Many ecological restoration projects have been carried out in Southwest China; however, changes in vegetation cover in the dry valleys of Southwest China have rarely been reported. With their unique characteristics of high temperatures and low humidity, these dry valleys have considerably lower vegetation cover than their neighboring areas, making them the main sediment sources of rivers in Southwest China. Thus, it is imperative to understand changes in vegetation cover in China’s dry valleys, as well as the effects of changes in precipitation, since water deficit is the dominant cause of obstructed plant growth. In this study, changes in fractional vegetation cover (FVC) in dry valleys in the period 2000 to 2020 were analyzed based on MODIS-NDVI data, and the effects of precipitation were also analyzed. Our results indicated that: (1) the long-term mean annual FVC values in the dry–hot valleys (DHVs), dry–warm valleys (DWVs), and dry–temperate valleys (DTVs) were 0.426, 0.504, and 0.446, respectively; (2) significant decreasing trends in FVC were mainly found in DHVs and DWVs that were distributed in the southwestern part of the dry valley region (DVR), which was mainly due to the decrease in precipitation; and (3) significant increasing trends were reported in DTVs of the Min River and the Baishui River, which was probably due to the increase in precipitation. By analyzing the temporal trends of FVC in dry valleys, this study highlighted the effects of precipitation on the dynamics of FVC and demonstrated that anthropogenic activities such as urbanization, land use changes, and hydro-power project construction may also have considerable effects on FVC in dry valleys. Overall, this study not only provides insights that might inform further detailed studies on the dynamics and mechanisms of vegetation cover, but could also provide valuable guidance for ecological restoration management in the dry valley region.

As China’s urban–rural integration progresses, the connections between urban and rural areas continue to strengthen, making the spatial matching between transportation infrastructure and tourism resources increasingly crucial for coordinated regional development. This study investigates the spatial–temporal mismatch between transportation development and tourism spatial vitality in Yunnan Province, proposing optimization strategies to improve their coordination. Using Weibo check-in big data and OpenStreetMap transportation network data, we apply Convolutional Long Short-Term Memory (ConvLSTM) networks and bivariate spatial autocorrelation analysis to examine this relationship. The results show strong transportation–tourism matching in Kunming and surrounding areas. However, northwest and southern Yunnan exhibit significant mismatches—despite transportation improvements, underdeveloped tourism resources constrain vitality growth. Particularly in some remote regions, well-developed transportation infrastructure coexists with low tourism vitality, revealing persistent spatial mismatches between transport facilities and tourism resources. In general, transportation infrastructure development generally enhances tourism spatial vitality, but requires coordinated tourism resource development and market demand alignment. The study results provide a basis for improving the coordinated development of transportation and tourism, offering practical guidance for policymakers to promote balanced regional development and urban–rural integration.

Non-photosynthetic vegetation (NPV) significantly impacts ecosystem degradation, drought, and wildfire risk due to its flammable and persistent litter. Yet, the accurate estimation of NPV in heterogeneous landscapes, such as dry–hot valleys, has been limited. This study utilized multi-source time-series remote sensing data from Sentinel-2 and GF-2, along with field surveys, to develop an NDVI-DFI ternary linear mixed model for quantifying NPV coverage (f_NPV) in a typical dry–hot valley region in 2023. The results indicated the following: (1) The NDVI-DFI ternary linear mixed model effectively estimates photosynthetic vegetation coverage (f_PV) and f_NPV, aligning well with the conceptual framework and meeting key assumptions, demonstrating its applicability and reliability. (2) The RGB color composite image derived using the minimum inclusion endmember feature method (MVE) exhibited darker tones, suggesting that MVE tends to overestimate the vegetation fraction when distinguishing vegetation types from bare soil. On the other hand, the pure pixel index (PPI) method showed higher accuracy in estimation due to its higher spectral purity and better recognition of endmembers, making it more suitable for studying dry–hot valley areas. (3) Estimates based on the NDVI-DFI ternary linear mixed model revealed significant seasonal shifts between PV and NPV, especially in valleys and lowlands. From the rainy to the dry season, the proportion of NPV increased from 23.37% to 35.52%, covering an additional 502.96 km². In summary, these findings underscore the substantial seasonal variations in f_PV and f_NPV, particularly in low-altitude regions along the valley, highlighting the dynamic nature of vegetation in dry–hot environments.

The vegetation cover in the Red River Basin (RRB) has undergone considerable changes over the past 20 years. Identifying vegetation cover and its transboundary differences is crucial for assessing the ecological health of the region. This study utilized normalized difference vegetation index (NDVI) data (2000–2023) to analyze the spatiotemporal dynamics of fractional vegetation cover (FVC) and its transboundary differences within the RRB. The results revealed the following: (1) From 2000 to 2023, overall FVC in the basin increased, with a mean value of 0.64, indicating favorable vegetation conditions. (2) In terms of spatial distribution, the RRB in China (RRBC) generally exhibited higher FVC in the west and lower FVC in the east, whereas the RRB in Vietnam and Laos (RRBVL) exhibited higher FVC in the east and lower FVC in the west. Regarding spatiotemporal changes, in RRBC, the changes were primarily characterized by both non-significant improvement (56.01%) and extremely significant improvement (21.45%). Conversely, RRBVL exhibited both areas of extremely significant improvement (25.4%) and areas of extremely significant degradation (18%). (3) Anthropogenic activities exerted a stronger influence than precipitation on both spatiotemporal changes and transboundary differences in FVC. In conclusion, an overall increase in FVC is observed throughout the RRB, with notable transboundary variations.

Soil erosion on sloping cropland is a major threat to agricultural sustainability and ecological security in mountainous regions, yet its spatial distribution and landscape-level structural characteristics remain insufficiently quantified. Taking Zhaotong in northeastern Yunnan, China, as a typical mountainous agricultural region in the upper Yangtze River Basin, this study integrated Sentinel-2 imagery, high-resolution reference data, field survey information, the Google Earth Engine platform, a random forest classifier, the Chinese Soil Loss Equation, and landscape pattern metrics to assess soil erosion on sloping cropland. The land use classification achieved an overall accuracy of 90.70% and a Kappa coefficient of 0.88, providing a reliable basis for sloping cropland extraction. Sloping cropland covered 4218.77 km², accounting for 84.64% of total cropland area, but contributed 1.84 × 10⁷ t·yr⁻¹ of annual soil loss, equivalent to 97.51% of total cropland erosion. The mean erosion rate of sloping cropland reached 4260.50 t·km⁻²·yr⁻¹, and 95.84% of sloping cropland exceeded the soil loss tolerance threshold. County-level analysis revealed strong spatial heterogeneity, with high erosion risks concentrated in northern and eastern mountainous counties. Intensive, Severe, and Extreme erosion occupied only 26.14% of the sloping cropland area but contributed 62.21% of total soil loss. Landscape metrics further showed that Moderate erosion had the highest patch density and edge density, indicating a critical fragmentation stage in erosion development. These findings support a tiered conservation strategy in which high-intensity patches are prioritized for immediate sediment reduction, while fragmented Moderate-erosion (2500–5000 t·km⁻²·yr⁻¹) areas receive preventive management. The proposed framework provides a useful approach for identifying erosion hotspots and supporting targeted soil and water conservation in mountainous agricultural landscapes.