With accelerating urbanization, the regional ecological security pattern (ESP) faces unprecedented threats. The situation is particularly serious in the Loess plateau of China (LPC) due to the fragile ecological environment and poor natural conditions. Constructing an ecological network and optimizing the ESP is significant for guiding regional development and maintaining the stability of the ecological process. This study constructed an ecological security network by integrating the minimum cumulative resistance (MCR) model and morphological spatial-pattern-analysis approach in LPC. Additionally, the optimization scheme of the regional ESP has also been proposed. Results show that the ecological source area is about 57,757.8 km², 9.13% of the total area, and is mainly distributed in the southeast of the study area. The spatial distribution of ecological sources shows specific agglomeration characteristics. The ecological security network constructed contains 24 main ecological corridors, 72 secondary ecological corridors, and 53 ecological nodes. Referring to the identified ecological sources area, corridors, nodes, and other core components, the “two barriers, five corridors, three zones and multipoint” ESP optimization scheme was presented. This research hopes to provide a valuable reference for constructing the ecological security network and optimizing ecological space in ecologically fragile areas of western China.

Quantitative analysis of the differences and the exploration of the evolution models of different loess landform types are greatly important to the in-depth understanding of the evolution process and mechanism of the loess landforms. In this research, several typical loess landform areas in the Chinese Loess Plateau were selected, and the object-oriented image analysis (OBIA) method was employed to identify the basic loess landform types. Three-dimensional (3D) landscape pattern indices were introduced on this foundation to measure the morphological and structural features of individual loess landform objects in more detail. Compared with the traditional two-dimensional (2D) landscape pattern indices, the indices consider the topographic features, thereby providing more vertical topographic information. Furthermore, the evolution modes between different loess landform types were discussed. Results show that the OBIA method achieved satisfying classification results with an overall accuracy of 88.12%. There are evident differences in quantitative morphological indicators among loess landform types, especially in indicators such as total length of edge, mean patch size, landscape shape index, and edge dimension index. Meanwhile, significant differences are also found in the combination of loess landform types corresponding to different landform development stages. The degree of surface erosion became increasingly significant as loess landforms developed, loess tableland area rapidly reduced or even vanished, and the dominant loess landform types changed to loess ridge and loess hill. Hence, in the reconstruction and management of the Loess Plateau, the loess tableland should be the key protected loess landform type. These preliminary results are helpful to further understand the development process of loess landforms and provide a certain reference for regional soil and water conservation.

In recent years, applications and analyses based on slope units have become increasingly widespread. Compared with grid units, slope units can better represent terrain features and boundaries and allow a more complete view of the morphology of the Earth’s surface. Maps based on slope units also offer significant improvements for disaster prediction and the analysis of slope land resources. Therefore, we need a reasonable method of slope unit classification. Although some methods have been proposed for slope unit classification, they have been too focused on morphological variations and have not fully considered the importance of geomorphology, and the geomorphological and physical significance of slope partitioning remain unclear. Therefore, we propose a novel slope unit classification method by combining terrain feature lines (CTFL) derived from the meaning of geomorphology ontology that use several terrain feature lines, such as geomorphic water division lines, valley shoulder lines, slope toe lines, and shady/sunny slope boundary lines, to classify slopes. The Jiuyuangou and Lushan study areas were selected to test the CTFL method. Compared with the traditional hydrological method, the CTFL method can effectively overcome topographic abruptness and distortions, improve the uniformity of slope and aspect within individual units, and increase the accuracy of slope unit applications and analyses. This work fully considers the importance of geomorphology and is conducive to future studies of slope unit division.

Tourist attractions, as core components of tourism product supply, play a crucial role in regional tourism development. Investigating the spatial relationship between the supply and demand of tourist attractions contributes to optimizing the spatial structure of regional tourism and promoting high-quality, balanced, and coordinated growth of the tourism industry. Taking high-grade tourist attractions in Anhui Province as the research object, this paper first analyzes the characteristics of accessibility using the time cost distance method and the standard deviational ellipse. Subsequently, it constructs a set of tourism demand indicators and employs the coupling coordination model and Markov chain method to evaluate the spatial coupling coordination between accessibility of tourist attractions and tourism demand. The results show a significant improvement in accessibility of tourist attractions from 2015 to 2024, with average travel time to tourist attractions at the county level decreasing from 65 to 41 minutes, and the proportion of areas reachable within 60 minutes rising from 62.5% to 92.3%. However, spatial disparities persist, particularly exhibiting persistent low accessibility in mountainous and peripheral areas. The coupling coordination levels between the accessibility of tourist attractions and tourism demand remained generally stable, with most counties classified into the moderate and high coordination categories. Spatial Markov analysis indicates that neighboring regions exert strong spatial spillover effects, influencing both the direction and magnitude of coordination level transitions. Notably, leap-level transitions were rare, while adjacent-level shifts dominated the dynamics. These findings underscore the importance of spatial context and infrastructure in shaping the interaction between tourism supply and demand. This study provides empirical evidence to support spatially differentiated planning and transportation investment strategies aimed at promoting balanced tourism development.

Stream morphology is an important indicator for revealing the geomorphological features and evolution of the Yangtze River. Existing studies on the morphology of the Yangtze River focus on planar features. However, the vertical features are also important. Vertical features mainly control the flow ability and erosion intensity. Furthermore, traditional studies often focus on a few stream profiles in the Yangtze River. However, stream profiles are linked together by runoff nodes, thus affecting the geomorphological evolution of the Yangtze River naturally. In this study, a clustering method of stream profiles in the Yangtze River is proposed by plotting all profiles together. Then, a stream evolution index is used to investigate the geomorphological features of the stream profile clusters to reveal the evolution of the Yangtze River. Based on the stream profile clusters, the erosion base of the Yangtze River generally changes from steep to gentle from the upper reaches to the lower reaches, and the evolution degree of the stream changes from low to high. The asymmetric distribution of knickpoints in the Hanshui River Basin supports the view that the boundary of the eastward growth of the Tibetan Plateau has reached the vicinity of the Daba Mountains.

Shoulder lines can best depict the morphological characteristics of the Loess Plateau. Moreover, a shoulder line depicts the external appearance of spatial differentiation of loess landforms and the internal mechanism of loess landform evolution. The efficient and accurate extraction of shoulder lines can help to deepen the re-understanding of the morphological structure and differentiation of loess landforms. However, the problem of shoulder line continuity in the extraction process has not been effectively solved. Therefore, based on high-resolution satellite images and digital elevation model (DEM) data, this study introduced the regional growing algorithm to further correct edge detection results, thereby achieving complementary advantages and improving the accuracy and continuity of shoulder line extraction. First, based on satellite images, the edge detection method was used to extract the original shoulder lines. Subsequently, by introducing the regional growing algorithm, the peaks and the outlet point extracted with the DEM were used as the growth points of the positive and negative (P-N) terrains to grow in four-neighborhood fields until they reached a P-N terrain boundary or a slope threshold. Finally, the P-N terrains extracted by the regional growing method were used to correct the edge detection results, and the “burr” was removed using a morphological image-processing method to obtain the shoulder lines. The experimental results showed that the method proposed in this paper can accurately and effectively complete the extraction of shoulder lines. Furthermore, the applicability of this method is better and opens new ideas for quantitative research on loess landforms.