Based on the classic filter of progressive triangulated irregular network（TIN） densification, an improved filter is proposed in this paper. In this method, we divide ground points into grids with certain size and se...Based on the classic filter of progressive triangulated irregular network（TIN） densification, an improved filter is proposed in this paper. In this method, we divide ground points into grids with certain size and select the lowest points in the grids to reconstruct TIN in the process of iteration. Compared with the classic filter of progressive TIN densification（PTD）, the improved method can filter out attached objects, avoid the interference of low objects and obtain relatively smooth bare-earth. In addition, this proposed filter can reduce memory requirements and be more efficient in processing huge data volume. The experimental results show that the filtering accuracy and efficiency of this method is higher than that of the PTD method.展开更多
A new algorithm to automatically extract drainage networks and catchments based on triangulation irregular networks(TINs) digital elevation model(DEM) was developed. The flow direction in this approach is determined b...A new algorithm to automatically extract drainage networks and catchments based on triangulation irregular networks(TINs) digital elevation model(DEM) was developed. The flow direction in this approach is determined by computing the spatial gradient of triangle and triangle edges. Outflow edge was defined by comparing the contribution area that is separated by the steepest descent of the triangle. Local channels were then tracked to build drainage networks. Both triangle edges and facets were considered to construct flow path. The algorithm has been tested in the site for Hawaiian Island of Kaho'olawe, and the results were compared with those calculated by ARCGIS as well as terrain map. The reported algorithm has been proved to be a reliable approach with high efficiency to generate well-connected and coherent drainage networks.展开更多
Digital Elevation Models(DEMs)play a crucial role in civil and environmental applications,such as hydrologic and geologic analyses,hazard monitoring,natural resources exploration,etc.Generally,DEMs can be generated fr...Digital Elevation Models(DEMs)play a crucial role in civil and environmental applications,such as hydrologic and geologic analyses,hazard monitoring,natural resources exploration,etc.Generally,DEMs can be generated from various data sources,such as ground surveys,photogrammetric stereo methods,satellite images,laser scanning,and digitized contour lines.Compared with other data sources,contour lines are still the cheapest and more common data source becausethey cover all areas,at different scales,in most countries.Although there are different algorithms and technologies for interpolation in between contour lines,DEMs extracted solely from contours still suffer from poor terrain quality representation,which in turn negatively affects the quality of analytical applications results.In this paper,an approach for improving the digital terrain modeling based on contour line densification and Delaunay triangulation is presented to acquire a more suitable DEM for hydrographic modeling and its applications.The proposed methodology was tested using a variety of terrain patterns in terms of intensity:hilly,undulated,and plain(1:25,000 topographic map,5 m contour interval).The precision of the extracted GRID model increases as the number of added contours increases.Adding four contour lines,the Root Mean Square Error(RMSE)of examining points were 0.26 m,0.29 m,and 0.05 m for hilly,undulated,and plain samples,respectively,and the Mean Absolute Error(MAE)were 0.50 m,0.48 m,and 0.17 m.The convergence probabilities between extracted and original flow lines for the same regions were 96.91%,94.93%,and 84.03%.Applying the methodology,experimental results indicate that the developed approach provides a significant advantage in terrain modeling enhancement,generates DEMs smoothly and effectively from contours,mitigates problems and reduces uncertainties.展开更多
基金Supported by the National Natural Science Foundation of China(41301519)
文摘Based on the classic filter of progressive triangulated irregular network（TIN） densification, an improved filter is proposed in this paper. In this method, we divide ground points into grids with certain size and select the lowest points in the grids to reconstruct TIN in the process of iteration. Compared with the classic filter of progressive TIN densification（PTD）, the improved method can filter out attached objects, avoid the interference of low objects and obtain relatively smooth bare-earth. In addition, this proposed filter can reduce memory requirements and be more efficient in processing huge data volume. The experimental results show that the filtering accuracy and efficiency of this method is higher than that of the PTD method.
基金the National Basic Research Program(973)of China(No.2007CB714103)
文摘A new algorithm to automatically extract drainage networks and catchments based on triangulation irregular networks(TINs) digital elevation model(DEM) was developed. The flow direction in this approach is determined by computing the spatial gradient of triangle and triangle edges. Outflow edge was defined by comparing the contribution area that is separated by the steepest descent of the triangle. Local channels were then tracked to build drainage networks. Both triangle edges and facets were considered to construct flow path. The algorithm has been tested in the site for Hawaiian Island of Kaho'olawe, and the results were compared with those calculated by ARCGIS as well as terrain map. The reported algorithm has been proved to be a reliable approach with high efficiency to generate well-connected and coherent drainage networks.
基金funded by the Deanship of Scientific Research(DSR),King Abdulaziz University,Jeddah[Grant No.D 1441-298-137].
文摘Digital Elevation Models(DEMs)play a crucial role in civil and environmental applications,such as hydrologic and geologic analyses,hazard monitoring,natural resources exploration,etc.Generally,DEMs can be generated from various data sources,such as ground surveys,photogrammetric stereo methods,satellite images,laser scanning,and digitized contour lines.Compared with other data sources,contour lines are still the cheapest and more common data source becausethey cover all areas,at different scales,in most countries.Although there are different algorithms and technologies for interpolation in between contour lines,DEMs extracted solely from contours still suffer from poor terrain quality representation,which in turn negatively affects the quality of analytical applications results.In this paper,an approach for improving the digital terrain modeling based on contour line densification and Delaunay triangulation is presented to acquire a more suitable DEM for hydrographic modeling and its applications.The proposed methodology was tested using a variety of terrain patterns in terms of intensity:hilly,undulated,and plain(1:25,000 topographic map,5 m contour interval).The precision of the extracted GRID model increases as the number of added contours increases.Adding four contour lines,the Root Mean Square Error(RMSE)of examining points were 0.26 m,0.29 m,and 0.05 m for hilly,undulated,and plain samples,respectively,and the Mean Absolute Error(MAE)were 0.50 m,0.48 m,and 0.17 m.The convergence probabilities between extracted and original flow lines for the same regions were 96.91%,94.93%,and 84.03%.Applying the methodology,experimental results indicate that the developed approach provides a significant advantage in terrain modeling enhancement,generates DEMs smoothly and effectively from contours,mitigates problems and reduces uncertainties.
