To solve grid-scale problems and evaluation indicator selection in landscape ecological risk index (LERI) evaluation, this paper takes the Bailong River Basin in Gansu Province (BLRB) as an example. The LERI evaluation formulae and optimal grid scales were determined by screening landscape indices and area changes in the LERI at different grid scales. The evaluation indices were finally obtained according to the landscape characteristics and the correlation analysis of the landscape index value. Through the statistical analysis of the area of the LERI at the grid scale of 1–6 km, the optimal grid scale was determined to be 5 km. There was little change in land use patterns, with the most significant increases in artificial surfaces at 3.29% and 3.58%, respectively. Cultivated land was the only land use type to decrease by 184.3 km². The LERI drops with the reduced cultivated land area; the landscape ecological medium risk area and cultivated land keep the same spatial distribution. Due to the limitation of the topography, cultivated land is generally distributed below 2500 m altitude, so 2500 m becomes the turning point in the spatial distribution of the LERI. The medium risk below 2500 m dominates the LERI type. Reduced cultivated land was the leading cause of reduced ecological risk according to an overlay analysis. The study of LERI evaluations provides a theoretical basis for sustainable and ecological environmental protection in the BLRB.

To address land space issues in the West Qinling Mountains—including habitat degradation, ecosystem damage, spatial pattern imbalance and unsustainable resource use—this study employed the InVEST habitat quality model and spatial autocorrelation analysis. Based on land use remote sensing data from 1990 to 2020, we simulated and evaluated habitat quality and degradation over this 30-year period to propose scientific recommendations and optimization strategies. The results showed that: (1) The area of grassland and farmland in the West Qinling Mountains decreased significantly, the area of construction land, bare land and forest land increased mainly; (2) The habitat quality of the West Qinling Mountains was generally high, and the average of the habitat quality showed an overall decreasing trend in the period of 1990–2020. The proportion of worst habitat increased from 4.11% to 5.21%. The habitat quality is in the process of polarization, the spatial distribution of habitat quality in West Qinling shows a pattern of “high in the west, low in the north and southeast”; (3) The hot and cold spots of habitat quality in West Qinling are spatially manifested as “hotter in the west and the south; colder in the center and the east”; (4) The spatial clustering of habitat quality in the West Qinling Mountains is obvious, with the area of the high–high area and the low–low area increasing with time, the high–low area decreasing, and the low–high area slightly increasing. (5) The degree of habitat degradation in the West Qinling Mountains is generally low, the average value of degradation from 1990 to 2020 showed an upward trend, habitat degradation is in the process of converging to medium risk. The area of medium habitat degradation expanded by nearly 1.5 times between 1990 and 2020. The spatial distribution of habitat degradation in the West Qinling Mountains generally shows a pattern of low in the west and high in the north and high in the southeast. In future planning and management, the west Qinling Mountains should formulate and carry out scientific ecological restoration plans and projects in terms of improving the quality of habitats, curbing habitat degradation, optimizing the direction of regional land use and reasonably protecting land resources, in an effort to balance urban development and ecological protection, curbing ecological degradation, guaranteeing the sustainable development of the habitats in a benign direction.

Lanzhou is the only provincial capital city in Northwest China where the main stream of the Yellow River and its tributaries flow through the city. Due to its geographical location and the influence of various factors, it is difficult to evaluate and simulate the climatic, hydrological, and ecological processes of the main stream of the Yellow River and its tributaries in the region. In this study, the Wanchuan River basin, currently undergoing ecological restoration, was selected as the study area. Seasonal backscatter differences generated using Sentinel-1/2 (S1/S2) data and the CD algorithm were used to reduce the effects of surface roughness; vegetation indices, soils, and field measurements were used to jointly characterize the vegetation contribution and soil contribution. Then, SM maps with a grid spacing of 10 m × 10 m were generated in the Wanchuan River basin, covering an area of 1767.78 km². To validate the results, optimal factors were selected, and a training set and validation set were constructed. The results indicated a high level of the coefficient of determination (R²) of 0.78 and the root mean square error (RMSE) of 0.08 for the comparison of measured and inverted water contents, indicating that the algorithm retrieved the SM values of the study area well. Furthermore, Box line plots with ERA5-Land and GLDAS confirmed that the algorithm is in good agreement with current SM products and feasibility for soil water content inversion work in the Wanchuan River basin.