Maoxian County Research Articles

Qiang Costumes in Maoxian, Sichuan Province: The Revival of Chinese Minority Identity for Application in Design

The purpose of this investigation was to fulfill three objectives: (1) to study the characteristics, connotations and reflected history and social development of Qiang costumes; (2) to study and analyze the cultural identity of Qiang Costumes for development into local products and (3) to design products inspired by Qiang Costumes in Maoxian County, Sichuan. The focus community was the Qiang people in Maoxian County, Sichuan Province, with the research population including local government workers, product sellers, design experts, and target consumers. Using a mixed-methods approach that combined qualitative and quantitative methodologies, the researchers gathered data through surveys, interviews, observations, and questionnaires. Results show that Qiang fabrics in Maoxian County are characterized by a number of local patterns, including fire, clouds, and flowers. These are incorporated into a rich and distinctive ethnic clothing identity. The researchers designed five everyday items based on the symbolism of Qiang clothing: a keychain, tableware, a bookmark, a fridge magnet, and a phone case. A questionnaire distributed to the target group found that the general level of consumer satisfaction with the products was at a very good level (x = 4.83). This investigation provides invaluable insights into the interplay between cultural preservation and economic development, highlighting the crucial role of integrating traditional Qiang culture into modern product design strategies.

Simulation analysis of 3D stability of a landslide with a locking segment: a case study of the Tizicao landslide in Maoxian County, southwest China

Abstract. Rock bridges, also known as locking masses in landslides, affect the three-dimensional (3D) stability and deformation patterns of landslides. However, it is always difficult to simulate rock bridges with continuous grid models in 3D landslides due to their discontinuous deformations. Tizicao landslide, located in Maoxian County, southwest China, is a typical landslide with a super-large rock mass volume of about 1388.2 × 104 m3 and a locking segment. To explore a better rock bridge model used to simulate 3D stability and deformations of the Tizicao landslide, this study introduced three rock bridge models into the FLAC3D program, including the intact rock mass model (IRMM), the Jennings model (JM), and the contact surface model with high strength parameters (CSM-HSP). The CSM-HSP model was eventually used in the FLAC3D program to obtain the 3D deformation characteristics of the landslide. In addition, the two-dimensional (2D) stability of the Tizicao landslide was analyzed using the GeoStudio program. The simulation results indicate that the Tizicao landslide is generally stable under current conditions owing to the existence of the locking segment in its southern front. This inference is consistent with the field deformation and monitoring data. It was found that the general stability and local deformations of the landslide are influenced by the locking segment according to the comparison between the 2D and 3D stability. There was a linear relationship between the locking ratio and the factor of safety (Fos), which applied to the 2D stability analysis of the landslides with a locking segment each, while there existed an approximate quadratic parabola suitable for the 3D stability of the landslides. Finally, this study analyzed the laws of the 3D Fos varying with the locking ratio and strength parameters of the locking masses and the sliding surface. Furthermore, it explored the advantages and disadvantages of the three rock bridge models in the simulation of the 3D stability of landslides with a locking segment.

Bedding slope damage accumulation induced by multiple earthquakes

The 2017 catastrophic Xinmocun landslide was triggered on a bedding slope in the Songpinggou Gully, Maoxian County, China. Previous research primarily focused on the dynamic slope response and deformation characteristics of a single earthquake, and focus on the effect of damage accumulation on slope stability is lacking. The shaking table tests were conducted in this study to understand historical earthquake-induced damage accumulation in bedding slopes. The acceleration amplification coefficient (BPGA) and plastic effect coefficient (PEC) were used to reflect the damage accumulation of bedding slope under the influence of multiple earthquakes. The results revealed that the bedding surface-induced seismic motion amplification contributes to damage constrained on the slope sliding surface. The damage accumulation during multiple earthquakes contributed to slope peak ground acceleration (PGA) amplification increasing and model's natural frequency decreasing in non-linearly form. The shortening of the gap between the driving force frequency and the model's natural frequency had a great impact on the slope damage accumulation. These findings suggest that the accumulation of damage caused by historical earthquake amplification contributes significantly to post-earthquake instability. Future evaluations of slope stability should consider the accumulation and reduced frequency of slope deformation associated with multiple earthquakes.

