3D Visualisation & DTM/DEM Modelling | Unistal.com

3D Visualization & DEM/DTM Modeling

3D Visualisation & DTM/DEM Modelling

  • Integrated Pipeline Network
  • 3D Models on Civil 3D
  • 3D Pipeline Alignment & Terrain Modeling
  • CAD/GIS Based Alignment Sheet Generation

Technical Objective

Today the availability of using the high-resolution space imagery, the complex mathematical computational strength of server and GIS technology has created a positive environment on the application of “Geo-remote sensing based scientific computing” technology for designing of the new alignment for pipelines.

The objective is to evaluate the 3D Geospatial Modelling, stereo pair remote sensing technology and 3D visualization technology for designing, development and production of AS-BUILT drawings.

Pipeline Alignment, Terrain Modelling and 3D Visualization:

Unlike the traditional way of designing the Oil & Gas pipeline alignment in which the design engineer manually tries to find out the alternative routes to access areas scheduled for harvest, or a rocky terrain difficult to dig/construct or a difficult crossing features like rail, river etc which may be difficult to negotiate during construction and may delay the progress, a computer-aided 3D geospatial digital terrain Modelling would be the best and technically advance way of addressing the need where the alternative pipeline alignments can be visualized in 3D interactive model. The engineering and socio-economic feasibility can be done on the model and once agreed to final alignment; the cost of the project and working detail drawing (alignment sheets) can be quickly derived out using 3D geospatial terrain model.

The 3D engineering model of final alignment will be used both during the initial phase of planning and also throughout the project life. Once the model is ready it will be used during the construction phase to monitor the progress and once the project is on, it will be used to overlay the HCA and integrity matrix of alignment section.

Computer-aided 3D geospatial digital alignment on terrain model will be comprised of multidisciplinary design data into visually rich virtual reality presentation that everybody can understand and view interactively. This results in more efficient communication, better design solutions and notable time and cost savings. When integrated into the design process, it makes sure that project parties succeed and goals are achieved. Virtual Map truly adds new dimensions into the design process.

The key features of 3D model will be as following:

  • Superior visual communication
  • Easy to use
  • Fun and inspiring – professional presentation
  • Design simulation
  • Design Analysis
  • Earth work quality management
  • Cross section view
  • Plan, longitudinal profile, cross-sections and 3D presentation
  • Notable time and cost savings
  • Real-time Construction visualization and progress management
  • Applicable till entire life of the project
  • Integrated engineering from design to drawing followed by visualization – All in 3D

Further, during all design phases, it is important to be able to present the project in a professional manner. Users can activate pre-defined viewpoints and movement paths or move inside the Computer-aided 3D geospatial digital alignment on the terrain model freely using many different navigation modes. Tools like measuring, groups, object info, search and document links add new dimensions to presentations. It is also possible to save images and animation videos. But most importantly, Virtual Map activates people to communicate and give valuable feedback.

Nowadays, it is beneficial to do what we call “Integration Modelling”. It means a dynamically updated virtual model of all design data from all design domains. During the whole design process, the model is updated constantly to reflect the current design status. The designs can be reviewed using the virtual model instead of multiple paper prints. Viewing the design as a 3D virtual model (3D Visualization) gives the design process, a whole new perspective. Conflicts like colliding structures, visibility obscuring objects, bad quality geometry or just unnoticed elements are immediately seen in the virtual model. The conflicts on crossing features can be saved as viewpoints with comments and can be sent back to the designers for fixing. This is an innovative new way of working and results in much better project management and better solutions.

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  • Site selection and location analysis
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3D Terrain:

A digital elevation model is a digital model or 3D representation of a terrain’s surface. It is created from terrain elevation data. In most cases, the term digital surface model (DSM) represents the surface and includes all the objects on it. In contrast to a DSM, the digital terrain model (DTM) represents the bare ground surface without any objects like plants and buildings. Once satellite stereo feature data is overlaid on the DTM, it becomes DSM.

Digital elevation models can be developed in a number of ways, but they frequently use remote sensing rather than direct survey data, which is always recommended. One powerful technique for generating digital elevation models is interferometric synthetic aperture radar: two passes of a radar satellite (such as RADARSAT-1 or TerraSAR-X), or a single pass if the satellite is equipped with two antennas (like the SRTM instrumentation), is enough to generate a digital elevation map tens of kilometers on a side with a resolution of around a meters. Alternatively, other kinds of stereoscopic pairs can be employed using the digital image correlation method, where two optical images acquired with different angles taken from the same pass of an airplane or an Earth Observation Satellite (such as the HRS instrument of SPOT5 or the VNIR band of ASTER).

