Digital Vector Maps Research Articles

Lossless Digital Watermarking Technology for Vector Maps

In ensuring the content of digital vector maps lossless, a high capacity digital watermarking algorithm is proposed based on encoding scheme. According to the structure of TAB file for digital vector maps, the watermark is hidden into the attribute blocks. As each vector object definition reserves redundant space, these information bits cannot be edited and displayed by any map editing tool, the watermark has good concealment. Experimental results show that the algorithm maintaining high capacity and good invisibility, it also can strongly resist various geometric transformations such as cropping, rotation, projection, etc..

Watermarking digital vector map using graph theoretic approach

Similar to any digital dataset, a digital map is also vulnerable to modification, deliberate alteration and copyright violation. A map is a visual representation of a geographical area that is digitally stored in either raster or vector forms. Vector map is preferred over raster for both space optimization and quick processing time. Digest concept used for message authentication is extended to digitally watermark a digital map. The map digest triplet ( , and ) is generated using various features of a digital map, supplier code and customer code. The approach computes two 160-bit hash values using secured hash algorithm (SHA1)and one 128-bit digest using message digest (MD5) algorithm. These two hash values of 160 bit and one digest of 128 bit are then embedded into a sequence of nodes of the map using graph theoretic approach in such a way that any alteration in the map alters the sub-graph. The sub-graph is the watermark. There are three watermarks.

Road effects on habitat richness of the Greek Natura 2000 network

The road network has both positive and negative ecological effects, and understanding these helps identify environmentally preferable solutions for transportation policy and planning. We investigated the relationship between road density and habitat type richness of Greek protected areas. We used digital vector maps of 214 sites included in the Greek Natura 2000 network. We calculated road density for the terrestrial part of each site and correlated it with habitat type richness. Average road density of protected areas (0.377 km/ km2) was significantly lower than the national road density of Greece (0.446 km/km2). We identified 32 sites that were not intersected by roads. These roadless sites were located at mountain tops, at islets, or in remote coastal zones. Overall we found no significant correlation between road density and habitat type richness. We suggest that the effect of road networks on habitat type richness is less apparent at landscapes with long history of human presence, because the landscape (and its habitat diversity) has coevolved with human activities over the past millennia. Our analysis provides a step towards quantifying the effect of road density on the diversity of habitats and consequently on species of conservation interest in international networks of protected areas such as the European Natura 2000 network.

Hiding Information in Vector Layer While Extracting Layers from Raster Data

ABSTRACT A topographic sheet contains information about road, rail, river, etc., of a particular geographical area. This information is used as a channel for hiding secret messages in a layer that is extracted from the topographic sheet through digitization in vector map form. The extraction of layers is carried out either manually or semi-automatically. Manual extraction is done either through tablet or through a process called onscreen digitizing. The onscreen digitizing is used here to hide message simultaneously with the extraction of the vector layer. A message is string of bits. Bit ‘1’ and ‘0’ of a message are coded as node and intermediate point, respectively, in the vector layer. A digital vector map is generated using three basic components: node, intermediate point, and segment. Three tolerance values of dangle, fuzzy, and weed determine the closeness of two nodes and two intermediates point in a segment. An algorithm is developed to hide/extract information in vector map form of a topographic sheet. The process is very useful for sharing contextual intelligence.

Automatic Building Reconstruction with Satellite Images and Digital Maps

This paper introduces an automated method for building height recovery through the integration of high-resolution satellite images and digital vector maps. A cross-correlation matching method along the vertical line locus on the Ikonos images was deployed to recover building heights. The rational function models composed of rational polynomial coefficients were utilized to create a stereopair of the epipolar resampled Ikonos images. Building footprints from the digital maps were used for locating the vertical guideline along the building edges. The digital terrain model (DTM) was generated from the contour layer in the digital maps. The terrain height derived from the DTM at each foot of the buildings was used as the starting location for image matching. At a preset incremental value of height along the vertical guidelines derived from vertical line loci, an evaluation process that is based on the cross-correlation matching of the images was carried out to test if the top of the building has reached where maximum correlation occurs. The accuracy of the reconstructed buildings was evaluated by the comparison with manually digitized 3D building data derived from aerial photographs.

Research on Lossless Digital Watermarking Algorithm on Digital Vector Maps

Lossless digital watermarking algorithm based on attribute information has been presented based on the location information and coordinate information of vertex in vector maps. With the knowledge of data structure and file structure of digital vector maps, its attribute information has been presented in detail and a lossless scheme with zero-bit dynamical extension has been proposed. On the basis of this, space clustering analysis with grid density was used to increase robustness of the scheme.

Digital cameras derived raster image transformation of old map sheets

The main focus of the research is to obtain digitized old map sheets with high geometric accuracy (a few decimeters of error) for Geographical Information Systems, urban planning, surveying engineering and other applications. For this purpose, Portable Digital Camera Raster Image versus Scanner Raster Image is examined regarding their use in reproduction of old map sheets in Digital Vector Map format. Therefore, we focused on coordinate transformations between the raster and the spatial coordinate systems along the research. The transformation methods subjected to this research are the Helmert, Affine, Polynomial transformations and radial basis functions techniques. Accordingly, a case study was performed on the 1/1000 scaled map sheets were the raster images are gathered using a portable digital camera and scanner. The performance of the results obtained by fitting techniques based on radial basis functions namely multiquadrics, natural cubic spline, thin plate spline and third order polynomials gave successful solutions according to this procedure. Root Mean Square error of the Scanner Raster Image for dx differences are 0.180, 0.183, 0.224, and 0.339 m and the Root Mean Square of the dy differences are 0.167, 0.223, 0.240, and 0.379 m, respectively for thin plate spline, natural cubic spline, multiquadrics and third order polynomials models. Similarly, Root Mean Square error of the Portable Digital Camera Raster Image for dx differences are 0.173, 0.176, 0.225, and 0.352 m and the Root Mean Square of the dy differences are 0.196, 0.240, 0.264, and 0.365 m respectively for thin plate spline, natural cubic spline, multiquadrics and third order polynomials models. Key word: Coordinate transformation, digital camera, radial basis functions, mapping, geographical information systems.