Early Identification and Influencing Factors Analysis of Active Landslides in Mountainous Areas of Southwest China Using SBAS−InSAR

Potential landslides in the mountainous areas of southwest China pose a serious threat to the lives and property of local residents. Synthetic aperture radar interferometry (InSAR) technology has the advantages of wide coverage, all weather applicability, and low cost and can quickly and accurately identify large range of active landslides, making it a useful geodetic tool for the early identification and prevention of landslides. This paper employed small baseline subset InSAR (SBAS−InSAR) technology and ascending and descending Sentinel−1 data from January 2019 to December 2021 to early identify active landslides in the Maoxian County to Li County National Highway (G317 and G213). The InSAR deformation results were verified by geometric distortion analysis, optical remote sensing interpretation, and field investigation, and 115 active landslides were successfully determined, among which 23 active landslides were identified by ascending and descending Sentinel−1 data together. In addition, InSAR deformation results show that fault, stratigraphic lithology, and rainfall are the three main factors that accelerate the deformation of active landslides and can trigger new active landslides. This study can provide an important reference for the early identification and prevention of landslides in mountainous areas.

Spatial Coupling Pattern and Driving Forces of Rural Settlements and Arable Land in Alpine Canyon Region of the Maoxian County, China.

For mountainous areas in different regions, the study of the spatial coupling relationship between rural settlements and arable land resources is a key aspect of coordinated rural development. In this study, a spatial coupling relationship model and a Geodetector are introduced to explore the spatial coupling relationship and driving factors of rural settlements and arable land in the alpine canyon region. The nearest neighbor index, Voronoi diagram, and landscape pattern index system based on the geographic grid are used to analyze the spatial differentiation characteristics of rural settlements in the alpine canyon region, and the spatial coupling relationship model is introduced to explore the spatial coupling relationship between rural settlements and arable land. Finally, the driving factors of the coupling relationship are detected based on Geodetector. The results show that (1) the spatial distribution of rural settlements in the study area is "T-shaped" with a relatively regular settlement shape; (2) the population in the alpine canyon region is relatively small, and the conflict between people and land is not prominent in most areas, so the overall coupling situation between rural settlements and farming land is dominated by fewer people and more land; and (3) the spatial coupling between rural settlements and arable land in the alpine canyon region is mainly affected by four types of factors: terrain topography, meteorology, soil and population, and economy. The interaction between the factors has a synergistic enhancement effect. The results of the study provide theoretical support for the development of rural settlements in the alpine canyon region.

Ranunculusmaoxianensis (Ranunculaceae), a new species from northwestern Sichuan, China, with an emended description of R.chongzhouensis, the putative closest ally of the new species.

Ranunculusmaoxianensis (Ranunculaceae), a new species from Jiuding Shan in Maoxian county, northwestern Sichuan province, China, is here illustrated and described. The species is morphologically similar to R.chongzhouensis, a species also occurring in Sichuan, in having reniform leaves and puberulous receptacles, carpels and achenes, but differs by having leaves adaxially puberulous with shorter appressed hairs 0.16‒0.28 mm long (vs. longer appressed hairs 0.55‒0.85 mm long), larger flowers (1.8‒2 cm vs. 1.4‒1.6 cm in diameter), larger (8‒10 × 5.5‒6.5 mm vs. 6‒7 × 4.5‒5 mm) and widely obovate petals (vs. obovate), more numerous stamens (35‒55 vs. 12‒18), and subglobose gynoecium and aggregate fruit (vs. ellipsoid). The two species are also different in chromosome number and chromosome morphology. Ranunculuschongzhouensis has a karyotype of 2n = 2x = 16 = 10m + 6sm while R.maoxianensis has a karyotype of 2n = 4x = 32 = 16m + 16sm. An emended description of R.chongzhouensis is provided, and its geographical distribution is largely extended.

