The Segment Tracing Algorithm (STA) is one of the effective methods for lineament extraction using DEM (Digital Elevation Model). However, the lineaments extracted by STA are the limited linear structures on the shadedrelief image derived from DEM and are not directly related with the topographical characteristics. In this study, we developed a lineaments extraction method using the line segments discriminated by the topographical characteristics of DEM based on the principle of STA in order to more directly extract lineaments related faults and flexures. The lineament extraction consists of the following five steps: ① calculation of the unit normal vector of topographic surface in each cell of DEM, ② determination of the direction of high continuity with less change of the unit normal vector direction, ③ extraction of the line segments, ④ connection of the line segments, and ⑤ integration of the lines. As a case study, the developed method has been demonstrated for the Rokko Mountains area, and it could be confirmed that there are lineaments coincided with known active faults. The effects of parameters such as size of small window on the extraction of lineaments have been discussed.

In recent years, due to climate change, heavy rainfall has occurred frequently, and the damage caused by inundation has increased. However, the soundness of the levee is done by the visual inspection while experts walk. Therefore, it is evaluated depending on the skills and experience of the experts. There has been a need for a method that can monitor the outer shape of the levee in detail in normal times and after flooding, and to conduct quantitative evaluation for taking measures immediately if abnormalities such as deformation are found. Mobile Mapping System (MMS), which is equipped with a laser scanner on a vehicle, has attracted attention as a method that can quickly carry out high-precision surveying. When the survey is conducted by using MMS that travels on the levee crown, a dead angle of laser irradiation occurs. It is possible to detect the subsidence of the levee crown with high accuracy, but it is not possible to detect where it is necessary to take measures in the whole levee including the slope surface by using MMS survey. In this paper, we clarified what kind of problem the dead angle of the laser light leads to, and discussed the advantages of acquiring 3D data for grasping the topography of the levee by irradiating the laser from a high position. We showed the relation between the laser irradiation angle and the traveling speed of the vehicle and the surveying accuracy, and considered the position to install the laser scanner device to acquire the 3D data up to the slope toe area. We also verified the effectiveness of the laser surveying which irradiates from the 5.5m height. In comparison with the conventional laser surveying by vehicle travel, it was demonstrated that the method we considered was efficient as a surveying work and detected a detailed deformation on the slope surface because it provided high density laser point clouds. Since the heavy rainfall of short duration will increase in the future, it is expected that the results of this study are considered to be useful as a method for efficiently grasping the topographical features of the levee.

A Drag & Drop Map (abbreviation: DD Map) specification is formulated as an innovative and efficient method for selecting, moving and using a map data on the web. Using the DD Map, map layer data is exchanged between websites using HTML5 drag & drop Application Programming Interface (API). The map data to be transferred is in a JavaScript Object Notification (JSON) format as a JSON text, a JSON file or a link to a JSON file. By using the DD Map, simple and intuitive map display and rapid utilization of new map data can be implemented. Furthermore, the role of the DD Map icon provider can be proposed and map layer data set with free ideas can be created.