Search Results (56)

Gravity erosion is one of the main physical processes of soil erosion and sediment sources in catchments, and its spatiotemporal patterns and driving mechanisms are seriously understudied, mainly due to the the great difficulties in monitoring and quantifying. This study obtained gravity erosion amounts by runoff scouring experiments on the field slope of the hilly–gully region of the Chinese Loess Plateau. The terrain point cloud before and after gravity erosion was obtained based on the TLS, SfM and the fusion of single-scan TLS and SfM, and then the gravity erosion was estimated by four terrain change detection algorithms (DoD, C2C, C2M and M3C2). Results showed that the M3C2 algorithm plus fused data had the highest quantization accuracy among all the algorithms and data sources, with a relative error of 14.71%. The fused data combined with M3C2 algorithm performed much better than other algorithms and data sources for the different gravity erosion magnitudes (mean relative error < 17.00%). The DoD algorithm plus TLS data were preferable for collapse areas, while the M3C2 algorithm plus TLS was suitable for the alcove area. This study provides a useful reference for the monitor and quantitative research of gravity erosion in complex topographic areas. Full article

Microtopography plays a crucial role in regulating soil moisture in arid and semi-arid regions, thereby significantly influencing vegetation growth and distribution. The Loess Plateau, characterized by a deeply incised and fragmented landscape, necessitates an in-depth understanding of the microtopograph–soil moisture–vegetation relationship to guide effective vegetation restoration. This study, based on field investigations and laboratory analyses in the hilly-gully region of the Loess Plateau, employed one-way ANOVA, Duncan’s multiple range test, and structural equation modeling to examine the effects of microtopography on vegetation community characteristics. The results revealed that microtopography significantly affects vegetation diversity and stability. Vegetation diversity and stability were higher on shady slopes than on sunny slopes, with diversity indices increasing by approximately 38% in certain regions. Additionally, downslope positions exhibited greater vegetation diversity than upslopes, with richness indices increasing by approximately 33% and the M. Godron index decreasing by 8.49, indicating enhanced stability. However, the effects of gullies varied significantly across different regions. Soil moisture content was higher on shaded slopes than on sunny slopes and greater at downslope positions than at upslopes, reaching up to 12.89% in gullies. Slope position exerted a direct and significant positive effect on soil moisture, which, in turn, indirectly influenced vegetation diversity and stability. This study reveals the dominant regulatory role of slope position in soil moisture, vegetation diversity, and stability, providing new perspectives and evidence for developing vegetation restoration strategies on the Loess Plateau and promoting the sustainable growth of regional vegetation. Full article

This study aims to develop a forest landscape stability assessment framework that integrates structure, function, and resilience to assess forest landscape stability under different landform types on the Loess Plateau, and to propose differentiated optimization strategies. Remote sensing images and ground survey data were combined to compare the effectiveness of different machine learning models in aboveground biomass (AGB) inversion. Meanwhile, forest fragmentation and landscape multifunctionality were assessed, and a Landscape Stability Index (LSI) was proposed to quantify regional forest landscape stability. The main findings are as follows: (1) between 2000 and 2022, the degree of forest fragmentation and multifunctionality in the hilly gully region improved significantly, and the Simpson’s Diversity Index (SDI) value showed an increasing trend; the plateau gully region showed a decreasing trend in the SDI value. The degree of forest fragmentation in the hilly gully region was higher and showed significant changes, while the plateau gully region was more stable, with the “Interior” and “Dominant” types dominating. (2) The eXtreme Gradient Boosting model outperformed other models in AGB estimation, with R² = 0.81 and RMSE = 24.67 ton ha⁻¹. (3) The LSI of the hilly gully region generally increased, especially in Yanchang, showing a significant increase in ecological stability; the LSI of the plateau gully region generally decreased, especially in Baishui, showing a trend of weakening stability. Based on the assessment results, optimization strategies for different stabilities were proposed, including the hierarchical management of fragmentation, multi-objective management to improve the SDI, and adaptive management for AGB. The forest landscape stability assessment framework proposed in this study can effectively assess the stability of forest landscapes, reveal the differences in ecological restoration in different regions, and provide new perspectives and strategies for forest landscape management and optimization in the Loess Plateau. Full article