Hemipiliaavisoides (Orchidaceae), a new species from Sichuan Province, China.

A new orchid species, Hemipiliaavisoides, is described from Songpan County and Maoxian County, Sichuan Province, China. Morphologically, H.avisoides is most similar to H.hui, but can be distinguished by the combination of its involute middle lip lobe that is smaller than the lateral lobes, floral bracts that are 5 mm long and are always shorter than the ovary, a leaf that is appressed to the substrate and is adaxially green with white lines along 7-9 principal veins and the subterranean stem with a solitary sheath at its base. The floral morphology of H.avisoides is presented by utilising in vivo micro-CT scanning and 3D visualisation.

Landslide susceptibility assessment using statistical and machine learning techniques: A case study in the upper reaches of the Minjiang River, southwestern China

Landslides have frequently occurred in deeply incised valleys in the upper reaches of the Minjiang River. Long-term interactions between rock uplift and river undercutting developed widely distributed landslides in this catchment, which recorded the typical tectonic geomorphology in the eastern margin of the Tibetan Plateau. In this study, we examined the landslides in the Minjiang catchment and aimed to compare the prediction ability of the statistical and machine learning (ML) models in landslide susceptibility assessment. We adopted the statistical models of the frequency ratio (FR) and information value (IV) models, and the ML models represented by a logistic model tree (LMT) and radial basis function classifier (RBFC) for landslide prediction. An inventory map of 668 landslides was compiled, and the landslides were randomly divided into training (80%) and validation (20%) datasets. Furthermore, 11 control factors of landslides based on topography, geology, hydrology, and other environments were applied for the analysis. The comprehensive performance of the four models was validated and compared using accuracy and area under the receiver operating characteristic curve (AUC). The results indicated that both sides of the valley along the Mingjiang and Heishuihe Rivers are in the high and very high susceptibility zones; in particular, the river segment from Wenchuan to Maoxian County has the highest susceptibility. The AUC values of the FR, IV, LMT, and RBFC models with the training data were 0.842, 0.862, 0.898, and 0.894, respectively, while the validation dataset illustrated the highest AUC value of 0.879 in the LMT model, followed by the RBFC (0.871), IV (0.869), and FR (0.839) models. Moreover, the LMT and RBFC models had higher accuracy values than the FR and IV models. This suggests that the ML models are superior to the statistical models in generating adequate landslide susceptibility maps, and the LMT model is the most efficient one for landslide prediction in the study region. This study provides a typical case in a landslide-prone region in the plateau margin to advance the understanding of landslide susceptibility assessment.

Refined landslide susceptibility analysis based on InSAR technology and UAV multi-source data

Landslide susceptibility analysis at the regional scale is the focus of landslide risk management. To obtain more accurate and guiding significance results of landslide susceptibility, it is necessary to conduct a refined analysis on the basis of regional scale. Therefore, we proposed a refined method for landslide susceptibility assessment. This method comprehensively considered the geological and dynamic surface deformation information, and was applied in some areas of Maoxian County. We selected twelve influencing factors (elevation, slope, relief amplitude, curvature, aspect, engineering geological rock group, distance to fault, distance to river, land type, vegetation type, and topographic wetness index, rainfall) and used the traditional machine learning method for landslide susceptibility. Then, the Interferometric Synthetic Aperture Radar (InSAR) technology was introduced to modify the unsuitable zoning of the traditional landslide susceptibility. Based on the improved landslide susceptibility mapping, field investigation and UAV models were used to verify. The results showed that the introduction of InSAR technology and UAV multi-source data can rationalize the inappropriate zoning in traditional landslide susceptibility, and landslides (L1 and L7) with very high susceptibility were identified. The field investigation and spatial-temporal evolution characteristics of typical landslides indicated that both L1 and L7 were severely damaged and in the deformation stage. L1 showed significant deformation during road construction. However, the deformation of L1 reacted on the pavement, resulting in many tensile cracks. The deformation of L7 was mainly affected by rainfall and presented the characteristics of seasonal variation, and the deformation was accelerated in the rainy season. Therefore, the proposed method had a better performance in landslide susceptibility and improved the accuracy. It can realize the refined analysis of landslide susceptibility in a large area and provide technical support for geological hazard susceptibility assessment and reference for disaster prevention and mitigation.

