排序方式： 共有2条查询结果，搜索用时 15 毫秒
1
1.
Brijendra K. Mishra Dipanjan Bhattacharjee Anupam Chattopadhyay Ganesh Prusty 《Natural Hazards》2018,92(2):673-697
The purpose of this study is to analyze and characterize recent landslide events in the Larji–Kullu Tectonic Window (LKTW), and to establish a relationship between the tectonic and lithologic characters of the terrain and the landslides activity. Using multispectral satellite image analysis with selected field investigation, a landslide occurrence database has been generated for the period between 1984 and 2015. To decipher the accelerated occurrences of landslides in the region, an integrated study is undertaken in the Kullu (also known as Kulu) valley of Beas River basin within the LKTW complex, to analyze the litho-structural and terrain slope interactions using morpho-tectonic parameters such as Topographic/Bedding Plane Interaction Angle (TOBIA) index, terrain surface roughness index and lithological competency analysis. A prominent clustering of landslides is observed in the north of Sainj River, contained within the tectonic window. Major sites of landslides are found to be located in the intensely fractured Manikaran Quartzite occurring within the core of the LKTW. The landslides are mostly associated with southern and southwestern-facing slopes and activations are pronounced in the ‘Orthoclinal’ slope class with gradient of 37°–48°. Thematic maps, e.g., geological, structural, geomorphological, slope and slope-aspect maps are generated and considered together to understand the morpho-tectonic scenario of the tectonic window. Observations from the above-stated thematic maps along with the occurrences of moderate magnitude earthquake epicenters helped to infer neotectonic movements along the Sainj River fault. Tectonic upliftment of the northern bank of the Sainj River along with increased precipitation through decades has resulted in recurrent landslides within the LKTW. 相似文献
2.
Evaluation of NDWI and MNDWI for assessment of waterlogging by integrating digital elevation model and groundwater level 总被引：1，自引：0，他引：1
Accurate information on the extent of waterlogging is required for flood prediction, monitoring, relief and preventive measures. The rule-based classification algorithms were used for differentiating waterlogged areas from other ground features using Resourcesat-2 AWiFS satellite imagery (Indian Remote Sensing Satellite with spatial resolution of 56 m). Two spectral indices normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) were used for extracting waterlogged areas in Sri Muktsar Sahib district of Punjab, India. These indices extracted the waterlogged areas (cropped areas inundated with water) but the water features were less enhanced in the NDWI-derived image (when compared with MNDWI-derived image) due to negative values of NDWI and, mixing of water with built up features. The water features were more enhanced with MNDWI and the values of MNDWI were positive for water features mixed with vegetation. The overall accuracy of waterlogged areas extracted from the MNDWI image was 96.9% with the Kappa coefficient of 0.89. The digital elevation model (DEM) was extracted from ASTER-GDEM. The relationships among depth to the water table recorded before the incessant rain in the region, DEM and classified MNDWI images explained the differences in the extent of waterlogging in various directions of the study area. These results suggest that MNDWI can be used to better delineate water features mixed with vegetation compared to NDWI. 相似文献
1