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The highway is an important mode of transportation in the Qinghai–Tibet Plateau, and can be regarded as a major contributor to the high-quality and sustainable development of the Qinghai–Tibet Plateau. It is of great significance to explore its spatial distribution and characteristics for understanding the regional and geographical process. Although Qinghai–Tibet Plateau’s highway transportation infrastructure has been experiencing rapid development in recent years, there lacks a systematic examination of the whole Qinghai–Tibet Plateau from the perspective of supportive capacity for its socio-economic activities. This paper applies geospatial analysis methods, such as network analysis, spatial statistics, and weighted overlay, to model the highway transport dominance in the Qinghai–Tibet Plateau in 2015 at the county scale and reveals the basic characteristics of the highway transport dominance’s spatial pattern. The results are mainly of four aspects: 1) there is a significant difference between the east and west of the highway in the Qinghai–Tibet Plateau, showing an irregular circle structure of gradual attenuation from the east to west; 2) at the county scale, the highway transport dominance in the Qinghai–Tibet Plateau shows strong spatial autocorrelation and a certain extent of spatial heterogeneity, presenting a spatial distribution pattern of High–High and Low–Low clustering; 3) the urban locations of Lhasa, Xining and other center cities have obvious spatial constraints on the distribution of highway transport dominance and generally have a logarithmic decline trend; and 4) there are obvious differences in distribution among the three Urban Agglomerations in the Qinghai–Tibet Plateau. Due to the influence of traffic location, topography, construction of national trunk lines, and level of socio-economic development., the traffic conditions of Lan-Xi Urban Agglomeration and Lhasa Urban Agglomeration are better than Kashgar Urban Agglomeration. This study can be used to guide the optimization of the highway network structure and provide a macro decision-making reference for the planning and evaluation of major highway projects in the Qinghai–Tibet Plateau.
Zhiheng Wang; Hongkui Fan; Daikun Wang; Tao Xing; Dongchuan Wang; Qiaozhen Guo; Lina Xiu. Spatial Pattern of Highway Transport Dominance in Qinghai–Tibet Plateau at the County Scale. ISPRS International Journal of Geo-Information 2021, 10, 304 .
AMA StyleZhiheng Wang, Hongkui Fan, Daikun Wang, Tao Xing, Dongchuan Wang, Qiaozhen Guo, Lina Xiu. Spatial Pattern of Highway Transport Dominance in Qinghai–Tibet Plateau at the County Scale. ISPRS International Journal of Geo-Information. 2021; 10 (5):304.
Chicago/Turabian StyleZhiheng Wang; Hongkui Fan; Daikun Wang; Tao Xing; Dongchuan Wang; Qiaozhen Guo; Lina Xiu. 2021. "Spatial Pattern of Highway Transport Dominance in Qinghai–Tibet Plateau at the County Scale." ISPRS International Journal of Geo-Information 10, no. 5: 304.
Due to the difference of the spatial and temporal distribution of rainfall and the complex diversity of the disaster-prone environment (topography, geological, fault, and lithology), it is difficult to assess the hazard of landslides at the regional scale quantitatively only considering rainfall condition. Based on detailed landslide inventory and rainfall data in the hilly area in Sichuan province, this study analyzed the effects of both rainfall process and environmental factors on the occurrence of landslides. Through analyzing environmental factors, a landslide susceptibility index (LSI) was calculated using multiple layer perceptron (MLP) model to reflect the regional landslide susceptibility. Further, the characteristics of rainfall process and landslides were examined quantitatively with statistical analysis. Finally, a probability model integrating LSI and rainfall process was constructed using logistical regression analysis to assess the landslide hazard. Validation showed satisfactory results, and the inclusion of LSI effectively improved the accuracy of the landslide hazard assessment: Compared with only considering the rainfall process factors, the accuracy of the landslide prediction model both considering the rainfall process and landslide susceptibility is improved by 3%. These results indicate that an integration of susceptibility index and rainfall process is essential in improving the timeliness and accuracy of regional landslide early warning.
Zhiheng Wang; Dongchuan Wang; Qiaozhen Guo; Daikun Wang. Regional landslide hazard assessment through integrating susceptibility index and rainfall process. Natural Hazards 2020, 104, 2153 -2173.
AMA StyleZhiheng Wang, Dongchuan Wang, Qiaozhen Guo, Daikun Wang. Regional landslide hazard assessment through integrating susceptibility index and rainfall process. Natural Hazards. 2020; 104 (3):2153-2173.