Older methods of generating DEMs often involve interpolating digital contour maps that may have been produced by a direct survey of the land surface. This method is not very much in practice provided it is not a dense forest and in such cases, the DGPS is used to capture the spot elevation.

Further with DGPS, the quality of a DEM is a measure of how accurate elevation is at each pixel (absolute accuracy) and how accurately is the morphology presented (relative accuracy). Several factors play an important role in the quality of DEM-derived products:

  • Terrain roughness;
  • Sampling density (elevation data collection method);
  • Grid resolution or pixel size;
  • Interpolation algorithm;
  • Vertical resolution;
  • Terrain analysis algorithm;

Following are the input used to develop the DTM model

  • Stereo Satellite imageries (4 Mts LISS)
  • Real Time Kinematic GPS
  • Topographic maps
  • Total station
  • GCPs taken by DGPS
  • Inertial surveys
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Remote Sensing – The Technology

In emerging technology paradigm, “Geographical Information System (GIS)” has emerged as a powerful tool which has the potential to organize complex spatial environment with tabular relationships between the pipeline and integrity management database. With Remote Sensing, the emphasis is on developing the digital spatial database, using the data sets derived from precise navigation and imaging satellites, aircraft, digitization of maps and transactional databases. The power and potential of GIS is limited only by one’s imagination.

However, to exploit the technology to benefit the corridor monitoring process there is a need to initiate a process for integration of data based on Interoperable open standards, specifications & formats. In recent years, the enormous demand for the storage, analysis and display of complex and voluminous data has led, to the use of Geographic Information Systems (GIS) for effective data handling and also for analyzing and geographically transferring the information around the corridor. It is, therefore, essential to devise the ways and means of organizing computerized pipeline corridor information system. These systems must be capable of handling a vast amount of data collected by modern techniques and produce up to date information. Remote Sensing technology has already demonstrated its capabilities to provide information on natural resources, soil pattern change, unwanted activities prediction, unwanted land-use, soil erosion, etc on a regular basis. Similarly, Geographic Information Systems (GIS) are the latest tools available to store, retrieve and analyze different types of data for the management of natural resources. Remote Sensing technology and GIS facilitates the systematic handling of data to generate information in a devised format. Thus it plays an important role in evolving alternate scenarios for natural resources management.

Remote Sensing (RS) data and Geographical Information System (GIS) play a rapidly increasing role in the field of pipeline corridor monitoring. One of the greatest advantages of using data for corridor change deduction modelling and monitoring is its ability to generate information in a spatial and temporal domain, which is very crucial for successful model analysis, prediction and validation. However, the use of this technology involves a large amount of spatial data management and requires an efficient system to handle such data. The GIS technology provides suitable alternatives for efficient management of large and complex databases.

Image data have been used as a primary source of natural resources information in thematic mapping which in turn is utilized in various corridor health studies. The remote sensing data provides a synoptic view of a fairly large area in the narrow and discrete bands of the electromagnetic spectrum at regular intervals. The space borne multispectral data enable generating timely, reliable and cost-effective information on various natural resources, namely surface water, ground-water, land use/cover, soil, forest cover and environmental hazards, namely water logging, salinity and alkalinity, soil erosion, human activities, etc.

Remote Sensing Technology Assessment:

There are airborne, unmanned aerial vehicles (UAV), satellite Synthetic Aperture Radar, LIDAR multi-spectral and hyper-spectral sensors could be used for pipeline monitoring. But one of “Proof of Concept” i.e. the feasibility study of appropriate satellite imageries and associated technology for monitoring transmission network needs to be tested out before implementing it across the entire network of Pipeline Operators. The objective of this approach is to ensure:

  • The kind of satellite imageries required
  • Frequency of satellite data depending on cloud conditions
  • Process of its procurement
  • Mathematical model for image processing
  • Tools and technology required
  • Data Modelling
  • Data safety& security
  • Integration of systems
  • Proposed automation to be included in the solution
  • Survey needs
  • Definition of warning, notification, alarm and alert
  • An integrated system definition
  • Expected cost and duration

DGPS Survey for capturing GCP’s

The Ground Control Points (GCP) were established in the corners of the forecasted imagery blocks and the center of each block. Additional GCP’s were added in strategic locations of the blocks, depending on the shapes of blocks and the number of the strips covering the area.

