capable of directly simulating the NPP [23]. Theoretically, the fundamental principle of the LUE model is designed for GPP; the direct simulation of NPP requires the assumption that the proportion of plant autotrophic respiration to GPP is the same across all ecosystem types and geographic regions. However, research indicates that the proportion of plant autotrophic respiration to GPP is not the same under temperature gradients, and using the same ratio for calculation will inevitably lead to corresponding errors [23]. Therefore, this study uses the EC-LUE model to estimate the total primary productivity in the research area, and uses the ratio of NPP to GPP as the value of carbon use efficiency (CUE), utilizing the product of GPP and CUE to represent the net primary productivity of vegetation in the research area.