Based on the support of RS and GIS technology, this paper analyzes the spatial and temporal variation characteristics and driving forces of land use in the Yanhe River Basin through the processing and interpretation of remote sensing images in different periods from 1980 to 2015 and the methods of the land use transfer matrix and dynamic attitude. The results show that cropland, grassland, and forest land are the three types of land use with the most obvious changes, while urban land and water body have relatively small changes in the Yanhe River Basin. The transfer between cropland, forest land, and grassland and urban land is very obvious, among which the conversion rate of cropland is the highest. During the 15 years from 2000 to 2015, the land use types of the Yanhe River Basin changed by 13.17%, with an average annual growth rate of 0.88%. The implementation of ecological restoration and governance policy is the direct driving force of land use change in the Yanhe River Basin. The results obtained in this study can provide reference basis for land use planning and management and land use structure optimization in the Yanhe River Basin in the future.

Runoff erosion capacity has significant effects on the spatial distribution of soil erosion and soil losses. But few studies have been conducted to evaluate these effects in the Loess Plateau. In this study, an adjusted SWAT model was used to simulate the hydrological process of the Xihe River basin from 1993 to 2012. The spatial variabilities between runoff erosion capacity and underlying surface factors were analyzed by combining spatial gradient analysis and GWR (Geographically Weighted Regression) analysis. The results show that the spatial distribution of runoff erosion capacity in the studying area has the following characteristics: strong in the north, weak in the south, strong in the west, and weak in the east. Topographic factors are the dominant factors of runoff erosion in the upper reaches of the basin. Runoff erosion capacity becomes stronger with the increase of altitude and gradient. In the middle reaches area, the land with low vegetation coverage, as well as arable land, show strong runoff erosion ability. In the downstream areas, the runoff erosion capacity is weak because of better underlying surface conditions. Compared with topographic and vegetation factors, soil factors have less impact on runoff erosion. The red clay and mountain soil in this region have stronger runoff erosion capacities compared with other types of soils, with average runoff modulus of 1.79 × 10⁻³ m³/s·km² and 1.68 × 10⁻³ m³/s·km², respectively, and runoff erosion power of 0.48 × 10⁻⁴ m⁴/s·km² and 0.34 × 10⁻⁴ m⁴/s·km², respectively. The runoff erosion capacity of the alluvial soil is weak, with an average runoff modulus of 0.96 × 10⁻³ m³/s·km² and average erosion power of 0.198 × 10⁻⁴ m⁴/s·km². This study illustrates the spatial distribution characteristics and influencing factors of hydraulic erosion in the Xihe River Basin from the perspective of energy. It contributes to the purposeful utilization of water and soil resources in the Xihe River Basin and provides a theoretical support for controlling the soil erosion in the Hilly-gully region of the Loess Plateau.

The Loess Plateau is one of the most severely affected regions by soil erosion in the world, with a fragile ecological environment. Vegetation plays a key role in the region’s ecological restoration and protection. This study employs the Geographical Detector (Geodetector) model to quantitatively assess the impact of natural and human factors, such as temperature, precipitation, soil type, and land use, on vegetation growth. It aims to reveal the characteristics and driving mechanisms of vegetation cover changes on the Loess Plateau over the past 26 years. The results indicate that from 1995 to 2020, the vegetation coverage on the Loess Plateau shows an increasing trend, with a fitted slope of 0.01021 and an R² of 0.96466. The Geodetector indicates that the factors with the greatest impact on vegetation cover in the Loess Plateau are temperature, precipitation, soil type, and land use. The highest average vegetation coverage is achieved when the temperature is between −4.8 and 2 °C or 12 and 16 °C, precipitation is between 630.64 and 935.51 mm, the soil type is leaching soil, and the land use type is forest. And the interaction between all factors has a greater effect on the vegetation cover than any single factor alone. This study reveals the factors influencing vegetation growth on the Loess Plateau, as well as their types and ranges, providing a scientific basis and guidance for improving vegetation coverage in this region.

Taking Henan province as an example, the index system of rural hollowing was constructed from three aspects of economy, population and land. Using the entropy weight method, hollowing index method, spatial autocorrelation analysis and Geo detector, spatial-temporal evolution characteristics and influencing factors of county rural hollowing from 2000 to 2013 in Henan province were analyzed. Results showed that the gap of rural hollowing between counties in Henan province expanded first and then decrease, and the whole province was at the middle level of rural hollowing, so the development of rural hollowing in Henan province was stable and positive. Spatial variation characteristics of different degrees rural hollowing during 2000-2013 were obvious, and the overall spatial pattern was higher in the northwest-southeast direction and lower in the northeast-southwest direction. There was a strong spatial positive correlation in rural hollowing, and spatial agglomeration was slightly weakened; the number of counties in H-H and L-L agglomeration areas was large and its agglomeration characteristics were obvious; the H-L agglomeration areas started from zero with a small number and scattered distribution. Influence of different factors on rural hollowing was quite different, and the per capita homestead area, the proportion of secondary and tertiary industries, the investment in fixed assets and the per capita net income of farmers were the dominant factors.

Soil erosion is a notable contributor to carbon emissions. Distributed erosion model can be used to study erosion distribution in different land cover, identify the main influential factors, and hence guide soil and water conservation. In this study, Regional Soil Erosion model (RSEM) was used to simulate the soil erosion processes of Jihe Basin in 2015, and the Multiscale Geographically Weighted Regression (MGWR) implementation was applied to compare the erosion regression of Geographically Weighted Regression (GWR) and MGWR as well as study the impact of influential factors on sediment modulus in hillslopes. The results are as follows: (1) MGWR results indicated slope was the dominant factors affecting soil erosion at the catchment scales, where the average coefficients of slope, forest coverage, and grass coverage descended in the value of 0.90, −0.11, and −0.19, and the influences of factors operate over scales; (2) MGWR with the adoptive bandwidths performed well in the goodness of fit, t-test of variables, scales that variables operate, and interactive interpretation of soil erosion; (3) the coupling effects and scales of vegetation and topography factors are an important approach to study soil erosion at a larger scale.