The gullies and valleys of the Loess Plateau, as key ecological zones for soil erosion control, play a critical role in the region’s sustainable development under increasing urbanization. This study employed the Soil and Water Assessment Tool (SWAT) to analyze the impacts of land use/cover changes (LUCC) on runoff at multiple spatial scales and locations within the Sanchuan River Basin (SRB) in the loess hilly and gully region. The methodology integrates SWAT modeling with LUCC scenario analysis, focusing on spatial and scale effects of land use changes on hydrological processes. The results revealed distinct spatial differences, with diminishing LUCC impacts on streamflow from the upper to lower reaches of the basin, regardless of land use type. Scale effects were also evident: grassland effectively controlled runoff within 300 m of riparian zones, while forest land was most effective beyond 750 m. A relatively insensitive range for runoff changes was observed between 300 and 750 m. These findings highlight the critical role of LUCC in influencing runoff patterns and underscore the importance of region-specific and scale-sensitive land use management strategies. This research provides valuable guidance for sustainable land planning, particularly in riparian zones, to enhance runoff control and optimize ecological benefits. Full article

With the rapid urbanization in China, traditional villages are undergoing simultaneous construction and destruction, making it crucial to scientifically balance the protection and development of these villages. The Loess Hilly Area of Northern Shaanxi, one of the most severely eroded regions in the world, was chosen as the study area. Socio-economic, land use, and natural ecological data from 152 traditional villages in this area were analyzed. First, an evaluation model was developed to assess the comprehensive level of protection and development in these villages. Next, a coupling coordination model and spatial autocorrelation model were employed to measure the coordination level and spatial distribution of protection and development. Finally, a coordination influence model was combined with a geographically weighted regression model to reveal the driving mechanisms promoting the coupling coordination between protection and development. The results indicate that (1) the protection and development levels of traditional villages in the study area exhibit contrasting patterns of “high in the east and low in the west” and “high in the west and low in the east”, respectively; (2) nearly half of the regions show a low level of coordination between protection and development, with a few counties and districts in the east achieving better coordination; and (3) the spatial variation in the coupling of protection and development is influenced by regional economic capacity, social development, resource endowment, and policy inclination, with various factors influencing the coordination in different ways. This study helps to further elucidate the relationship between the protection and development of traditional villages and provides valuable references for the protection and development of traditional villages in other ecologically fragile areas. Full article

The hilly and gully region of the Loess Plateau represents one of China’s most ecologically vulnerable landscapes, characterized by severe soil erosion, intensive land use, and pronounced disturbances to the structure and functionality of ecosystem services. Taking Zichang City as a case study, this research integrates grid-scale analysis with the InVEST-PLUS model and bivariate spatial autocorrelation techniques to examine the spatiotemporal dynamics and inter-relations of four critical ecosystem services—carbon storage, water yield, biodiversity, and soil retention—under varying land use intensity scenarios from 1990 to 2035. The findings indicate that (1) between 1990 and 2020, land use intensity in Zichang City steadily declined, exhibiting a spatial distribution pattern typified by central-area clustering and gradual peripheral transitions. (2) Across three development scenarios, the spatial distribution of the four ecosystem services aligned with the patterns observed in 2020, with central areas showing pronounced fluctuations, whereas peripheral regions experienced relatively minor changes. Specifically, from 1990 to 2020, the proportion of low-carbon storage areas increased by 2.89%, and high water yield areas expanded by 9.45%, while the shares of low habitat quality and low soil retention areas decreased by 5.59% and 6.25%, respectively. (3) A significant spatial autocorrelation was observed between land use intensity and the four ecosystem services, with widespread cold and hot spots reflecting dynamic spatial clustering patterns. These results offer valuable insights for optimizing land use strategies, improving ecosystem service performance, and advancing ecological conservation and sustainable development initiatives. Full article

