5-9 Digital Plotting 5-9-1 Plotting Work Flow The plotting work was conducted as in the following chart. Preparation of Raster Images of Photo Preparation of Aerial Triangulation Interior Orientation Importing the results of Aerial Triangulation Inspection of Models Automatic DTM Manual drawing of Generation contour lines Preparation of Field Identification results DTM Editing Planimetric Features (Road, River and Other Linear Objects) TIN（Contour line Planimetric Features (Buildings, Villages) generation） Contour Line Editing Planimetric Features (Vegetation and oth- ers) Consolidation of Contour lines and Planimetric Features Quality Management (Inspection)) Figure 5-17 Plotting Work Flow 5-9-2 Equipment Used Several digital phtogrammetric systems were used for mapping process. The three types of system were mainly used together with AutoCAD and MicroStation. They were: DiAp (ISM); Summit Evolution (DAT/AM); and Socet Set (LEICA_HERAVA). 132 Photo 5-6 Plotting Work with Digital Plotting System 5-9-3 Plotting Process (1) Preparation The followings were prepared and confirmed before plotting work. 1) Scanned image of aerial photography 2) Preparation of a camera-file using the calibration data of a camera used. 3) Aerial-triangulation data 4) Acquisition standard classification table 5) Line library and symbol library corresponding to assignment codes 6) Field-identification photographs (2) Data Setting Data required for plotting are imported to a digital photogrammetric system. 1) Scanned images 2) Camera files 3) Aerial-triangulation data 4) Line library/symbol library (3) Interior orientation The minimum number of fiducial marks of the photographs was observed to determine the relationship between the calibrated fiducial coordinates and corresponding raster co- ordinates on the photograph images after project-file preparation. The residuals of ob- servation of fiducial marks were to be less than 30 microns by a Helmert's transforma- tion. (4) Preparation of Models (relative and absolute orientation) Aerial-triangulation data were imported after finishing the interior orientation, and cal- culation of parameter of each photographs were performed. A model and photograph images were associated after calculation, and a model was created. (5) Inspection of Model After model preparation, in order to verify the accuracy of aerial triangulation, the fol- lowing inspection was performed. The locations of inspection are four corners and a center for an adjusted block. Others are selectively conducted when it was necessary. At locations such as ocean or large lakes where a model becomes incomplete, the in- spection was to be conducted carefully. The following inspection was performed. 133 1) Vertical parallax 2) Accuracy of horizontal locations and height 3) Connection discrepancy with an adjacent model 5-9-4 Plotting for Planimetric Features Plotting work for planimetric feature such as road, river, lake, building, vegetation and other ground objects were acquired referring to the field verification results by three di- mensional model of the air photograph. When existing digital data were available from existing information, the data were imported beforehand and inspected during plotting. (1) Criteria of data acquisition Data acquisition was performed according to the map specifications and their applica- tion rules before plotting. (2) Order of data acquisition for planimetric feature Generally data of planimetric feature were acquired by the following sequence. 1) Frame data such as road, river, lake. 2) Building, structure, various objects, power transmission line, various pipelines, distortion places such as cliff 3) Vegetation (3) Photographic interpretation The items that were not included in field identification were acquired by photo- inter- pretation. Photographic interpretation was carried out as an interpreter identifies com- ponents, such as configuration, color, pattern, shadow of an object. The existing maps were also useful as a reference material for the photo-interpretation. If there is pre- liminary knowledge, such as characteristics of the region, the interpretation accuracy will be improved further. Moreover, it becomes effective also to inspect possible er- rors in field identification. (4) Details of plotting 1) Road i) The road data was acquired referring to the results obtained by field identification, plotting interpretation, and the existing maps. ii) For roads that were found in photo-interpretation but not in the results of field identification or in existing maps, the interpreted results were used as the road data. iii) Built-up areas and densely developed areas were extracted by the density of houses. iv) Road Bridges and large fords were extracted onto roads. Data acquired from GPS were used for road bridges and fords (small). Drainage System i) Shore lines were extracted as in the photographs taken. ii) Water bodies were extracted by photo-interpretation, referring to the results ob- tained by field-identification. When acquisition was difficult, data from existing maps were used. iii) Since locations of wells, reservoir, and spring