A New Deep Learning Neural Network Model for the Identification of InSAR Anomalous Deformation Areas

The identification and early warning of potential landslides can effectively reduce the number of casualties and the amount of property loss. At present, interferometric synthetic aperture radar (InSAR) is considered one of the mainstream methods for the large-scale identification and detection of potential landslides, and it can obtain long-term time-series surface deformation data. However, the method of identifying anomalous deformation areas using InSAR data is still mainly manual delineation, which is time-consuming, labor-consuming, and has no generally accepted criterion. In this study, a two-stage detection deep learning network (InSARNet) is proposed and used to detect anomalous deformation areas in Maoxian County, Sichuan Province. Compared with the most commonly used detection models, it is demonstrated that the InSARNet has a better performance in the detection of anomalous deformation in mountainous areas, and all of the quantitative evaluation indexes are higher for InSARNet than for the other models. After the anomalous deformation areas are identified using the proposed model, the possible relationship between the anomalous deformation areas and potential landslides is investigated. Finally, the fact that the automatic and rapid identification of potential landslides is the inevitable trend of future development is discussed.

Landslide Susceptibility Mapping with Deep Learning Algorithms

Among natural hazards, landslides are devastating in China. However, little is known regarding potential landslide-prone areas in Maoxian County. The goal of this study was to apply four deep learning algorithms, the convolutional neural network (CNN), deep neural network (DNN), long short-term memory (LSTM) networks, and recurrent neural network (RNN) in evaluating the possibility of landslides throughout Maoxian County, Sichuan, China. A total of 1290 landslide records was developed using historical records, field observations, and remote sensing techniques. The landslide susceptibility maps showed that most susceptible areas were along the Minjiang River and in some parts of the southeastern portion of the study area. Slope, rainfall, and distance to faults were the most influential factors affecting landslide occurrence. Results revealed that proportion of landslide susceptible areas in Maoxian County was as follows: identified landslides (13.65–23.71%) and non-landslides (76.29–86.35%). The resultant maps were tested against known landslide locations using the area under the curve (AUC). This study indicated that the DNN algorithm performed better than LSTM, CNN, and RNN in identifying landslides in Maoxian County, with AUC values (for prediction accuracy) of 87.30%, 86.50%, 85.60%, and 82.90%, respectively. The results of this study are useful for future landslide risk reduction along with devising sustainable land use planning in the study area.

Spatial characteristics of vegetation habitat suitability and mountainous settlements and their quantitative relationships in upstream of Min River, southwestern of China