Glacier runoff variation and its influence on river runoff during 1961–2006 in the Tarim River Basin, China

Using monthly precipitation and temperature data from national meteorological stations, 90 m resolution DEM and a digital vector map of modern glaciers from the Chinese Glacier Inventory, the glacier mass balance and glacier runoff in the Tarim River Basin (TRB), China, were estimated based on a monthly degree-day model for 1961–2006. The results suggest that the modified monthly degree-day model can simulate the long-term changes in glacier mass balance and glacier runoff, which have been confirmed by short-term observation data and other results in literatures. The characteristics and trends of mass balance and glacier runoff variation were analyzed. It was found that the mean annual glacier mass balance during 1961–2006 was −139.2 mm per year and the cumulative mass balance over the 46 year period was −6.4 m in the TRB. The glacier mass balance displayed a clear decreasing trend over the entire TRB during 1961–2006. The average annual glacier runoff in the TRB was 144.16×108 m3 for 1961–2006. The results also show that glacier runoff has increased in the last 46 years, especially since the 1990s with 85.7% of the increased river flow being derived from the increased glacier runoff caused by loss of ice mass. Over the entire TRB, glacier runoff accounts for 41.5% of the total river flow during 1961–2006. The impact of glacier runoff on river flow has increased in the TRB as a result of glacier shrinkage.

Geocoding of Synthetic Aperture Radar Images Using Digital Vector Maps

In this letter, a possible approach to automate synthetic aperture radar (SAR) geocoding (or to automatically refine the existing one) is presented. The procedure is based on edge detection, where ground control lines obtained from digital vector maps are located in the SAR images. In geocoding, affine, projective, and rigorous SAR sensor transformation models can be used. According to the experiments, the procedure seems to be accurate and reliable as long as the initial values of the geocoding transformation model are accurate enough. The procedure copes well with displacements of about ten pixels on SAR images, but good results have been obtained in cases of even larger displacements. According to the well-defined checkpoints, the resulting geocoding accuracies for test images were around a few pixels. When the rigorous SAR sensor model was used, the accuracies were less than two pixels in most cases.

Determination of Exterior Orientation Using Linear Features from Vector Maps

AbstractThis paper presents a procedure for the determination of the exterior orientation (EO) of images using existing digital vector maps. The most important characteristic is that there is no need for signalised ground control points (GCPs), because the EO is carried out solely using ground control lines (GCLs) acquired from the geographical information system (GIS). Although the proposed EO procedure could be fully automated, a small amount of operator guidance is needed in the adjustment of the initial EO, which should be moderately accurate prior to automating the EO procedure. However, adjusting the initial EO parameters is fairly easy, because the projected locations of the map vectors on the image are updated in real time on the computer monitor. Ultimately, the final EO is determined by using an automatic method that uses a local line scanning technique that attempts to locate the linear features from the image. The final EO is calculated using the line photogrammetry method. The EO procedure was implemented as software running in a Microsoft Windows environment and, although the software is able to process only one image at a time, it provides a way to determine the EO that is both reliable and rapid. The test results showed that the accuracy achieved depends on the positional accuracy of the linear features used. Therefore, 2D coordinate shifts in the vector maps will be directly passed to the EO parameters without other control.

3D Building Modelling with Digital Map, Lidar Data and Video Image Sequences

AbstractThree‐dimensional (3D) reconstruction and texture mapping of buildings or other man‐made objects are key aspects for 3D city landscapes. An effective coarse‐to‐fine approach for 3D building model generation and texture mapping based on digital photogrammetric techniques is proposed. Three video image sequences, two oblique views of building walls and one vertical view of building roofs, acquired by a digital video camera mounted on a helicopter, are used as input images. Lidar data and a coarse two‐dimensional (2D) digital vector map used for car navigation are also used as information sources. Automatic aerial triangulation (AAT) suitable for a high overlap image sequence is used to give initial values of camera parameters of each image. To obtain accurate image lines, the correspondence between outlines of the building and their line features in the image sequences is determined with a coarse‐to‐fine strategy. A hybrid point/line bundle adjustment is used to ensure the stability and accuracy of reconstruction. Reconstructed buildings with fine textures superimposed on a digital elevation model (DEM) and ortho‐image are realistically visualised. Experimental results show that the proposed approach of 3D city model generation has a promising future in many applications.

Vegetation growth zonation of Sri Lanka for improved water resources planning

Water resources planning depends on the physical environments, notably on the vegetation and hydrological conditions in river basins. Vegetation growth—both natural and human induced—has a strong dynamic behavior which, especially at larger scales, is difficult to survey in the field. Low cost imagery from the NOAA–AVHRR satellite provides new opportunities to estimate vegetation development and biomass production. Composite maps of biomass production were compiled as the primary basis to establish a growth zone classification. A total of 92 vegetation growth zones were delineated by visual interpretation. Digital vector maps of land use and soil type, as well as digital raster maps of moisture availability index, soil moisture and actual evapotranspiration have been explored to describe vegetation growth zones from satellite data. These vegetation growth zones will contribute more to water resources planning than existing agro-ecological zonations and land use mapping, because vegetation growth is based on the environment and has strong linkages with the hydrological processes occurring in different parts of the basin. It provides a vehicle to relate water demand and water use in river basins to various types of vegetation.