water locations were hard to identify by plotting, GPS data and data from existing maps were used. iv) Coast lines, island lines, lake lines, lakeside lake, etc. were to be plotted at the same height. Villages, buildings, etc. 134 i) Since photo-interpretation had its limits identifying particular built-up area, inhab- itable areas, occupied residential areas, and illegal settlements, field completion was needed. ii) For large buildings, actual shapes were extracted and for small buildings in built-up area they were acquired as generalized area. iii) Small ground objects such as churches, schools, hospital, etc. were acquired refer- ring to coordinates of GPS in the field-identification. Objects identified on exist- ing maps were extracted in the plotting process and were confirmed in the supple- mental survey. Landform features and others i) Cliffs and ravines were to be carefully selected on channels. ii) The transformation ground was to be acquired as contour lines as much as possible. Depending on a topography, map symbol would be used. iii) To avoid accidental omission of contour lines, elevations of summits, depressions and peaks were continuously followed. When necessary, spot elevations were acquired. Symbols on planimetric features i) Lighthouses, windmills, monuments, substations, sport recreation facilities, ceme- tery, etc. are acquired referring to coordinates of GPS obtained by the field-identification. When objects could be identified on existing maps, they were to be confirmed during the plotting. ii) Mining areas, quarries, and mines were acquired using existing maps and plotting interpretation. Vegetation i) Plotting interpretation itself was not sufficient; therefore, field identification pho- tographs and existing maps were used for data acquisition. ii) Plantations, and isolated trees were acquired from the field-identification maps. When objects could be identified on existing maps, they were to be confirmed dur- ing the supplemental survey. (5) Plotting inspection The visual inspection of the plotting data was conducted by placing Ortho-photographs as the background of the plotting data. Main checkpoints are as follows: 1) Codes other than assigned and errors of codes; 2) Overlap of buildings; 3) Extrusion of a building to a road; 4) Conflict between edges of roads, edges of bridges and roads, walls and others that are to be overlapped; 5) Disconnection, dangle, etc.; 6) Short vector; 7) Consistency with field-identification photographs; 8) Conflict with a flow direction and contour lines if a contour line crosses a road and river; and 9) Conflict among contour line, spot elevation and control point. (6) Data type and format The used data types were only Point, Line, Polyline or Single line text. The final data 135 format is dxf ASCII format version 12. A sample of the planimetric feature data is shown in Figure 5-18. Planimetric feature 1 Planimetric feature 2 Figure 5-18 Sample of Planimetric Feature 5-9-5 Preparation of Contour Lines (1) Contour Delineation Originally, the methodology of contour delineation was planned to use an automatic Digital Terrain Model (DTM) module in digital plotting systems. However, it was found big discrepancy of automatic DTM and actual ground height in some forest area. In the case of big discrepancy, more than 5m, the accuracy of maps was expected to be- come to low accuracy than specifications. Therefore, a manual contour delineation method was used with three-dimensional view. In some area where there is no vegeta- tion, Automatic DTM and TIN model method were useful sometimes. Automatic DTM and automatic contour lines created by TIN model were checked by 3D model visually and edited, if necessary. (2) Spot Elevations Placement of spot elevations is as follows: 1) Main summits of mountains; 2) Main junctions of road; cols to which a road passes; other main cols. 3) Valley front, junction of river, dry riverbed; 4) Critical point of the main ramps; 5) Point representing a general plane of a location; 6) The deepest part of a depression that is identifiable; and 7) A point required in order to clarify landform. A sample of the plotted data is shown in Figure 5-19. 136 Manual Method DTM method Figure 5-19 Sample of CAD Data Extracted by Digital Plotting System (3) DEM Generation In this study, TOPOGRID command which is one of function in ArcInfo was used for generating DEM data with the use of contour and spot height data. Its grid space is 20 meters by requesting from INETER. After generating DEM in ArcInfo, the data has been edited in ERDAS IMAGINE for providing constant value to the flat area such as surface of lake and sea . 1. Data preparation 2. DEM generation 3. Display of terrain Contour & Spot height data DEM(ArcInfo grid format) The bird’s-eye view of DEM Figure 5-20 Work Flow of DEM Generation DEM has been generated in consideration of the joint among neighboring map sheets. After joining contour and spot height data of neighboring map sheets, DEM was gener- ated with the use of those data, and was clipped by a map quadrangle data which is 20m (one pixel of DEM) larger than a normal map quadrangle.