Vegetation habitat suitability (HS) and mountainous settlements are continuously varying, and display spatial heterogeneity in their spatial arrangement at multiple scales substantially. This paper focuses on spatial characteristics of vegetation HS and mountainous settlement and their quantitative relationships in the upstream of Min River, southwest of China. Based on the spatially distributed maps of vegetation HS types and different nationality mountainous settlements, we first described spatial differentiation and cluster of vegetation HS from global and local standpoints through lacunarity analysis and Multilevel Bayesian model. Then, we depicted the effects of nationality attribute on the spatially distributed characteristics of mountainous settlements. Finally, we revealed the relationships between the geometrical features of mountainous settlements and vegetation HS. The detailed results were as following: 1) The vegetation habitats are classified into four types based on the vegetation HS indexes, the largest spatially heterogeneities of comprehensive, unsuitable and worst unsuitable vegetation HS types occurred in Wenchuan county, but the largest spatially heterogeneities of suitable and sub-suitable vegetation HS categories appeared in Songpan county. The largest spatially clusters of comprehensive, suitable and sub-suitable vegetation HS categories were in Wenchuan, Songpan and Lixian counties, respectively. This suggested that their spatial clusters were low and spatial heterogeneity were high. However, the largest spatially clusters of unsuitable and worst unsuitable vegetation HS types were in Maoxian county. 2) The largest spatially cluster occurred in the Han nationality mountainous settlements revealed their closure characteristics in mountainous regions. Meanwhile, the spatial cluster of all mountainous settlements across watershed approximated to Tibetan nationality mountainous settlement, indicating that the spatial heterogeneity and layout characteristics of Tibetan nationality mountainous settlement could reflect the spatial differentiation of all settlements across watershed. 3) The average values of vegetation HS indexes for Tibetan-Qiang-Hui-Han nationality mountainous settlements were 2.8157, 2.6217, 2.5291 and 2.6441. It meant that the spatial distribution of mountainous settlements perfectly match with spatial pattern of vegetation habitat. Moreover, the sensitivities of geometrical feature characteristics for all mountainous settlements to vegetation HS were similar to Qiang nationality mountainous settlement. The quantitative results obtained from analysis on spatial characteristics of vegetation HS and mountainous settlements, and their interactive relationships could provide effective data supports for ecological construction of vegetation habitat and spatial reconstruction of mountainous settlements.

Analysis of edible characteristics, antioxidant capacities, and phenolic pigment monomers in Lilium bulbs native to China

Lilium is cherished for its health-promoting properties in China. The bulbs of Lilium are rich in phenolic compounds, which are associated with antioxidant capacity. However, no systematic evaluation on phenolic compositions and antioxidant capacities for the edible Lilium native to China has been conducted. Herein, bulbs of 56 wild populations and three cultivars were collected. Their edible characteristics, antioxidant capacities, and pigments have been investigated and analyzed. The results showed that phenolic compounds contributed to the major colors (red, yellow and white) in Lilium bulbs. The seven phenolic pigment monomers responsible for the color of bulbs—cyanidin-3-O-rutinoside, isoquercitrin, regaloside B, regaloside C, regaloside H, regaloside A and regaloside D—were identified by the combination of HPLC-MS and NMR analysis. The population Lilium regale E. H. Wilson (Maoxian County, Sichuan Province) had the highest antioxidant capacity. According to the quantification results, Lilium bulbs with darker and redder colors possessed larger biomass, better nutrient compositions, significantly higher bioactive constituents, and higher antioxidant capacities than the three currently consumed cultivars of edible lily bulbs. Overall, these findings suggest that the mountainous area of southwest China could be the fourth source of edible lilies with the bulb-colored Lilium species.

Application of CORS in Landslide Monitoring

Global Navigation Satellite System (GNSS) can provide continuous and high-precision absolute displacement information and therefore has been an important technical means of landslide surface displacement monitoring. When GNSS is used for landslide monitoring, a reference station is usually set for a monitoring landslide (referred to as “one reference station for one landslide”). Through the method of short baseline relative positioning, high-precision monitoring is realized by eliminating the atmospheric propagation error with strong spatial correlation. However, this application mode has problems such as high monitoring cost, low data reuse of reference station, and heavy dependence on the single reference station for the calculation results of monitoring stations, which limit the large-scale promotion and application of GNSS in landslide monitoring. Aiming at the above problems, this study took Liujiafen Landslide in Maoxian County, Sichuan Province as a case to study the application of Continuously Operating Reference Stations (CORS) and Virtual Reference Station (VRS) issued by Natural Resource system in landslide monitoring to optimize the existing application mode of “one reference station for one landslide”. In this study, the evaluation of the quality of VRS data, the calculation accuracy of static base line, and the comparative analysis of the calculation results between virtual and physical reference stations were carried out to demonstrate the applicability of CORS in landslide monitoring. According to the results: (1) The data quality of the selected virtual reference station was good; (2) The calculation accuracy of the baseline composed of virtual reference station and monitoring station was basically equal to that of the baseline composed of physical reference station and monitoring station. In view of the regional differences in the construction density and quality of CORS reference stations, and the relationship between atmospheric propagation correction model and topographic relief, it is suggested that the application should be decided after comprehensive evaluation based on the actual distribution of reference stations and specific environmental conditions.

