The terrestrial ecosystem is the cradle of energy and material basis for human survival and development. However, there are large research deficits in accurately and finely depicting the quality of the terrestrial ecosystem (QTE) and assessing its changing triggers\' contribution. Here, we summarized three major principles for selecting image sources in remote sensing data fusion. A continuous 30-m net vegetation productivity (NPP) dataset during 2000-2019 for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was derived by using the Carnegie-Ames-Stanford approach model and pre-fused normalized difference vegetation index. The factors\' contributions to the QTE changes were quantitatively assessed. The role of the QTE in affecting the socio-economic and its behind mechanisms was quantitatively investigated. The results showed that: (1) High-quality images sources are the preference for spatio-temporal fusion of remote sensing data. Images with close month, the same season and year, and sensors should be then selected. Images of different sensors with similar spectral bandwidth, the ones from adjacent years and seasons, can be alternately considered. (2) Fine-resolution NPP has higher accuracy than coarse-resolution NPP and has marked advantages in finely characterizing the QTE. In the past 20 years, the QTE in the GBA has shown a fluctuating increasing trend (0.20 Tg C/yr). (3) Human activities contributed 54.19% of the QTE changes in the GBA, and dominates the QTE changes in the central rapidly urbanizing areas. Residual factors accounted for an overall contribution ratio of 35.71%. Climate change dominants the peripheral forest variations in the GBA. (4) In the GBA, the improvement of QTE has a significant positive socio-economic impact, it contributes to the GDP increment firstly then the GDP aggregate indirectly. Our results highlight that it is of great urgent to estimate long-term continuous NPP with high spatio-temporal resolution globally. Controlling strategies should be implemented to reduce factitious impacts on QTE. High level of ecological and environmental protection promotes the sustainable development.

Against the background of \"carbon neutrality\" and sustainable development goals, it is of great significance to assess the carbon storage changes and sustainability of terrestrial ecosystems in order to maintain the coordinated sustainable development of regional ecological economies and the balance of terrestrial ecosystems. In this study, the terrestrial ecosystem carbon storage in Guizhou from 2010 to 2020 was assessed with the InVEST model. Using the PLUS model, the distribution of terrestrial ecosystem carbon storage by 2030 and 2050 was predicted. The current sustainable development level of the terrestrial ecosystem of Guizhou was evaluated after establishing an index system based on SDGs. The results showed the following: (1) From 2010 to 2020, the terrestrial ecosystem carbon storage decreased by 1106.68 × 104 Mg. The area and carbon storage of the forest and farmland ecosystems decreased while the area and carbon storage of the grassland and settlement ecosystems increased. (2) Compared with 2020, the terrestrial ecosystem carbon storage will be reduced by 4091.43 × 104 Mg by 2030. Compared with 2030, the terrestrial ecosystem carbon storage will continue to decrease by 3833.25 × 104 Mg by 2050. (3) In 2020, the average score of the sustainable development of the terrestrial ecosystem was 0.4300. Zunyi City had the highest sustainable development score of 0.6255, and Anshun had the lowest sustainable development score of 0.3236. Overall, the sustainable development of the terrestrial ecosystem of Guizhou was found to be high in the north, low in the south, high in the east, and low in the west. The sustainable regional development of the terrestrial ecosystem of Guizhou was found to be unbalanced, and the carbon storage of the terrestrial ecosystem will keep decreasing in the future. In order to improve the sustainable development capacity of the terrestrial ecosystem, the government needs to take certain measures, such as returning farmland to forests and grasslands, curbing soil erosion, and actively supervising.