Search Results (11)

To ensure water source security and sustainability of the national major strategic project “South-to-North Water Diversion”, this study aims to evaluate the spatio-temporal evolution characteristics of the ecosystem service value (ESV) in its water source area from 2002 to 2022. This study reveals its changing trends and main influencing factors, and thereby provides scientific support for the ecological protection and management of the water source area. Quantitative assessment of the ESV of the region was carried out using the Equivalence Factor Method (EFM), aiming to provide scientific support for ecological protection and resource management decision-making. In the past 20 years, the ESV has shown an upward trend year by year, increasing by 96%. The regions with the highest ESV were Garzê Prefecture and Aba Prefecture, which increased by 130.3% and 60.6%, respectively. The ESV of Xinlong county, Danba county, Rangtang county, and Daofu county increased 4.8 times, 1.5 times, 12.5 times, and 8.9 times, respectively. In the last two decades, arable land has decreased by 91%, while the proportions of bare land and water have decreased by 84% and 91%, respectively. Grassland had the largest proportion. Forests and grasslands, vital for climate regulation, water cycle management, and biodiversity conservation, have expanded by 74% and 43%, respectively. It can be seen from Moran’s I index values that the dataset as a whole showed a slight positive spatial autocorrelation, which increased from −0.041396 to 0.046377. This study reveals the changing trends in ESV and the main influencing factors, and thereby provides scientific support for the ecological protection and management of the water source area. Full article

Under global climate change, sustainable management of plant resources in alpine canyon regions faces severe challenges. M. esculenta, highly valued for its edible and medicinal properties, is widely harvested for consumption by residents in the upper Dadu River–Minjiang River region. This study employs ensemble models to simulate the potential distribution of M. esculenta in this region, predicting the impacts of future climate change on its distribution, centroid migration of suitable habitats, and niche dynamics. Additionally, a production dynamics model integrating ecological suitability and nutritional components was developed to delineate current and future potential cultivation zones for M. esculenta. The results indicate that current high-suitability areas and core cultivation zones of M. esculenta are predominantly distributed in a patchy and fragmented pattern. The high-suitability habitats in the upper Dadu River–Minjiang River region have three distribution centers: the largest spans southern Danba County, southern Jinchuan County, and northeastern Kangding City, while the other two are located in northeastern Li County, southwestern Aba County, and northwestern Ma’erkang City, with sporadic distributions in Heishui County, Maoxian County, and Wenchuan County. First-level cultivation areas are primarily concentrated in Kangding City, Danba County, Ma’erkang City, Li County, and surrounding regions. Under climate change, low-suitability areas and third-level cultivation zones for M. esculenta in the region have increased significantly, while high- and medium-suitability areas, along with first- and second-level cultivation zones, have decreased notably. Concurrently, suitable habitats and cultivation zones exhibit a migration trend toward higher northern latitudes. The most pronounced changes in suitable areas and cultivation zones, as well as the largest niche migration, occur under the high-emission climate scenario. This study facilitates the formulation of suitability-based management strategies for M. esculenta in the upper Dadu River–Minjiang River region and provides a scientific reference for the sustainable utilization of mountain plant resources under climate change. Full article

