Land use is closely related to the sustainability of ecological development. This paper employed a patch-generating land use simulation (PLUS) model for the multi-scenario simulation of urban agglomerations. In addition, mathematical analysis methods such as Theil-Sen Median trend analysis, R/S analysis, Getis-Ord Gi* index and unary linear regression were used to study the temporal and spatial evolution characteristics of net primary productivity (NPP) for the impact of land use changes on NPP in urban agglomerations from 2000 to 2020 and to forecast the future trend of NPP. The results indicate that urban expansion is obvious in the baseline scenario and in the ecological protection scenario. In the scenario of cropland protection, the urban expansion is consistent with the land use plan of the government for 2035. The NPP in Beijing decreased gradually from northwest to southeast. The hot spot areas are concentrated in the densely forested areas in the mountainous areas of northwest. The cold spot areas are mainly concentrated in the periphery of urban areas and water areas. The NPP will continue to increase in forest and other areas under protection and remain stable in impervious surfaces. The NPP of Beijing showed a strong improvement trend and this trend will continue with the right ecological management and urban planning of the government. The study of land use in urban agglomeration and the development trend of vegetation NPP in the future can help policymakers rationally manage future land use dynamics and maintain the sustainable development of urban regional ecosystems.

With the implementation of human activities, such as logging, reclamation, and construction, the increasing fragmentation of ecological space and the increasing blockage of biological migration corridors cause many threats to biodiversity conservation. In this study, we used the Northwest Beijing Ecological Containment Area as the research area. Based on an integrated circuit theoretical model, we identified functional connectivity networks and analyzed the spatial and temporal changes of ecological blockage patterns in the region from 1998–2018 in terms of the landscape connectivity, ecological breakpoints, pinch points, and barriers, respectively. The results show that the average remote sensing ecological index had a trend of decreasing and then increasing, and a total of 33, 34, and 63 habitat core areas and 70, 74, and 152 ecological corridors were identified in 1998, 2010, and 2018, respectively. The regions with high ecological blockage were mainly in the central part of Yanqing District, the southwest corner of the study area, and the eastern urban area. Although the number of potential ecological corridors gradually increases with the probability of migration in the study area, the blockage status and vulnerability of the ecological corridors continue to increase due to the conflict between land uses. The ecological status of the study area reflects the comprehensive effectiveness of the capital’s high-quality development under the strategic deployment of ecological civilization. In the context of habitat fragmentation, the effective protection and restoration of the ecological conditions in the ecological function areas is of great importance in guaranteeing the ecological quality and sustainable development of the country.

Vegetation changes and factors have a profound influence on the local ecology, the economy, and the long-term durability of human construction. This study focuses on the impacts of climate change and human activity on vegetation changes on the Qinghai-Tibet Plateau and aims to develop a dataset of human activity levels on the plateau. Sen and Mann-Kendall trend analysis was used to evaluate the spatial distribution of vegetation NDVI and its trends, as well as the lagged response of plant growth to climatic circumstances. Using a geodetector model, the effects of meteorological and anthropogenic intensity data were examined. The study’s findings show that, although anthropogenic influences and ecosystem vulnerability caused a decline in the region’s vegetation, a stable climate and a healthy ecosystem supported the growth of vegetation. From 2000 to 2017, the area where vegetation grass improved significantly accounted for the highest proportion, reaching 34.22%. Different anthropogenic intensities are distributed spatially, and this interplay of anthropogenic intensities and climatic factors affects the distribution of vegetation greenness more than each element acting alone. The study of how human activity and climate change affect vegetation greenness can offer practical recommendations for maintaining the Qinghai-Tibet Plateau’s natural ecology. It is crucial to responsibly safeguard the Qinghai-Tibet Plateau’s environment in response to the nation’s ecological civilization.

A significant portion of Zhanjiang City’s ecological land areas have been reduced as a result of the city’s growing urbanization, which has caused the city’s ecological environment quality to decline. In order to monitor the quality of the ecological environment, the remote sensing ecological index (RSEI) is frequently utilized. In this study, the Landsat series satellite images from 2000, 2005, 2009, 2015, and 2020 were used. The Normalized Differential Vegetation Index (NDVI), Wetness (WET), Normalized Differential Build-up and bare Soil Index (NDBSI), and Land Surface Temperature (LST) were the four indicators utilized in the RSEI to quantitatively evaluate the changes in ecological environment quality in Zhanjiang City. The results are as follows. (1) The mean RSEI values for the years 2000, 2005, 2009, 2015, and 2020 are, respectively, 0.579, 0.597, 0.597, 0.607, and 0.601. In addition, the overall ecological environment of Zhanjiang is very good. In terms of spatial differences, the ecological environment quality in the central and southeastern parts of Zhanjiang is significantly higher than that in other areas, while the ecological environment quality in its coastal town areas is much worse. The lower RSEI index of developed land in coastal areas proves that the RSEI index can reflect the deterioration of the urban environment in coastal areas from 2000 to 2020. Therefore, the RSEI can be used to evaluate the ecological environment quality of Zhanjiang City. (2) The ecological environment changes in the study area are “substantially better,” “better,” “no change,” “worse,” and “much worse,” respectively, according to the difference in RSEI processed between 2000 and 2020. These changes were 38.38, 6,047, 13.93, 6.65, and 34.58%. The percentage of ecological environmental quality in Zhanjiang City that has become better is higher than that has become worse. This indicates that the quality of ecological environment in Zhanjiang City has improved between 2000 and 2020. (3) The regression produced the following equation for the association, which was significant at the 0.053 level: 100*Rsei = 154.69–1.18*IS(R = 0.66). The remote sensing ecological index for Zhanjiang in 2035 is 0.488 when the city’s planned population and area are added together.