Chicago/Turabian StyleZhiheng Wang; Dongchuan Wang; Qiaozhen Guo; Daikun Wang. 2020. "Regional landslide hazard assessment through integrating susceptibility index and rainfall process." Natural Hazards 104, no. 3: 2153-2173.
Agricultural floods in the middle and lower reaches of the Yangtze River, known as the “land of fish and rice” in China, have increased both in areal coverage and frequency over the past 50 years, presenting a grave challenge to sustainable development and food security in the region. Studying the spatiotemporal variation characteristics of agricultural floods in this region is thus important for providing a scientific basis for regional flood control and disaster mitigation. We used variation trend analyses, Mann–Kendall tests, wavelet analyses, and center of gravity modeling to study spatiotemporal changes in agricultural floods in the study area, based on agricultural flood indicators. Changes in agricultural flood frequency showed an overall increasing trend. The frequency of floods changed abruptly in 1990, with the average frequency of floods per station increasing by 0.2086/year from 1991 through 2018, characterized by multiple time-scale changes. The time scale of 17 years had three low–high cycles, that of eight years had six, and that of four years had 13. Agricultural floods in the study area were concentrated in the southern Yangtze River and mainly occurred in northeastern Jiangxi Province and the southeastern Zhejiang Province. The area with high agricultural flood indices increased. Agricultural floods were closely related to the Yangtze River and the direction of the gravity center of agricultural floods was similar to that of the river. Affected by precipitation intensity and frequency, the gravity center fluctuated greatly and generally alternated from southwest to northeast.
Shuqi Wu; Shisong Cao; Zhiheng Wang; Xinyuan Qu; Shanfei Li; Wenji Zhao. Spatiotemporal Variations In Agricultural Flooding In Middle and Lower Reaches of Yangtze River From 1970 to 2018. Sustainability 2019, 11, 6613 .
AMA StyleShuqi Wu, Shisong Cao, Zhiheng Wang, Xinyuan Qu, Shanfei Li, Wenji Zhao. Spatiotemporal Variations In Agricultural Flooding In Middle and Lower Reaches of Yangtze River From 1970 to 2018. Sustainability. 2019; 11 (23):6613.
Chicago/Turabian StyleShuqi Wu; Shisong Cao; Zhiheng Wang; Xinyuan Qu; Shanfei Li; Wenji Zhao. 2019. "Spatiotemporal Variations In Agricultural Flooding In Middle and Lower Reaches of Yangtze River From 1970 to 2018." Sustainability 11, no. 23: 6613.
Landslides are usually initiated under complex geological conditions. It is of great significance to find out the optimal combination of predisposing factors and create an accurate landslide susceptibility map based on them. In this paper, the Information Value Model was modified to make the Modified Information Value (MIV) Model, and together with GIS (Geographical Information System) and AUC (Area Under Receiver Operating Characteristic Curve) test, 32 factor combinations were evaluated separately, and factor combination group with members Slope, Lithology, Drainage network, Annual precipitation, Faults, Road and Vegetation was selected as the optimal combination group with an accuracy of 95.0%. Based on this group, a landslide susceptibility zonation map was drawn, where the study area was reclassified into five classes, presenting an accurate description of different levels of landslide susceptibility, with 79.41% and 13.67% of the validating field survey landslides falling in the Very High and High zones, respectively, mainly distributed in the south and southeast of the catchment. It showed that MIV model can tackle the problem of “no data in subclass” well, generate the true information value and show real running trend, which performs well in showing the relationship between predisposing factors and landslide occurrence and can be used for preliminary landslide susceptibility assessment in the study area.
Qianqian Wang; Dongchuan Wang; Yong Huang; Zhiheng Wang; Lihui Zhang; Qiaozhen Guo; Wei Chen; Wengang Chen; Mengqin Sang. Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment. Sustainability 2015, 7, 16653 -16669.
AMA StyleQianqian Wang, Dongchuan Wang, Yong Huang, Zhiheng Wang, Lihui Zhang, Qiaozhen Guo, Wei Chen, Wengang Chen, Mengqin Sang. Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment. Sustainability. 2015; 7 (12):16653-16669.
Chicago/Turabian StyleQianqian Wang; Dongchuan Wang; Yong Huang; Zhiheng Wang; Lihui Zhang; Qiaozhen Guo; Wei Chen; Wengang Chen; Mengqin Sang. 2015. "Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment." Sustainability 7, no. 12: 16653-16669.