Study on Genetic Relationship of Genus Corylus Resources in Sichuan Province Based on SSR Markers

At least seven domestic wild hazelnut species are distributed in Sichuan province, which is an important distribution area for genus Corylus resources. In this study, nine SSR markers were used to analyze the population genetic diversity and genetic relationships of C. heterophylla var. sutchuenensis, C. yunnanensis, C. ferox, C. mandshurica, and C. avellana. The results showed that the mean number of effective alleles, observed heterozygosity, expected heterozygosity, and Shannon's information index of eleven test populations were 2.772, 0.644, 0.546, and 1.016, respectively, indicating that the population genetic diversity was at a medium level. In addition, the population diversity level of C. heterophylla var. sutchuenensis in Maoxian county and of C. yunnanensis in Luding county were higher than the other populations. Meanwhile, principal coordinate analysis and UPGMA cluster analysis showed that C. mandshurica was closely related with C. avellana, and that C. heterophylla var. sutchuenensis was also closely related with C. yunnanensis. This study was helpful to promote the breeding, protection and utilization of hazelnut germplasm resources in Sichuan province.

The Xinmo rockslide-debris avalanche: An analysis based on the three-dimensional material point method

On June 24, 2017, a catastrophic rock avalanche with a volume of 5.08 × 106 m occurred in Xinmo village, Maoxian County, Sichuan Province, SW China. Several studies focusing on the triggering factors, failure mechanism and dynamic process of the Xinmo landslide have been reported in the literature. However, there are few studies with detailed three-dimensional investigations based on numerical modeling that assess the post-failure stage of the landslide. In the present study, the three-dimensional material point method is used to reproduce the kinematics of the landslide to obtain better insight into the disaster by considering the effects of fragmentation and entrainment. Based on this framework, a velocity-weakening friction law is implemented to describe the basal friction between the moving mass and the substrate, and a strain–softening Drucker–Prager constitutive model is used to describe the internal deformation of the moving mass. The entrainment processes obtained with and without the proposed model are compared, and the simulated results generated with the presented models showing the distribution characteristics of the materials in the deposit area match the observed results fairly well. The implementation of a velocity-weakening friction law and a strain-softening Drucker–Prager constitutive model in the material point method may provide valuable insight for the enforcement of physically based risk assessments of “rockslide-debris avalanches”.

Preliminary Identification of Geological Hazards from Songpinggou to Feihong in Mao County along the Minjiang River Using SBAS-InSAR Technique Integrated Multiple Spatial Analysis Methods

Landslides and collapses are common geological hazards in mountainous areas, posing significant threats to the lives and property of residents. Therefore, early identification of disasters is of great significance for disaster prevention. In this study, we used Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology to process C-band Sentinel-1A images to monitor the surface deformation from Songpinggou to Feihong in Maoxian County, Sichuan Province. Visibility analysis was used to remove the influence of geometric distortion on the SAR images and retain deformation information in the visible area. Hot spot and kernel density analyses were performed on the deformation data, and 18 deformation clusters were obtained. Velocity and slope data were integrated, and 26 disaster areas were interpreted from the 18 deformation clusters, including 20 potential landslides and 6 potential collapses. A detailed field investigation indicated that potential landslides No. 6 and No. 8 had developed cracks and were severely damaged, with a high probability of occurrence. Potential collapse No. 22 had developed fissures, exposing a dangerous rock mass and posing significant threats to the lives and property of residents. This study shows that the proposed method that combines visibility analysis, InSAR deformation rates, and spatial analysis can quickly and accurately identify potential geological disasters and provide guidance for local disaster prevention and mitigation.

