Spatio-Temporal Evolution, Future Trend and Phenology Regularity of Net Primary Productivity of Forests in Northeast China  
[PERSON]  
1 Key Laboratory of Soil and Water Conservation and Desertification Prevention, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China; [EMAIL_ADDRESS] (C.W. ); [EMAIL_ADDRESS] (K.L. )1 Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China 1  
Footnote 1: email: {1,3,4,5,6,7,8,9,10,11  
and TRIPLEX1.0 model [4], based on national forest resource inventories and Landsat time-series data, especially in North America and European [3; 4; 5; 6]. However, as an important player in the harmony between human and nature, forest ecosystem in East Asia also plays an irreplaceable role in maintaining global biodiversity, regulating climate, conserving water, and providing biological resources and other economic goods [7; 8; 9; 10]. With the acceleration of economic development and industrialization, the environmental pollution and ecological damage have become increasingly serious and even the stability of forest ecosystem has been severely damaged. Therefore, the sustainable development of forest ecosystem has gradually and globally become of concern [11; 12; 13]. As an important factor of forest ecosystem, vegetation Net Primary Productivity (NPP) is one of the indispensable core parameters for estimating terrestrial ecosystem function to explore the impact, response and countermeasures of global changes on ecosystem [14]. Moreover, the NPP, which is the main indicator of ecosystem ecological balance and ecosystem health, is closely related to major issues of concern such as carbon cycle and carbon disturbance, land use change, climate change and natural resource management. In addition, changes in regional phenology regularity, especially the data from the start of the vegetation growth season (SOS) and end of the vegetation growth season (EOS), not only influence terrestrial carbon and water cycle, but also exert significant impact to climate by regulating the land-atmosphere energy exchange [15; 16]. Therefore, studies on how accurately simulate and predict the NPP and explore the phenology regularity in the regional scale ecosystem are of great significance [17; 18]. In particular, they can provide an important basis for the dynamic carbon cycle in the atmosphere, the vegetation and soil continuum as well as the sustainable management of forest ecosystem [19; 20; 21]. In recent years, the rapid development of remote-sensing techniques has promoted its wide application in vegetation dynamic monitoring and prediction. Plenty of studies worldwide have conducted extensive studies on estimating forest biomass [22; 23; 24], the analysis on spatio-temporal distribution of NPP [25], the responses of NPP to climate changes in the past decades [26; 27]. The Light Utilization Energy (LUE) models are commonly used to estimate and evaluate vegetation NPP on a regional or global scale. On the one hand, this kind of model simplifies the physiological and ecological process of vegetation, and the calculation is relatively simple. On the other hand, this model can be used to estimate the temporal and spatial variation of vegetation NPP on a large regional or global scale with high accuracy. These advantages promote the development and research of such models. Currently, there are four LUE models of NPP estimation models, such as the Vegetation Photosynthesis Model (VPM) [28; 29], Carnegie-Ames-Stanford Approach (CASA) [30], Global Production Efficiency Model (GLO-PEM) [31] and Moderate Resolution Imaging Spectroradiometer (MODIS) GPP algorithm [32]. Among these LUE models, the CASA model has been widely used, whose principle of that is to estimate NPP by vegetation photosynthetic effective radiation and actual utilization of light energy. For example, [PERSON] et al.