Landslide inventory plays an important role in recording landslide events and showing their temporal-spatial distribution. This paper describes the development, visualization, and analysis of a China's Landslide I...Landslide inventory plays an important role in recording landslide events and showing their temporal-spatial distribution. This paper describes the development, visualization, and analysis of a China's Landslide Inventory Database(Cs LID) by utilizing Google's public cloud computing platform. Firstly, Cs LID(Landslide Inventory Database) compiles a total of 1221 historical landslide events spanning the years 1949-2011 from relevant data sources. Secondly, the Cs LID is further broken down into six zones for characterizing landslide cause-effect, spatiotemporal distribution, fatalities, and socioeconomic impacts based on the geological environment and terrain. The results show that among all the six zones, zone V, located in Qinba and Southwest Mountainous Area is the most active landslide hotspot with the highest landslide hazard in China. Additionally, the Google public cloud computing platform enables the Cs LID to be easily accessible, visually interactive, and with the capability of allowing new data input to dynamically augment the database. This work developed a cyber-landslide inventory and used it to analyze the landslide temporal-spatial distribution in China.展开更多
基金funded by National Natural Science Foundation (Grant No. 41501458)National Natural Science Foundation (Grant No. 41201380)+4 种基金National Basic Research Program of China: (Grant No. 2013CB733204)Key Laboratory of Mining Spatial Information Technology of NASMG (KLM201309)Science Program of Shanghai Normal University (SK201525)sponsored by Shanghai Gaofeng & Gaoyuan Project for University Academic Program Development, project 2013LASW-A09, project SKHL1310the Center of Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai, China
文摘Landslide inventory plays an important role in recording landslide events and showing their temporal-spatial distribution. This paper describes the development, visualization, and analysis of a China's Landslide Inventory Database(Cs LID) by utilizing Google's public cloud computing platform. Firstly, Cs LID(Landslide Inventory Database) compiles a total of 1221 historical landslide events spanning the years 1949-2011 from relevant data sources. Secondly, the Cs LID is further broken down into six zones for characterizing landslide cause-effect, spatiotemporal distribution, fatalities, and socioeconomic impacts based on the geological environment and terrain. The results show that among all the six zones, zone V, located in Qinba and Southwest Mountainous Area is the most active landslide hotspot with the highest landslide hazard in China. Additionally, the Google public cloud computing platform enables the Cs LID to be easily accessible, visually interactive, and with the capability of allowing new data input to dynamically augment the database. This work developed a cyber-landslide inventory and used it to analyze the landslide temporal-spatial distribution in China.