The Western Sichuan Plateau, an ecologically critical transition zone between the Qinghai–Tibet Plateau and the Sichuan Basin, is also a typical fragile and sensitive area in China’s ecological security. This study established a multi-process evaluation model using the Spatial Distance Index Method, integrating cluster analysis, Sen–Mann–Kendall trend detection, and OWA-based scenario simulations to assess composite ecological sensitivity dynamics. The optimal geodetector was further applied to quantitatively determine the driving mechanisms underlying these sensitivity dynamics. The research showed the following findings: (1) From 2000 to 2020, the ecological environment of the Western Sichuan Plateau exhibited a phased pattern characterized by significant improvement, partial rebound, and overall stabilization. The composite ecological sensitivity grading index showed a declining trend, indicating a gradual reduction in ecological vulnerability. The effectiveness of ecological restoration projects became evident after 2010, with the area of medium- to high-sensitivity zones decreasing by 24.29% at the regional scale compared to the 2010 baseline. (2) The spatial pattern exhibited a gradient-decreasing characteristic from west to east. Scenario simulations under varying decision-making behaviors prioritized Jiuzhaigou, Xiaojin, Jinchuan, Danba, and Yajiang counties as ecologically critical. (3) Driving force analysis revealed a marked increase in the explanatory power of freeze-thaw erosion, with its q-value rising from 0.49 to 0.80. Moreover, its synergistic effect with landslide disasters spans 74.19% of county-level units. Dominant drivers ranked: annual temperature range (q = 0.32) > distance to faults (q = 0.17) > slope gradient (q = 0.16), revealing a geomorphic-climatic-tectonic interactive mechanism. This study provided methodological innovations and decision-making support for sustainable environmental development in plateau transitional zones. Full article

Landslides play a crucial role in landscape evolution, particularly in tectonically active areas. However, research on the relationship between landslide development and landscape evolution remains limited. This study examines the hypsometric integral (HI) values of the Daduhe river mainstem catchments to assess the landscape evolution stage and investigate its spatial correlation with the occurrence of landslides. Additionally, it evaluates the distribution of large landslides concerning elevation and slope. Furthermore, by analyzing the longitudinal profile of the Daduhe river, this study explores the relationship between the occurrence of landslides and knickpoints, as well as the impact of landslides on catchment morphology and material redistribution. The results show that the HI values of catchments along the Daduhe river range from 0.35 to 0.71, exhibiting a progression from youth to maturity and monadnock stages from upstream to downstream. Large landslides were predominantly distributed in areas with elevations of 1000–2000 m and slopes < 40°. Their distribution was closely linked to HI values: large landslides were sparse in catchments with HI > 0.5 (Banma county to Danba county) but more frequent in catchments with HI < 0.5 (Danba county to the river outlet). The longitudinal profile of the Daduhe river illustrates variations in channel morphology, with large landslides entering the river and facilitating the formation of knickpoints. The impact of large landslides on catchment landscape transformation, both in terms of morphology and material movement, exhibits a trend of gradual intensification from upstream to downstream. This study shows that landscape evolution can provide rich information to locate regions prone to landslides. Full article

The ancient Aniangzhai (ANZ) landslide in Danba County, Sichuan Province of southwest China was reactivated after a series of complex hazard events that occurred in June 2020. Since then, and until June 2021, emergency engineering work was carried out to prevent the further failure of the reactivated landslide. This study investigates the potential of joint use of time series Interferometric Synthetic Aperture Radar (InSAR) and optical pixel offset tracking (POT) to assess deformation characteristic and spatial-temporal evolution of the reactivated ANZ landslide during the post-failure stage. The relationships between sun illumination differences, temporal baseline of correlation pairs and the uncertainties were deeply explored. Surface deformation along the line-of-sight (LoS) direction was retrieved by the time series InSAR processing with the two Sentinel-1 datasets, revealing a maximum deformation rate up to 190 mm/year. The large horizontal displacements were also detected from the POT processing using 11 optical images acquired by the PlanetScope satellite (3 m spatial resolution), showing a significant increase of about 24 m between 24 June 2020 and 11 June 2021. The time series analysis from the InSAR and optical POT results revealed that the reactivated ANZ landslide body is gradually slowing down to a steady deformation status since its occurrence in August 2020, indicating the effectiveness of engineering work on the prevention of further landslide. A slight acceleration was detected from both InSAR and optical POT time series analysis between May 2021 and June 2021, which could be caused by the increased rainfall in May 2021. Full article

