This data is the disturbance disaster data of 1:250000 major projects in the Qinghai Tibet Plateau. For the scope of disaster interpretation, line engineering (national highway, high-speed, railway and Power Grid Engineering) and hydropower engineering are bounded by the first watershed on both sides of the project; Mine, oilfield and port projects are bounded by 1km away from the project. Engineering disturbance disasters can be divided into two categories: ① landslide, collapse and debris flow disasters induced by engineering construction; ② For natural disasters that may affect the project, it is stipulated that all natural disasters within the above interpretation scope belong to category ② engineering disturbance disasters. The data includes the location, length, width, height difference, distribution elevation, genetic type, inducing factors, occurrence time, lithology and other elements of landslide, disaster related projects and project construction years. Based on Google Earth image and 1:500000 geological diagram, 6176 disaster points were interpreted; Google Earth is mainly used for disturbance disaster interpretation, and combined with field investigation to verify the interpretation results, ArcGIS is used to generate disaster distribution map; The data comes from Google Earth high-resolution images, with high accuracy of original data. In the process of generating disaster files, the interpretation specifications are strictly followed, and special personnel are assigned to review, so the data quality is reliable; Based on the collected data, the disaster risk analysis of the study area can be carried out to provide theoretical guidance for the smooth operation of the built projects and the construction of the line projects not built / under construction.
QI Shengwen
Based on GRACE Level-1b satellite gravity data, a time series of mass change over Greenland for the period 2002 to 2016, with a spatial resolution of 1 degree × 1 degree and a time resolution of one month was developed by the satellite gravity team led by Professor Shen Yunzhong from Tongji University. The reference time of this time series is the mean time span between January 2004 and December 2009. During data processing, ICE5G model was used to reduce the effect of GIA, and the contribution of GAD was added back by using AOD1B RL06 from GFZ
SHEN Yunzhong
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