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中尼交通廊道1:25万地质灾害危险性评估系列图件(2023-2024)

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国家青藏高原科学数据中心2025-03-31 更新2025-04-05 收录
下载链接:
https://data.tpdc.ac.cn/zh-hans/data/557a1d13-ef52-459b-bd7f-4303d7fa2f7d
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资源简介:
本数据含中尼交通廊道崩塌滑坡危险性评估图(全域)和中尼交通廊道崩塌滑坡危险性评估图(公路沿线),比例尺为1:25万。全域采用因子叠加的方法计算评估;公路沿线则基于中尼廊道崩塌滑坡分布数据及孕灾背景数据,采用人工神经网络方法,进行建模,获得崩塌滑坡的高易发地貌单元;进而利用Flow-R模型对不稳定单元运动轨迹进行计算,获得中尼廊道崩塌滑坡的危险区。主图中分别选取A和B两个典型区进行展示。危险性评估数据以tiff文件的形式存储,结构类型栅格数据。Hazard.tif:公路沿线崩塌滑坡危险性;lshazard:全域崩塌滑坡危险性;city.shp:城市;county.shp:县城;boundary.shp:研究区边界;river.shp:河流;road.shp:所有等级公路;Groad.shp:国道。

This dataset contains two collapse and landslide hazard assessment maps for the China-Nepal transportation corridor: one covering the full domain and the other along the highway, both with a scale of 1:250,000. For the full-domain assessment, the factor superposition method was utilized for calculation. For the highway-aligned part, based on the distribution data of collapse and landslide along the China-Nepal corridor and disaster-inducing background data, an artificial neural network (ANN) was adopted to build the model and identify geomorphic units with high susceptibility to collapse and landslide. Subsequently, the Flow-R model was applied to calculate the movement trajectories of unstable units, thereby obtaining the hazard zones of collapse and landslide along the China-Nepal transportation corridor. Two typical areas, A and B, were selected from the main map for demonstration. All hazard assessment data are stored in TIFF format as raster data. The specific files are described as follows: `Hazard.tif`: Hazard level of collapse and landslide along the highway; `lshazard`: Hazard level of collapse and landslide for the full domain; `city.shp`: Shapefile of urban areas; `county.shp`: Shapefile of county seats; `boundary.shp`: Shapefile of the study area boundary; `river.shp`: Shapefile of rivers; `road.shp`: Shapefile of highways of all grades; `Groad.shp`: Shapefile of national highways.
提供机构:
张建强,张崇磊
创建时间:
2024-09-11
搜集汇总
数据集介绍
main_image_url
背景与挑战
背景概述
该数据集是中尼交通廊道1:25万地质灾害危险性评估系列图件,覆盖2023-2024年,包含全域和公路沿线崩塌滑坡危险性评估,全域采用因子叠加方法,公路沿线结合人工神经网络和Flow-R模型进行建模。数据以栅格格式存储,空间分辨率为10m-100m,用于地质灾害风险分析,适用于地理信息系统软件。
以上内容由遇见数据集搜集并总结生成
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