For landslide surface monitoring, the Global Navigation Satellite System (GNSS) has been widely used in landslides due to its real-time, all-weather, high-precision, simple operation and a high degree of automation. However, these data are not intuitive and visual data will be more interesting for users without professional knowledge. At the same time, the conventional data representation method is in the form of curves or tables for three-dimensional data of landslide surface deformation collected by GNSS. To make the data more intuitive, clear and valuable, it is easier for people to understand the process of landslide deformation and finally realize the visualization of decision. Here we show that a polar coordinate system rather than a Cartesian coordinate system is adopted to visualize the horizontal data, which not only shows the horizontal deformation of the landslide, but also easily knows the direction of the landslide deformation. The vertical data is in the form of slices rather than curves, which not only shows the deformation of the landslide surface, but also shows the process of the vertical change of the landslide in terms of the time series. Single GNSS monitoring station is composed of a GNSS receiver, GNSS antenna with random, a solar power unit, and a network transmission module. The system can be powered by the solar energy system, which can realize 24-hour unmanned operation, 7 days a week. The system can receive satellite signals in real-time process and analyze deformation data, then it automatically broadcast early warning information. Our results demonstrate that it is a better choice that the thematic map of Geographic Information System (GIS) is a technical system for collecting, storing, managing, calculating, analyzing and displaying geographic data supported by computer hardware and software systems. Here we show that the multi-dimensional properties of deformation monitoring and multiple expressions of the attribute values are displayed synchronously in order to obtain more useful information from the visual graphics.

Earthquake, flood, human activity, and rainfall are some of the trigger factors leading to landslides. Landslide monitoring data analysis indicates the deformation characteristics of landslides and helps to reduce the threat of landslide disasters. There are monitoring methods that enable efficient acquisition of real-time data to facilitate comprehensive research on landslides. However, it is challenging to analyze large amounts of monitoring data with problems like missing data and outlier data during data collection and transfer. These problems also hinder practical analysis and determination concerning the uncertain monitoring data. This work analyzes and processes the deformation characteristics of a rainfall-induced rotational landslide based on exploratory data analysis techniques. First, we found that the moving average denoising method is better than the polynomial fitting method for the repair and fitting of monitoring data. Besides, the exploratory data analysis of the Global Navigation Satellite System (GNSS) monitoring data reveals that the distribution of GNSS monitoring points has a positive correlation with the deformational characteristics of a rotational landslide. Our findings in the subsequent case study indicate that rainfalls are the primary trigger of the Zhutoushan landslide, Jiangsu Province, China. Therefore, this method provides support for the analysis of rotational landslides and more useful landslide monitoring information.

Abstract. Due to the complex geological structure of landslides, the installation of a monitoring network could be useful for a variety of scopes studying the possible evolution of a landslide for early warning, and the occurrence of disasters of different types landslides is different not only in the form of deformation, but also in the trigger factor. In the process of landslide monitoring, due to equipment failure and external factors, data loss or abnormal are inevitable. In this paper, through the processing and analysis of the monitoring data of the Zhutoushan landslide, the landslide is rotational landslide which is caused by the rainfall. The box plot is used to detect outliers, and the polynomial fitting function and the moving average denoise method are compared to repair the data, and the latter is better. Through the exploratory analysis of GNSS data, the correlation between monitoring points at different locations is found, which provides a basis for the identification of landslide types.

It introduces the basic frame of the geology space of cities,represents that the logical divide to space solid in the design of database.It discusses the stratification design and the attribute design of based on the geology space database based on Geodatabase,to implement the integration and shearing of the massage resource of cities.

在地籍测量中,传统的测量手段已经很难满足实际工作的需要,实现地籍测量的无纸化、信息化、自动化与数字化是其发展的必然趋势。而数字测图在地籍测量中的广泛应用掀起了一场深刻的变革,加之新型的测量设备——RTK与自动化全站仪的出现给测绘领域提供了高效益高精度的测量手段和方法。探讨的重点是应用现代测量设备去实现地籍测量中的数字化。

This paper discusses emphatically the method for establishing the map symbol database based on ArcGIS,and expounds in detail of the methods for realizing the point symbol, line symbol and area symbol.