A sufficient number of GCP’s from DGPS survey were made available and ensuring that maximum AT block stability and accuracy is achieved.

The accuracy of these GCPs will be smaller or equal to + 1M

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Retracing and Pegging of TP’s using Total Survey Station

In order to peg the Turning Points on the ground, they were re-traced using Total Survey Station and peg was installed.

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DGPS Survey of all TP’s and Crossings

Features mapped while carrying out Survey are;


  • TP’s
  • IP’s
  • GCP’s


  • Roads
  • Highways
  • Canals
  • Power Lines
  • Water Bodies

In order to peg the Turning Points on the ground, they were re-traced using Total Survey Station and peg was installed.

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Feature Extraction from Satellite Imagery.

Analysis of existing data: It is important to analyze the existing data (maps, satellite images, tables and reports) available with pipeline operator. A process of verification was carried out on the existing data for the authentication of the quality. What is checked? – The attributes, errors of undershoots & overshoots, locations, connectivity, etc.

For the base map creation, some raster maps (toposheets, satellite images and other paper maps) were scanned and converted to the digital format. Then, digitization is carried out and DGPS survey data integrated with the GIS data layers. A process of geocoding the details of the survey data and other attributes were done in a GIS environment. Then the final DGPS survey data was published on the web server system for the client verification and other users availability.

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Preliminary Alignment :

The preliminary alignment was placed on the Google map to ensure the corridor and TPs. The TPs were surveyed using DGPS and high-resolution satellite image and stereo pair generated DTM was used to refine the alignment

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Satellite image processing and Ortho photo generation

Satellite data comes in binary format. Extracting the valuable information from satellite needs to convert the binary DN values into a representative FCC colored image. This is known as image processing. In ATF pipeline two images were used, (a) PAN (1 M, single band) and Multispectral (3 band – RBG; 4 M). These images were merged to sharpen the data. SOI and GCPs were used to develop the ortho photo generation.

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Histogram equalization is done to sharpen the image to the best pixel level. Satellite images acquired through satellite sensors contain camera and terrain related distortions which make the images unsuitable for geospatial analysis, and DTM Modelling as positions within the image may be significantly inaccurate. Orthorectification converts imagery into map-accurate form by removing camera and terrain related distortions from the imagery through the use of sensor and terrain (elevation) information. The resulting orthoimages, also known as ortho-maps, can be directly applied in GIS based 3D alignment for ATF line. Orthoimage generation is mathematical modelling for establishing relationship between object and pixel space. This mathematical modelling is determined by the exterior orientation with the use of extended co-linearity equations and GCPs. Since Space Imaging (SI) does not release information about the sensor model and no typical Rational Polynomial Coefficient can be used as this modelling is very much dependent on geography, altitude and terrain slope.

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A Digital Elevation Model (DEM) is a regularly spaced raster grid of elevation values of a surface terrain. DEMs can be used to produce maps such as contour maps, orthophoto maps, and perspective maps. DEMs can be used to exactly map the surface terrain which will be ultimately deployed for 3D line planning and design. The DEM Extraction Module enables the extraction of elevation data from stereo images –which came from satellite imagery. It is important that the imagery has associated rational polynomial coefficients (RPCs) which contain necessary information about the sensor model. In addition, RPCs are used in tie point generation and to calculate the stereo image pair relationship.

The DEM extraction process requires a stereo pair of images containing RPC positioning from either along track or across track satellite acquisition. Along track, stereo images are acquired on the same orbital pass by a satellite which usually has more than one sensor looking at the Earth from different angles. Across track stereo images are those taken by the same sensor on multiple orbits.

DEM extraction is a multi-step decision-making process involving the setting of many parameters used in different steps. These steps can be run individually from the ERDAS menu options, or from within the DEM Extraction Wizard. The Wizard guides you through nine steps. It presents you with objective parameters, such as minimum/maximum elevation of the area of interest, as well as other strategy parameters that depend upon the terrain relief, cultural content, image quality, shadowing, and the desired speed of operation.