Over recent decades, the hilly and gully regions of the northern Loess Plateau in Shaanxi province have grappled with severe soil erosion and a precarious ecological milieu. Shaped by urbanization policies, this locale has encountered a gamut of issues, including an imbalance in human–environment dynamics and the degradation of ecological integrity. Consequently, the comprehension of how urban expansion impacts the optimization of regional landscape configurations, the alignment of human–environment interactions in the Loess Plateau’s hilly and gully domains, and the mitigation of urban ecological challenges assumes paramount importance. Leveraging data from land use remote sensing monitoring, alongside inputs from natural geography and socio-economic spheres, and employing methodologies such as landscape pattern indices, we conduct an exhaustive analysis of Zichang City’s urban fabric from 1980 to 2020. Furthermore, employing the CLUE-S model, we undertake multifaceted scenario simulations to forecast urban expansion in Zichang City through to 2035. Our findings delineate two distinct phases in Zichang City’s urban expansion trajectory over the past four decades. From 1980 to 2000, urban construction land in Zichang City experienced a phase of methodical and steady growth, augmenting by 64.98 hectares, alongside a marginal decrease in the landscape shape index (LSI) by 0.02 and a commensurate increase in the aggregation index (AI) by 1.17. Conversely, from 2000 to 2020, urban construction land in Zichang City witnessed an epoch of rapid and haphazard expansion, doubling in expanse, marked by a notable escalation in LSI (2.45) and a corresponding descent in the AI (2.85). The precision of CLUE-S model simulations for Zichang City’s land use alterations registers at 0.88, fulfilling the exigent demand for further urban expansion and land use change prognostication. Under the aegis of the natural development scenario, the augmentation of urban construction land in Zichang City primarily encroaches upon grassland, farmland, and woodland, effectuating an increase of 159.81 hectares. Conversely, under the ambit of urbanization development, urban construction land contends predominantly with farmland, grassland, and woodland, heralding an augmentation of 520.42 hectares. Lastly, under the mantle of ecological protection, urban construction land expansion predominantly encroaches upon grassland, farmland, and woodland, resulting in an augmentation of 4.27 hectares. Through a nuanced analysis of the spatiotemporal evolution of urban expansion and scenario-based simulations, this study endeavors to furnish multi-faceted, scenario-driven, and policy-centric insights for regional planning, urban spatial delineation, and regional ecological safeguarding. Full article

Landslides represent a significant global natural hazard, threatening human settlements and the natural environment. The primary objective of the study was to develop a landslide susceptibility modeling approach that enhances prediction accuracy and informs land-use planning decisions. The study utilized a hybrid ensemble-based methodology to improve prediction accuracy and effectively capture the complexity of landslide susceptibility patterns. This approach harnessed the power of ensemble models, employing a bagging algorithm with base learners, including the reduced error pruning decision tree (REPTree) and functional tree (FT) models. Ensemble models are particularly valuable because they combine the strengths of multiple models, enhancing the overall performance and robustness of the landslide susceptibility prediction. The study focused on Yanchuan County, situated within the hilly and gully region of China’s Loess Plateau, known for its susceptibility to landslides, using sixteen critical landslide conditioning factors, encompassing topographic, environmental, and geospatial variables, namely elevation, slope, aspect, proximity to rivers and roads, rainfall, the normalized difference vegetation index, soil composition, land use, and more. Model performances were evaluated and verified using a range of metrics, including receiver operating characteristic (ROC) curves, trade-off statistical metrics, and chi-square analysis. The results demonstrated the superiority of the integrated models, particularly the bagging FT (BFT) model, in accurately predicting landslide susceptibility, as evidenced by its high area under the curve area (AUC) value (0.895), compared to the other models. The model excelled in both positive predictive rate (0.847) and negative predictive rate (0.886), indicating its efficacy in identifying landslide and non-landslide areas and also in the F-score metric with a value of 0.869. The study contributes to the field of landslide risk assessment, offering a significant investigation tool for managing and mitigating landslide hazards in Yanchuan County and similar regions worldwide. Full article

This study explored the innovative use of multiple remote sensing satellites and unmanned aerial vehicles to calculate soil losses in the Loess Plateau of Iran. This finding emphasized the importance of using advanced technologies to develop accurate and efficient soil erosion assessment techniques. Accordingly, this study developed an approach to compare sinkholes and gully heads in hilly regions on the Loess Plateau of northeast Iran using convolutional neural network (CNN or ConvNet). This method involved coupling data from UAV, Sentinel-2, and SPOT-6 satellite data. The soil erosion computed using UAV data showed AUC values of 0.9247 and 0.9189 for the gully head and the sinkhole, respectively. The use of SPOT-6 data in gully head and sinkhole computations showed AUC values of 0.9105 and 0.9123, respectively. The AUC values were 0.8978 and 0.9001 for the gully head and the sinkhole using Sentinel-2, respectively. Comparison of the results from the calculated UAV, SPOT-6, and Sentinel-2 data showed that the UAV had the highest accuracy for calculating sinkhole and gully head soil features, although Sentinel-2 and SPOT-6 showed good results. Overall, the combination of multiple remote sensing satellites and UAVs offers improved accuracy, timeliness, cost effectiveness, accessibility, and long-term monitoring capabilities, making it a powerful approach for calculating soil loss in the Loess Plateau of Iran. Full article