The Niexia slope, located in Danba County, Sichuan Province, China, with steep slope terrain and dense vegetation coverage, has a height difference of about 3002 m. A traditional manual survey cannot be performed here, and single remote sensing technology is not comprehensive enough to identify potential landslides on such high and steep slopes. In this paper, an integrated approach with multi-remote sensing techniques was proposed to identify potential landslides of the Niexia slope, which combined Interferometry Synthetic Aperture Radar (InSAR), airborne Light Detection and Ranging (LiDAR), and optical remote sensing technologies. InSAR technology was used to monitor the small displacements of the whole slope, and three potential landslides on Niexia slope were identified. The maximum cumulative displacement reached up to 11.9 cm over 1 year. Subsequently, high-resolution optical remote sensing images acquired by remote sensing satellites and a Digital Elevation Model (DEM) without vegetation influence obtained by LiDAR were used to finely interpret the sign of landslide micro-geomorphology and to determine the potential landslide geometry boundaries. As a result, four and nine potential landslides with landslide micro-geomorphic features were identified, respectively. Finally, the identification results of the three techniques were fused and analyzed to assess the potential landslides on the Niexia slope. We compared the results from multi-remote sensing technologies, showing that the three techniques have advantages and disadvantages in terms of monitoring objects, monitoring range, and monitoring accuracy. The integrated use of these three technologies can identify and monitor potential landslides more comprehensively, which could play an important role in the future. Full article

In the process of development, traditional villages, as important tourism resources, have been impacted by external factors and lost their original authenticity. Looking for the important factors affecting its tourism development, in an attempt to assist the sustainable development of a rural destination, is Jiaju Tibetan Village in the Southwest of China. The sustainable evaluation index system divides the assessment criteria into five guideline layers: economic development, ethnic culture, management, sustainable development, and infrastructure and service facilities. The sub-criteria layer and the index layer under each of the guideline layers were refined, and matrices were constructed for various layers of indices, which calculate the weight of each indicator to produce a comprehensive score of the destination’s sustainability. The findings of this study are as follow: ➀ the Tibetan ethnic cultural life experience and the convenience of transportation are the most influential factors. ➁ Jiaju Tibetan Village is in a stage of basic sustainable development. ➂ The determinants of the indicators should be adjusted according to the tourist destination. ➃ Traditional villages should learn from each other’s tourism development experience. Finally, this study provides a reference for adjusting and formulating the tourism development strategy of ethnic traditional villages, and reasonable planning to use land, and plays an exemplary role for the development of traditional villages in concentrated ethnic minority areas. Full article

The technique of interferometric synthetic aperture radar (InSAR) is increasingly employed for landslide detection over large areas, even though the limitations of initial InSAR analysis results have been well acknowledged. Steep terrain in mountainous areas may cause geometric distortions of SAR images, which could affect the accuracy of InSAR analysis results. In addition, due to the existence of massive ground deformation points in the initial InSAR analysis results, accurate landslide recognition from the initial results is challenging. To efficiently identify potential landslide areas from the ascending–descending SAR datasets, this paper presents a novel interpretation approach to analyze the initial time-series InSAR analysis results. Within the context of the proposed approach, SAR visibility analysis, conversion analysis of deformation rates obtained from the time-series InSAR analysis, and spatial analysis and statistics tools for cluster extraction are incorporated. The effectiveness of the proposed approach is illustrated through a case study of landslide identification in Danba, a county in Sichuan, China. The potential landslide regions in the study area are identified based on the interpretation of small baseline subset InSAR (SBAS-InSAR) results, obtained with ascending–descending Sentinel-1A datasets. Finally, on the basis of the field survey results, a total of 21 landslides are detected in the potential landslide regions identified, through which the results obtained from the proposed interpretation approach are tested. Full article