As with the DEM Extraction Wizard, extracting a relative or absolute DEM from a stereo pair of images can be accomplished using the Stereo Pair 3D Measurement Tool and Epipolar 3D Cursor Tool to create an output DEM.

The Stereo Pair 3D Measurement Tool allows you to select a common point from two stereo images and calculate an elevation value for that point.

The Epipolar 3D Cursor tool performs 3D measurements in a 3D stereo viewing environment based on an existing epipolar stereo pair of images. It is easy to view an anaglyph of epipolar stereo imagery and adjust the apparent height of the cursor to extract elevation data.

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Creating a DEM

There are three steps in creating a DEM that are crucial to generating acceptable results: epipolar image creation, image matching, and DEM geocoding.

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Epipolar Image Creation – The creation of epipolar images is an essential processing step in DEM extraction. Epipolar geometry describes the geometrical constraint between two frame images of a stereo pair. It represents the fact that a ground point and the two optical centres lie on the same plane. This means that for a given point in one image, its conjugate point in the other image must lie on a known line in the second image. By creating epipolar images, the search space for finding corresponding image points in automatic image matching is reduced. For information about building epipolar images for use with DEM Extraction Wizard, see Building Epipolar Images.

Image Matching – Image matching finds the conjugate points on both the left and right images which correspond to the same ground feature. The output of the image matching procedure is called a parallax image, in which the x-coordinate difference (along epipolar lines) between the left and right image is stored and is used to build the DEM. Thus, the quality of image matching largely determines the quality of the output DEM.

DEM Geocoding – DEM geocoding re-projects the DEM from the epipolar projection to the user-specified output map projection and units. This step involves the filling of failed pixels and resampling to a pixel spacing specified by the user. When GCPs are provided, the absolute orientation of the computed terrain model is performed in this step.

Output DEM

A relative DEM is a DEM with possible differences in position, scale, and rotation from the geodetic coordinates on the ground (horizontal reference system) and the mean sea level (vertical reference system). If the satellite imagery does not have ground control point (GCP) information associated with it, the DEM Extraction Wizard can derive a relative DEM result.

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An absolute DEM was developed in the pipeline project as the horizontal and vertical reference systems tied to geodetic coordinates. This help to develop the entire alignment in 3D on a single GIS+ DTM model.

DTM Overlay on Satellite Land Use:

The DTM (Elevation data) was overlaid on the 2D pan sharpened satellite image and a 750 Mts either side buffer was created. This model was taken into Civil 3D module for pipeline alignment.

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DTM+ Pan Sharpen Image of Buffer

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Ground Surface model:

The DTM and Satellite image was taken into Civil 3D. The centerline land coordinates were available. The TIN model was developed to define the ground surface model as shown below.

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Pipeline Centerline Alignment in Civil 3D

In Civil 3D the IPs were placed. The centerline object (3D polyline) was placed passing through the IPs. The circular arcs and spirals were fitted at every IPs ensuring R>400D criteria. The vertical section along the terrain was derived from the DTM in Civil 3D environment. The alignments are combined with profiles and assemblies (cross sections) to create 3D design models called 3D centerline.

Alignments in Civil 3D are dynamic objects linked to the profiles and corridors that depend on them, which means that changing an alignment through a table of design data or through on-screen grip editing automatically redefines the alignment and updates profiles and corridors accordingly.

Object Styles

Civil 3D uses object styles were developed as per clients design template to control the display and annotation of objects such as points, alignments, profiles and so on. Alignment geometry and labels automatically appear in the alignments in real-time based on selected alignment styles and alignment label styles.

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Creating Alignments

In Civil 3D from polylines passing through TPs fitted with circular and spiral curves (R> 40D) was used to develop the vertical alignment. It was developed by joined polyline with Alignments/Create Alignment from Polyline to ensure that every cross-section complies with design. This approach found best as it was real-time computing the depth of pipeline from the soil surface.

Typical As-Built layout was used to develop the construction drawings.

Extraction of model:

The Civil 3D model with terrain was extracted out into infrastructural modeller for development of 3D virtual Digital City Pipeline visualization.

Cutting the Corridor on Satellite Imagery

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2D Alignment Sheet Generation

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Planimetry Alignment

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3D Alignment Sheets

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Development of 3D visualization and animation using DTM

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Terrain with pipeline trace on the ground

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Terrain tilted to horizon view (same view frame as above)

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