Spatial Forecast of Landslides in Three Gorges Based On Spatial Data Mining
نویسندگان
چکیده
The Three Gorges is a region with a very high landslide distribution density and a concentrated population. In Three Gorges there are often landslide disasters, and the potential risk of landslides is tremendous. In this paper, focusing on Three Gorges, which has a complicated landform, spatial forecasting of landslides is studied by establishing 20 forecast factors (spectra, texture, vegetation coverage, water level of reservoir, slope structure, engineering rock group, elevation, slope, aspect, etc). China-Brazil Earth Resources Satellite (Cbers) images were adopted based on C4.5 decision tree to mine spatial forecast landslide criteria in Guojiaba Town (Zhigui County) in Three Gorges and based on this knowledge, perform intelligent spatial landslide forecasts for Guojiaba Town. All landslides lie in the dangerous and unstable regions, so the forecast result is good. The method proposed in the paper is compared with seven other methods: IsoData, K-Means, Mahalanobis Distance, Maximum Likelihood, Minimum Distance, Parallelepiped and Information Content Model. The experimental results show that the method proposed in this paper has a high forecast precision, noticeably higher than that of the other seven methods.
منابع مشابه
Landslide Susceptibility Analysis Based on Data Field
The Three Gorges are the areas in which the geological disasters are very serious. There often happen great landslide disasters, which brings tremendous threat to normal running of the Three Gorge Dam and the properties and lives of the residents in the reservoir. So landslide susceptibility analysis is an important task of prevention and cure of landslides in the Three Gorges. In this paper, l...
متن کاملStudy on displacement prediction of landslide based on neural network
In recent years, the economic losses caused by landslides were as high as several billion dollars. Therefore, the study of landslide risk has become a hot topic today. Landslide displacement prediction is a highly nonlinear and extremely complex issue. In most cases, it is difficult to use mathematical models to describe the process clearly. Data mining technology, which uncovers the hidden dat...
متن کاملTime Series Analysis of Very Slow Landslides in the Three Gorges Region through Small Baseline SAR Offset Tracking
Sub-pixel offset tracking has been used in various applications, including measurements of glacier movement, earthquakes, landslides, etc., as a complementary method to time series InSAR. In this work, we explore the use of a small baseline subset (SBAS) Offset Tracking approach to monitor very slow landslides with centimetre-level annual displacement rate, and in challenging areas characterize...
متن کاملAssessment of uncertainty for coal quality-tonnage curves through minimum spatial cross-correlation simulation
Coal quality-tonnage curves are helpful tools in optimum mine planning and can be estimated using geostatistical simulation methods. In the presence of spatially cross-correlated variables, traditional co-simulation methods are impractical and time consuming. This paper investigates a factor simulation approach based on minimization of spatial cross-correlations with the objective of modeling s...
متن کاملDeveloping a Model Based on Geospatial Information Systems (GIS) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for Providing the Spatial Distribution Map of Landslide Risk. Case Study: Alborz Province
Landslide is one of these natural hazards which causes a great amount of financial and human damage annually allover the world. Accordingly, identification of areas with landslide threat for implementation of preventive measures in order to confront against the instability of hillsides for reduction of potential threats and related risks is very important. In this research a new method for clas...
متن کامل