On 17 June 2020, a large ancient landslide over the Aniangzhai (ANZ) slope, Danba County, Sichuan Province, China, was reactivated by a series of multiple phenomena, including debris flow triggered by heavy rainfall and flooding. In this study, Synthetic Aperture Radar (SAR) images acquired by the Sentinel-1A/B satellite and optical images captured by the PlanetScope satellites were jointly used to analyze and explore the deformation characteristics and the Spatial-Temporal evolution of the ANZ landslide before and after the multi-hazard chain. Several areas of pre-failure movements were found from the multi-temporal optical images analysis before the reactivation of the ANZ landslide. The large post-failure surface deformation over the ANZ slope was also retrieved by the optical pixel offset tracking (POT) technique. A major northwest movement with the maximum horizontal deformation of up to 14.4 m was found. A time-series InSAR technique was applied to analyze the descending and ascending Sentinel-1A/B datasets spanning from March 2018 to July 2020, showing that the maximum magnitudes of the Line of Sight (LoS) displacement velocities were −70 mm/year and 45 mm/year, respectively. The Spatial-Temporal evolution over the ANZ landslide was analyzed based on the time-series results. No obvious change in acceleration (precursory deformation) was detected before the multi-hazard chain, while clear accelerated deformation can be observed over the slope after the event. This suggested that heavy rainfall was the most significant triggering factor for the generation and reactivation of the ANZ landslide. Other preparatory factors, including the deformation behavior, the undercutting and erosion of the river and the outburst flood, the local terrain conditions, and earthquakes, might also have played an important role in the generation and reactivation of the landslide. Full article

Interferometric synthetic aperture radar (InSAR) technology is known as one of the most effective methods for active landslide identification and deformation monitoring in large areas, and thus it is conducive to preventing and mitigating the losses caused by landslides. However, great uncertainty inevitably exists due to influences of complex terrains, dense vegetations, and atmospheric interferences in the southwestern mountainous area of China, and this is associated with false or erroneous judgment during the process of landslide identification. In this study, a landslide identification method is put forward by integrating InSAR technology and airborne light detection and ranging (LiDAR) technology. Via this method, surface deformation characteristics detected by InSAR technology and micro-geomorphic features reflected by LiDAR technology were used to identify and map landslides of large areas. Herein, the method was applied to process 224 Sentinel-1 images covering Danba County and its surrounding areas (540 km²) from October 2014 to September 2020. Firstly, 44 active landslides with total areas of 59 km² were detected by stacking InSAR technology. Then, major regions up to 135 km² were validated by data gained from the airborne LiDAR technology. Particularly, several large landslides with lengths and/or widths of more than 2 km were found. Further, the precipitation data were integrated with the above results to analyze the temporal deformation characteristics of three typical landslides from major regions via SBAS InSAR technology. The key findings were as follows: (1) The combination of InSAR and LiDAR technologies could improve the accuracy of landslide detection and identification; (2) there was a significant correlation between temporal deformation characteristics of some landslides and monthly rainfall, with an obvious hysteretic effect existing between the initiation timing of rainfall and that of deformation; (3) the results of this study will be important guidance for the prevention and control of geological hazards in Danba County and areas with similar complex geomorphological conditions by helping effectively identify and map landslides. Full article

This paper focuses on thermal environmental conditions in the stone dwellings of a Tibetan village in Danba County, Sichuan, China, in winter. During the study, field measurements and subjective survey studies were collected, simultaneously, to provide a comprehensive understanding of the thermal comfort conditions that were experienced by residents in cold rural areas of Sichuan. Subjective surveys involved questions about thermal comfort perceptions and acceptability in cold conditions. The status of thermal comfort and characteristics of indoor environmental qualities were investigated in the study. The majority of survey participants (47% and 74%) voted as “slightly cool” for temperature, and “slightly dry” for humidity in the studied typical winter days, respectively. The available adaptive opportunities for the residents were investigated through the survey studies. Adjusting clothing, drinking hot beverages, blocking air infiltration through windows, and changing activities were the most common adaptive measures. An adaptive coefficient ( $\mathsf{\lambda }$ ) was determined based on adaptive predicted mean votes (aPMV) models using least square methods to assess the different adaptation measures in the region. Findings of this study provided a valuable reference for thermal comfort adaptations in cold climates, where limited adaptive opportunities were available due to the low standard of living. Full article