[33] proposed an improved CASA model to achieve a comparable result of NPP with the results from the early CASA model and ground measured NPP. [PERSON] et al. [26] analyzed quantitatively the NPP of different vegetation types on a monthly scale by inputting different climate datasets into the ecological process model, and then further explored the influence of different climate variables on NPP. Most of the abovementioned studies focused on the quantitative analysis and on the changes of the previous vegetation cover at inter-annual and monthly scales, lacking the analysis on a more accurate timescales, which was not conducive to obtain the information of phenology change. In addition, several recent studies have highlighted that there are many uncertainties and systematic errors when implementing all these models for estimating forest NPP in some specific ecological regions [34; 35], only considering the effect of water stress in soil or air on vegetation. [PERSON] et al. [36] also found that the GLO-PEM performed better by comparing the four LUE models to estimate terrestrial gross primary production. The GLO-PEM developed by [PERSON] and [PERSON] [31] is driven by the variables derived almost entirely from satellite products (please see Section 3.2.1 for specific explanations). To sum up, the past studies most concentrate on the past analysis of NPP and comparison of different models to estimate NPP [35], not considering the phenology regularity of different crops and future sustainability analysis. As a typical region in the Northeast Asia, the forest in Northeast China is not only a significant ecological barrier for urban agglomerations, but it is also the part of northeast forest belt of the national ecological pattern named \"two screens and three belts\" [37], as they accounted for over 30% of the total forest area in China. Although the Chinese government has implemented a series of ecological construction projects, such as \"Returning Farmland to Forest\" or \"Grassland and Three North Revetment Forests\", several ecological and environmental issues still exist [38], such as the declining forest productivity and deteriorating water quality and so on. In order to better solve the above problems, this study takes Northeast China as an example to explore the ecological environment changes based on the past limitations. Our objectives were to do the following: (1) improve the inversion estimation of forest NPP on the timescale of eight days, by using the improved GLO-PEM and MODIS remote-sensing data; (2) further explore the phenology regularity and its sustainability trend in the future, combined with the evolution characteristics of its spatio-temporal pattern; and (3) reveal the ecological environment quality in the newest year, which is from 2016 to 2019, and its future challenge in Northeast China. Here ecological environment quality reflects the suitability of ecological environment for human survival and sustainable social and economic development at the ecosystem level. These will provide a reference for decision-making about the rational exploitation and utilization of regional forest resources, as well as the slowing down of the global warming trend and cleaner production energy for the surrounding area.