The Loess Plateau is a typical ecologically sensitive area that can easily be perturbed by the effects of human activities and global climate change. Therefore, it is necessary to develop tools to monitor the environmental quality in the LP quickly and accurately. To reveal the spatio-temporal changes in environmental quality in the LP from 2000 to 2020, we used the Moderate-Resolution Imaging Spectroradiometer (MODIS) products on the Google Earth Engine platform and constructed the remote sensing ecological index (RSEI) through principal component analysis (PCA). Then, Sen–Mann–Kendall methods were applied to determine the changing trend of the environmental quality of the LP. Finally, natural and anthropogenic factors affecting the environmental quality were probed using a geographical detector model. The results showed that: (1) the average RSEI values in 2000, 2010 and 2020 were 0.396, 0.468 and 0.511, respectively, displaying an upward trend from 2000 to 2020, with a growth rate of 0.005 year−1. The overall environment quality was moderate (0.4–0.6). (2) In terms of spatial distribution, the environmental quality was excellent in the southeast and poor in the northwest of the LP. The areas with improved environmental quality (84.51%) were located in all the counties, whereas the areas with degraded environmental quality (8.11%) occurred in the north and southeast of the study area. (3) Greenness, heat, wetness, dryness and land use types were prominent factors affecting RSEI throughout the study period; additionally, the total industrial gross domestic product showed a growing influence. The contribution of multi-factor interaction was stronger than that of single factors. The results will provide a reference and a new research perspective for local environmental protection and regional planning.

As one of the three major black soil regions in the world, northeastern China has an important strategic position there. Since the 20th century, the local environment has undergone great changes under the influence of the natural economy, and it is particularly important to quantitatively assess the degree of change. However, there have been few long-term quantitative studies of environmental spatial-temporal variances in the three northeastern provinces. Therefore, in this study, four typical remote sensing indices of the normalized difference vegetation index (NDVI), land surface temperature (LST), normalized differential building–soil index (NDBSI) and wetness (WET) were employed to construct the remote sensing ecological index (RSEI) using a principal component analysis (PCA) method based on the Google Earth Engine (GEE) platform in northeastern China. The spatiotemporal variations in the eco-environmental quality were detected using linear slope and M–K test, and the direct and interactive effects of different influencing factors on the RSEI changes during 2000–2020 were explored based on geographic detection. The results show that the interannual variations in the RSEI show a fluctuating upward trend, with an increase percentage of 12.45% in the last two decades, indicating that the ecological quality of northeast China has gradually improved. Furthermore, that the western and eastern Heilongjiang provinces and western Jilin provinces contributed substantially to the improvement of environmental quality, while the environmental quality of Jilin provinces and central Liaoning provinces decreased to varying degrees. Compared with 2000, the area with a fair environmental quality grade had the greatest change, and had decreased by 60.69%. This was followed by the area with an excellent quality grade, which increased by 117%. Land-use type had the greatest impact on environmental changes in northeastern China, but the impact degree gradually decreased, while the impact of socioeconomic factors such as the gross production of agriculture, forestry, animal husbandry and fishery and population density on environmental quality gradually increased. The major reason for the decline of environmental quality in central Jilin and central Liaoning is that urbanization development had occupied a large amount of cropland. This shows that taking into account the virtuous cycle of an ecological environment while promoting urban and rural development may be an important task for northeastern China in the future.

Spatio-temporal change characteristic in leaf area index (LAI), gross primary productivity (GPP), total leaf area and total carbon sequestration of terrestrial vegetation at different geographic regions, provinces and land cover change types over China during 2000–2018 were clarified, respectively. The net increase in total leaf area and carbon sequestration over China from 2000 to 2018 is 1.7491 × 106 km2 and 1957.36 TgC, and Southwestern part contributes the most with a contribution of 25.3% for leaf area and 20.1% for carbon sequestration, respectively. The overall contribution of northern provinces to enhanced carbon sequestration capacity is greater than that of southern provinces, with a maximum for Inner Mongolia, even though southern provinces have a much higher leaf area increase. The annual increase rates of LAI and GPP in returning cropland to forest–grassland and artificial restoration of forest–grassland are higher than that of self-rehabilitation of rapid growth stage for planted young vegetation. However, due to self-rehabilitation of forest–grassland has the largest area percentage of 59%, it contributes the most to the increases of leaf area and carbon sequestration among different land cover change types, except for northeastern China, where improved farmland productivity is a dominant factor. It should be noted that the leaf area and carbon sequestration exhibit upward trends in urbanized areas over China. whereas slight increasing and even negative trends are also observed in southwestern, southern, and eastern China (e.g., Shanghai), where artificial surface construction occupied more cropland during urbanization processing. Compared with climatic factors, LAI is the dominant factor influencing GPP increases over China since 2000, and gradually weakened coupling relationship between LAI and GPP is observed from north to south. For climatic factors, GPP is dominantly affected by precipitation in northern parts and by solar radiation in southern parts.