The selection of suitable tree species and the reasonable allocation of planting areas are important measures for improving soil quality. This study aimed to investigate the characteristics of typical vegetation type soil quality differences and their dominant factors in loess hilly–gully areas after returning farmland to the forest (grassland). The soil quality status and dominant factors of arbors, shrubs and grasslands in the study area were comprehensively analyzed using the soil quality index (SQI) and structural equation modeling (SEM). The results showed the following: (1) In the study area, the shrub forest had a high capacity for air permeability, water retention and nitrogen fixation. (2) The soil quality of the three vegetation types improved with increasing precipitation, and the soil quality indicator of shrubs was the highest, indicating a better soil quality improvement. However, the soil quality of the arbors and grasslands showed a greater percentage increase. In the precipitation range of 400–410 mm, the soil quality of shrub forests was significantly higher than that of arbors and grasslands. (3) Structural equation modeling analysis indicated that precipitation, vegetation and soil factors are closely related to soil quality. Further analysis showed that soil bulk density, porosity, capillary water-holding capacity, soil organic carbon and total phosphorus were the dominant factors affecting the soil quality in the study area. The purpose of this study was to evaluate quantitatively the soil quality after different vegetation types under different precipitation gradients, to clarify the variation trend of soil quality at different vegetation types with different precipitation gradients and to provide a scientific basis and data support for the quantitative evaluation of vegetation restoration and selection of tree species and vegetation configuration within different precipitation gradients in loess hilly and gully regions in the future. Full article

Vegetation on the Loess Plateau, China, has continuously improved thanks to certain ecological restoration (ER) strategies, including the integrated soil conservation project that began in the late 1970s and the “Grain for Green” project that began in the 1990s. The experience of these strategies in different geomorphological regions is of great value to ER worldwide. In this study, the evolution of the land-use transition (LUT) pathway and ecosystem service value (ESV) in four geomorphological regions of the Beiluo River Basin was analyzed using geo-informatic Tupu and the equivalent factor method with data from 1975 to 2015. The results indicated that, from 1975 to 2015, the proportion of forestland in the Beiluo River basin increased by 18.27%, while the areas of shrub, grassland, cultivated land, and water decreased by 1.03%, 0.16%, 18.23%, and 0.26%, respectively. In the past 40 years, the overall ESV of the basin increased by USD 3.209 billion (54.16%). The landform, vegetation cover, LUT, and ESV analysis indicated that the main ecological functions of the loess hilly and gully (LHG), loess plateau gully (LPG), rocky mountain (RM), and terrace and plain (TP) regions are soil and water conservation (SWC), SWC and food production, regulation and food production, respectively. ER projects enhanced the main ecological function of individual regions. In detail, the transition of “cultivated land → grassland” enhanced SWC function in the LHG region, and the transition of “grassland (shrub) → forestland” enhanced the regulating services of the RM and LPG regions. Moreover, the transition of “cultivated land to grassland” did not seriously lower the food production services of the TP and LPG regions, owing to the increase in grain yield per unit area. However, there were alternating transitions between cultivated land and ecological land types, implying a game between the peasant households’ demands and the ER strategies. Conflicting demands between local households and the public necessitate precision ER strategies, including land planning, ecological compensation, training and employment for local residents, etc. Full article

Featuring complex and fractured terrain, the Loess hilly and gully regions suffer poor grain production capacity. The behavior of farmers, the major users of agricultural production space, significantly influences the agricultural production space. Hence, it is essential to explore the evolution rules of the agricultural production space under the influence of farmer behavior and reveal the influencing mechanism of agricultural production space change, which will facilitate the promotion of ecological protection and high-quality development of the Yellow River Basin. Relying on six-stage remote sensing images of the Yanhe River Basin from 1995 to 2018, this study utilized a land use dynamic index, transfer matrix and landscape pattern index to analyze the spatial pattern evolution of agricultural production in the Yanhe River Basin. Furthermore, the geographic detector model was applied to quantitatively analyze the influencing factors of the spatial pattern evolution of agricultural production. The results demonstrated the following: (1) From 1995 to 2018, the overall area of cultivated land in the Yanhe River Basin decreased by 927.02 km², with a change degree of 21.07%. The spatial structure of agricultural production changed, mainly transferring the cultivated land to woodland and grassland. (2) The spatial form of agricultural production has changed from fragmentation to regularity, and the complexity of the production space shows a trend of first increasing and then decreasing. (3) The evolution of the spatial pattern of agricultural production was affected by multiple factors of farmer behavior, where significant interactive enhancement effects existed. Specifically, labor input was the dominant factor affecting the overall scale of the production space, with an influence value of 0.202; fertilization input and cultivated land transfer were the key factors affecting the spatial distribution of production, with influence values of 0.264 and 0.242, respectively; income level and social interaction were the base factors affecting the spatial form of production, with influence values of 0.558 and 0.438, respectively. The research results provide scientific support for the improvement of agricultural production quality and the spatial evolution mechanism of agricultural production in the Yanhe River Basin. Full article

