## 1 Introduction  
Dynamic change in the carbon cycles of terrestrial ecosystems is a core component of climate change and regional sustainable development [1]; it plays an important role in the global carbon balance. Because of the impacts of various environmental and biological factors (such as climate change, vegetation distribution, and land-use change), the carbon cycles of terrestrial ecosystems show significant spatial heterogeneity [2]. Forest ecosystems are an important component of terrestrial ecosystems and play an important role in improving and maintaining the ecological environment, in addition to regulating the global carbon balance [3, 4]. Therefore, it is essential to quantify carbon fluxes in forest ecosystems and explore their response to environmental factors in the carbon cycles of terrestrial ecosystems. Carbon flux [5] is the basis for determining the carbon source/sinkof an ecosystem and plays an important role in the global carbon cycle and carbon balance. Ecosystem productivity is an important indicator for quantitatively describing the carbon sequestration capacity of an ecosystem, which mainly includes gross primary production (GPP) and net primary production (NPP) [6]. GPP refers to the amount of organic carbon fixed by photosynthesis per unit time and unit area of green plants [7; 8]. It reflects the carbon sequestration ability of vegetation, and is the largest carbon flux in terrestrial ecosystems [9]. NPP is the organic matter or energy remaining for vegetation growth after deducting the organic matter consumed by vegetation autotrophic respiration (RA) on the basis of GPP [10]. It can directly reflect the production capacity and ecological environment quality of surface vegetation in the natural environment, and is an important indicator for evaluating the carbon sink of ecosystems, in addition to regulating ecological processes [11; 12]. The methods to obtain carbon fluxes of forest ecosystems mainly include sample site inventory, eddy covariance technology, and model simulation. Sample site inventory can estimate carbon fluxes more accurately, but the estimation of the carbon fluxes of forest ecosystems requires long-term field measurements, which consume substantial amounts of time and labor [13]; therefore, it limits the estimation of carbon fluxes in forest ecosystems. Eddy covariance technology has the advantages of being a long-term, continuous, and non-destructive method [14], and has been widely used to estimate the carbon fluxes of forest ecosystems [15]. However, the number of flux observation sites is limited and the area of effective observation is very small. There are uncertainties in expanding it from the site to the regional scale, and it is often hindered by topography and climate conditions; therefore, eddy covariance technology has limitations in studying carbon fluxes in forest ecosystems at the regional scale. Model simulation is an important method of evaluating carbon fluxes in forest ecosystems [16; 17]. Remote sensing for earth observation technology has the characteristics of real-time, dynamic, and large-area synchronous monitoring, in addition to rich information [13]. It readily records the dynamic changes in environmental conditions, vegetation distribution patterns and activities, and land use in the form of electromagnetic information. This provides the necessary parameters of vegetation (such as NDVI and LAI) and environmental variables for the carbon flux model, and becomes a powerful method to study the distribution, seasonal change, and interannual change in carbon fluxes [18]. Therefore, the application of remote sensing data in the model estimation helps achieve cross-scale simulation of the carbon cycle process and reflect the spatial distribution and dynamic changes in the carbon budget at the regional and global scales. It increases the reliability and operability of vegetation carbon flux estimation and has become an important research topic [18; 19; 20; 21; 22].