The classical methods of two dimensional remote change detection are no longer working effectively in three dimensional change scenes

such as geographical disaster areas. Vegetation information extraction also generally requires near-infrared bands.Visible light images from 2010 and 2011 in Yingxiu are selected and vegetation and three dimensional terrain change detection methods are presented under conditions without near-infrared bands. The Digital Elevation Model（ DEM） and Digital Ortho Map（ DOM） in two periods are generated by DPGrid. Then

vegetation changes in DOM are detected by the CIE Lab and Otsu a lgorithms. This study proposes an adaptive threshold method of three dimensional change detection based on the theory of probability and statistics. After censored samples are selected

the threshold range of elevation change is obtained by the 3σ rule of Gaussian distribution. High risk areas of geological disasters are extracted under the condition of high probability confidence r egions. Finally

the corresponding earthwork change quantities are estimated by discretized integral. Vegetation changes in two p eriods are successfully detected

and change areas are located on the edge of the canyon in floodplain. This study determines the elevation change threshold range of three dimensional change detection by calculation. The threshold values of elevation decrease and increase are 2. 73 m and 2. 43 m

respectively. Landslide high risk areas and two debris flow accumulation areas located along Minjiang River are successfully detected. The earthwork quantitative change of 10 landslide high risk areas and two debris flow a ccumulation areas are estimated. Results show that the proposed method is effective

feasible

and practical. This study not only elevates conventional two dimensional change detection into three dimensional space but also quantitatively estimates three dimensional terrain changes. Therefore

the proposed method can be applied to monitor dynamic remote sensing and evaluate geological disasters. Even without near-infrared band

the proposed method can still successfully detect vegetation changes. In this study

s tatistical methods are used to determine the elevation change threshold. In allusion to landslide disaster

elevation-significant r eduction risk areas are extracted. The distribution of risk areas is consistent with other research results. With discretized integral calculation

this study explores the earthwork quantity estimation method based on DEM. This method breaks the assumption that the surface is continuous and gradual

and can quickly estimate earthwork quantity by DEM. This method also incurs some errors caused by limited data source. The quantitative analysis for the uncertainty of the error is the main research target in the future.The two DEMs are generated separately in two periods; thus

they have their own errors in three dimensional change detection. Errors may also be amplified in error propagation. In future studies

the geographic information system data from previous periods will be used as control information to generate a DEM for a new period. Doing so would reduce relative errors. A domain-specific model will be also used to analyze and evaluate geological disasters.