To determine the spatial–temporal variations and the factors leading to vegetation recovery in the loess hilly and gully region of China, this study analyzed a two-decade trend in the variation of vegetation cover based on normalized difference vegetation index (NDVI) data from 1998 to 2019 using the Sen + MK test and Hurst index and determined the driving factors using the Geodetector model. The vegetation index in the area was high in the southeast and low in the northwest, with an overall increasing rate of 0.0108/year. The areas with significant improvement in vegetation cover accounted for 95.14%, and the areas with persistent change accounted for 37.36%. Annual precipitation is the most crucial factor driving the NDVI change, and potential evapotranspiration, relative humidity, elevation, land use type, and vegetation type can also explain local variations. The effect of compound factors is significantly greater than that of a single factor. The most effective factors are annual precipitation, potential evapotranspiration, relative humidity and elevation, which varied between 559.4–698.6 mm, 530.6–744.6 mm, 59%–62%, and 2006–2717 m, respectively. The land use, vegetation, and soil types suitable for healthy vegetation growth are forest, coniferous forest, and eluvial soil. Full article

Exploring the complex relationship between ecological restoration and economic development is valuable for decision makers to formulate policy for sustainable development. The large-scale environmental restoration program—Grain for Green—was mainly implemented in the Loess Plateau of China to improve the soil retention service. However, whether this world-famous program affects local economic development has not been fully explored. In this study, using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and spatializing the gross domestic product (GDP) based on the remotely sensed nightlight data, we explored the tradeoff between environment (i.e., soil retention service) and economy (i.e., GDP) for the Loess Plateau in a spatially explicit way. We found that the soil retention service increased prominently over the past 40 years, especially after implementing the Grain for Green project. Meanwhile, the GDP increased about nine-fold over the past four decades from 4.52 to 40.29 × 10⁷ USD. A win–win situation of soil retention and economic development was achieved in the Loess Plateau of China, particularly in the loess gully and loess hilly gully regions of the Loess Plateau. The win–win situation of soil retention and economic development was as a result of the Grain for Green program, the optimization of industrial structure, and the increase in non-agriculture employment. Compared with previous studies, more spatial information was available for the Loess Plateau in this study, which is more valuable to policymakers. Full article

Located in the middle and upper parts of the Yellow River Basin, Qingshuihe County, Inner Mongolia, is a typical hilly and gully loess region and one of areas under the implementation of major ecological protection and restoration projects in the key ecological areas of Yellow River. Scientifically and accurately constructing a soil quality evaluation system for different types of artificial forest land and evaluating their soil quality are essential because they help optimize the structure of artificial forest land and improve the soil quality in the loess hilly area of Yellow River Basin. In this study, soil from four representative types of artificial forest land in the middle and upper reaches of the Yellow River Basin in Inner Mongolia was selected as the study object, with natural non-forest land as the control. Sixteen soil property indices in five classes, namely, soil texture, acid–base properties, moisture, pore, and nutrient, were screened using correlation analysis, minimum dataset (MDS), and principal component analysis methods, and an MDS of soil quality evaluation was constructed. Results showed that (1) the evaluation indices of artificial forest land soil quality based on the MDS included total potassium content, total phosphorus content, alkali-hydrolyzed nitrogen content, total nitrogen content, sand content, moisture content, and non-capillary porosity. (2) No significant differences were observed in the soil quality index among the MDS, total dataset, and significant dataset (SDS), all of which exhibited significant positive correlations. (3) The soil quality of the different types of forest land was sorted from high to low as follows: mixed coniferous and broad-leaved forests, larch forests, mixed arbor and shrub forests, Armeniaca sibirica forests, and natural non-forest land. Full article