Experimental investigation on the seismically induced cumulative damage and progressive deformation of the 2017 Xinmo landslide in China

A catastrophic landslide occurred in Xinmo village, Maoxian County, China, on June 24, 2016. The landslide destroyed the whole village and caused 10 deaths, and 73 people were reported to be missing. In this study, the contributions of historical earthquakes to rock damage and progressive deformation are the main focus. A detailed field investigation revealed that historical earthquakes seriously damaged the rock mass in the source area, and there were five macrocracks in this area before the landslide. The landslide was initiated along the cracks and foliation plane of the phyllite under long-term gravity. The rock damage induced by historical earthquakes was tested by uniaxial cyclic loading tests. The results indicate that the damage in the phyllite induced by earthquakes is significantly greater than that to slate and metamorphic sandstone. Moreover, the static loading after earthquakes can trigger the long-term deformation of phyllite, and it is accelerated with the incremental damage in the phyllite. Finally, catastrophic failure was triggered when the phyllite was in a significantly damaged state. As a result, the joint influence of historical earthquakes and long-term gravity loading contributed to the progressive deformation of the Xinmo landslide.

A DEM fusion method for ascending and descending orbit StereoSAR DEMs in complicated mountain areas considering SAR echo intensity

To extract the high-quality DEM in complicated mountain areas, a DEM fusion method for ascending and descending orbit StereoSAR DEMs considering Synthetic Aperture Radar (SAR) echo intensity is proposed. After the analysis for the influence of terrain features and SAR side-looking imaging characteristics on radar echo intensity and DEM accuracy, four TerrasAR-X images with the stripmap mode and the 3 m spatial resolution covering a certain area of Maoxian County, Sichuan Province, China, was selected as the experimental area. StereoSAR technology was used to extract the ascending orbit StereoSAR DEM and the descending orbit StereoSAR DEM, respectively, and the corresponding radar echo intensity map was calculated. Then, while comparing the radar echo intensity corresponding to the same point position, DEM fusion was carried out, and the accuracy of DEM before and after the fusion was analyzed with the ground points measured by GNSS-RTK as reference data. Finally, a high-quality DEM with a 3 m spatial resolution in the experimental area was obtained. The DEM accuracy was improved on all slopes, and the mean absolute deviation (MAD) improved to 4.798 m, the standard deviation (SD) improved to 6.087 m and the LE90 improved to 40.48 m. The experimental results indicate that the fusion method of high-resolution ascending and descending orbit StereoSAR DEMs considering SAR echo intensity can effectively extract DEM with high accuracy and reliability, which can provide technical support for obtaining high-quality terrain information in similar areas.

An Investigation Report on Cultural Poverty Alleviation in Ethnic Minority Areas—Taking the Survey Data from Changdou Village of Maoxian County as an Example

The targeted poverty alleviation strategy emphasizes cultural poverty alleviation, which helps poor households get rid of poverty and effectively prevent them from getting back to poverty. This paper takes the villagers of Changdou Village in Qiang Ethnic region as the main object. Through field investigation and questionnaire, it is concluded that there are some problems in the village, such as low level of education, serious poverty culture phenomenon, insufficient development of local characteristic cultural resources, and imperfect construction of spiritual civilization. Based on the research data of Changdou Village and making full of the cultural resource advantages of the supporting units, in this paper the targeted poverty alleviation of the village’s culture will be emphasized, and corresponding suggestions on cultural poverty alleviation put forward from four dimensions “ambition, wisdom, governance and system”.