Based on the disaster records during 2008-2020 in Qinghai province,the disaster index is used to study the spatial and temporal distribution characteristics of flood disasters,and high-risk areas are identified.Additionally,a flood disaster prediction model is constructed by machine learning algorithms utilizing the multi-source fusion CLDAS precipitation data from 2017 to 2020,and the disaster-causing rainfall threshold of high-risk area is calculated.The findings indicate that:(1)The highest number of flood disasters,sum to 98,occurred in 2018,while the lowest number,sum to 16,occurred in 2014.The most devastating floods occur in July and August.Based on the annual mean number of disasters in Qinghai,Hainan-eastern Haixi prefecture is the high-risk area of flood disasters,and based on the annual average disaster index,Haidong-Xining is another high-risk area.(2)The 1,2,and 24 h rain intensity of CLDAS data are significant parameters for disasters prediction using a variety of machine learning techniques.The precipitation threshold of Hainan and the eastern part of Haixi prefecture is that the maximum rain intensity of 1 h or 2 h reaches 6.8 mm,or that of 24 h reaches 11.1 mm,while the threshold of Haidong-Xining and nearby areas is that the maximum rain intensity of 1 h or 2 h reaches 13 mm,or that of 24 h reaches 18.2 mm.
为让"慢游"用户合理安排旅游日程与多目标之间最短路线,发展景点当地旅游业,文章介绍了使用HTML5语言设计并实现一款Android与IOS系统兼容的通过后期架构封装成Web App软件包进行发布的手机App.该软件结合HTML5与Web App的优势,融合WebGIS移动开发技术,为喜好"慢游"旅游方式的人群提供了有效实用的帮助.
在我国人民生活日益富裕的社会背景下,人们对旅游提出了更高的要求,如何有效地利用智能技术和科技手段,满足人们的旅游舒适感及慢生活理念,是发展慢游旅游中亟待解决的问题.基于此,旨在运用LBS定位服务技术、3d Max技术,在3S理论背景下进行慢游旅游平台的开发.产品基于市场旅游APP基本功能,加入自定义慢游服务,致力于探索未知旅游地,从而为中老年人群及其他享受慢节奏旅游的人群提供专业化、可视化、高品质的旅游服务.
